Merge branch 'master' into USER-DPD_kokkos

This commit is contained in:
Stan Moore 2017-08-23 15:20:56 -06:00
commit cbf3646806
1033 changed files with 74799 additions and 41892 deletions

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\documentclass[12pt]{article}
\begin{document}
$$
v(t+\frac{\Delta t}{2}) = v(t) + \frac{\Delta t}{2}\cdot a(t),
$$
$$
r(t+\Delta t) = r(t) + \Delta t\cdot v(t+\frac{\Delta t}{2}),
$$
$$
a(t+\Delta t) = \frac{1}{m}\cdot F\left[ r(t+\Delta t), v(t) +\lambda \cdot \Delta t\cdot a(t)\right],
$$
$$
v(t+\Delta t) = v(t+\frac{\Delta t}{2}) + \frac{\Delta t}{2}\cdot a(t++\Delta t),
$$
\end{document}

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\documentclass[12pt]{article}
\begin{document}
$$
\mathbf{F}_{ij}^{C} = \alpha_{ij}{\omega_{C}}(r_{ij})\mathbf{e}_{ij},
$$
$$
\mathbf{F}_{ij}^{D} = -\gamma {\omega_{D}}(r_{ij})(\mathbf{e}_{ij} \cdot \mathbf{v}_{ij})\mathbf{e}_{ij},
$$
$$
\mathbf{F}_{ij}^{R} = \sigma {\omega_{R}}(r_{ij}){\xi_{ij}}\Delta t^{-1/2} \mathbf{e}_{ij},
$$
$$
\omega_{C}(r) = 1 - r/r_c,
$$
$$
\alpha_{ij} = A\cdot k_B(T_i + T_j)/2,
$$
$$
\omega_{D}(r) = \omega^2_{R}(r) = (1-r/r_c)^s,
$$
$$
\sigma_{ij}^2 = 4\gamma k_B T_i T_j/(T_i + T_j),
$$
\end{document}

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\documentclass[12pt]{article}
\begin{document}
$$
\frac{\mathrm{d}^2 \mathbf{r}_i}{\mathrm{d} t^2}=
\frac{\mathrm{d} \mathbf{v}_i}{\mathrm{d} t}
=\mathbf{F}_{i}=\sum_{i\neq j}(\mathbf{F}_{ij}^{C}+\mathbf{F}_{ij}^{D}+\mathbf{F}_{ij}^{R}),
$$
$$
C_v\frac{\mathrm{d} T_i}{\mathrm{d} t}= q_{i} = \sum_{i\neq j}(q_{ij}^{C}+q_{ij}^{V}+q_{ij}^{R}),
$$
\end{document}

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\documentclass[12pt]{article}
\begin{document}
$$
q_i^C = \sum_{j \ne i} k_{ij} \omega_{CT}(r_{ij}) \left( \frac{1}{T_i} - \frac{1}{T_j} \right),
$$
$$
q_i^V = \frac{1}{2 C_v}\sum_{j \ne i}{ \left\{ \omega_D(r_{ij})\left[\gamma_{ij} \left( \mathbf{e}_{ij} \cdot \mathbf{v}_{ij} \right)^2 - \frac{\left( \sigma _{ij} \right)^2}{m}\right] - \sigma _{ij} \omega_R(r_{ij})\left( \mathbf{e}_{ij} \cdot \mathbf{v}_{ij} \right){\xi_{ij}} \right\} },
$$
$$
q_i^R = \sum_{j \ne i} \beta _{ij} \omega_{RT}(r_{ij}) d {t^{ - 1/2}} \xi_{ij}^e,
$$
$$
\omega_{CT}(r)=\omega_{RT}^2(r)=\left(1-r/r_{ct}\right)^{s_T},
$$
$$
k_{ij}=C_v^2\kappa(T_i + T_j)^2/4k_B,
$$
$$
\beta_{ij}^2=2k_Bk_{ij},
$$
\end{document}

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\documentclass[12pt]{article}
\begin{document}
$$
\kappa = \frac{315k_B\upsilon }{2\pi \rho C_v r_{ct}^5}\frac{1}{Pr},
$$
\end{document}

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\documentclass[12pt]{article}
\begin{document}
$$
\mathbf{F}_{ij}^C = Aw_c(r_{ij})\mathbf{e}_{ij} + B(\rho_i+\rho_j)w_d(r_{ij})\mathbf{e}_{ij},
$$
$$
\mathbf{F}_{ij}^{D} = -\gamma {\omega_{D}}(r_{ij})(\mathbf{e}_{ij} \cdot \mathbf{v}_{ij})\mathbf{e}_{ij},
$$
$$
\mathbf{F}_{ij}^{R} = \sigma {\omega_{R}}(r_{ij}){\xi_{ij}}\Delta t^{-1/2} \mathbf{e}_{ij},
$$
\end{document}

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\documentclass[12pt]{article}
\begin{document}
$$
Q_{ij}^D = -\kappa_{ij} w_{DC}(r_{ij}) \left( C_i - C_j \right),
$$
$$
Q_{ij}^R = \epsilon_{ij}\left( C_i + C_j \right) w_{RC}(r_{ij}) \xi_{ij},
$$
$$
w_{DC}(r_{ij})=w^2_{RC}(r_{ij}) = (1 - r/r_{cc})^{\rm power\_{cc}},
$$
$$
\epsilon_{ij}^2 = m_s^2\kappa_{ij}\rho,
$$
\end{document}

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\documentclass[12pt]{article}
\begin{document}
$$
\mathbf{F}_{ij}^{C} = A{\omega_{C}}(r_{ij})\mathbf{e}_{ij},
$$
$$
\mathbf{F}_{ij}^{D} = -\gamma {\omega_{D}}(r_{ij})(\mathbf{e}_{ij} \cdot \mathbf{v}_{ij})\mathbf{e}_{ij},
$$
$$
\mathbf{F}_{ij}^{R} = \sigma {\omega_{R}}(r_{ij}){\xi_{ij}}\Delta t^{-1/2} \mathbf{e}_{ij},
$$
$$
\omega_{C}(r) = 1 - r/r_c,
$$
$$
\omega_{D}(r) = \omega^2_{R}(r) = (1-r/r_c)^{\rm power\_f},
$$
$$
\sigma^2 = 2\gamma k_B T,
$$
\end{document}

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\documentclass[12pt]{article}
\begin{document}
$$
\frac{\mathrm{d}^2 \mathbf{r}_i}{\mathrm{d} t^2} = \frac{\mathrm{d} \mathbf{v}_i}{\mathrm{d} t}=\mathbf{F}_{i}=\sum_{i\neq j}(\mathbf{F}_{ij}^{C}+\mathbf{F}_{ij}^{D}+\mathbf{F}_{ij}^{R}),
$$
$$
\frac{\mathrm{d} C_{i}}{\mathrm{d} t}= Q_{i} = \sum_{i\neq j}(Q_{ij}^{D}+Q_{ij}^{R}) + Q_{i}^{S},
$$
\end{document}

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@ -685,6 +685,7 @@ package"_Section_start.html#start_3.
"drude"_fix_drude.html,
"drude/transform/direct"_fix_drude_transform.html,
"drude/transform/reverse"_fix_drude_transform.html,
"edpd/source"_fix_dpd_source.html,
"eos/cv"_fix_eos_cv.html,
"eos/table"_fix_eos_table.html,
"eos/table/rx"_fix_eos_table_rx.html,
@ -704,6 +705,9 @@ package"_Section_start.html#start_3.
"meso"_fix_meso.html,
"manifoldforce"_fix_manifoldforce.html,
"meso/stationary"_fix_meso_stationary.html,
"mvv/dpd"_fix_mvv_dpd.html,
"mvv/edpd"_fix_mvv_dpd.html,
"mvv/tdpd"_fix_mvv_dpd.html,
"nve/dot"_fix_nve_dot.html,
"nve/dotc/langevin"_fix_nve_dotc_langevin.html,
"nve/manifold/rattle"_fix_nve_manifold_rattle.html,
@ -732,6 +736,7 @@ package"_Section_start.html#start_3.
"smd/move/triangulated/surface"_fix_smd_move_triangulated_surface.html,
"smd/setvel"_fix_smd_setvel.html,
"smd/wall/surface"_fix_smd_wall_surface.html,
"tdpd/source"_fix_dpd_source.html,
"temp/rescale/eff"_fix_temp_rescale_eff.html,
"ti/spring"_fix_ti_spring.html,
"ttm/mod"_fix_ttm.html,
@ -775,6 +780,7 @@ KOKKOS, o = USER-OMP, t = OPT.
"erotate/sphere"_compute_erotate_sphere.html,
"erotate/sphere/atom"_compute_erotate_sphere_atom.html,
"event/displace"_compute_event_displace.html,
"fragment/atom"_compute_cluster_atom.html,
"global/atom"_compute_global_atom.html,
"group/group"_compute_group_group.html,
"gyration"_compute_gyration.html,
@ -836,6 +842,7 @@ package"_Section_start.html#start_3.
"cnp/atom"_compute_cnp_atom.html,
"dpd"_compute_dpd.html,
"dpd/atom"_compute_dpd_atom.html,
"edpd/temp/atom"_compute_edpd_temp_atom.html,
"fep"_compute_fep.html,
"force/tally"_compute_tally.html,
"heat/flux/tally"_compute_tally.html,
@ -868,6 +875,7 @@ package"_Section_start.html#start_3.
"smd/ulsph/stress"_compute_smd_ulsph_stress.html,
"smd/vol"_compute_smd_vol.html,
"stress/tally"_compute_tally.html,
"tdpd/cc/atom"_compute_tdpd_cc_atom.html,
"temp/drude"_compute_temp_drude.html,
"temp/eff"_compute_temp_eff.html,
"temp/deform/eff"_compute_temp_deform_eff.html,
@ -1024,6 +1032,7 @@ package"_Section_start.html#start_3.
"eam/cd (o)"_pair_eam.html,
"edip (o)"_pair_edip.html,
"edip/multi"_pair_edip.html,
"edpd"_pair_meso.html,
"eff/cut"_pair_eff.html,
"exp6/rx"_pair_exp6_rx.html,
"gauss/cut"_pair_gauss.html,
@ -1041,6 +1050,8 @@ package"_Section_start.html#start_3.
"lj/sdk (gko)"_pair_sdk.html,
"lj/sdk/coul/long (go)"_pair_sdk.html,
"lj/sdk/coul/msm (o)"_pair_sdk.html,
"mdpd"_pair_meso.html,
"mdpd/rhosum"_pair_meso.html,
"meam/c"_pair_meam.html,
"meam/spline (o)"_pair_meam_spline.html,
"meam/sw/spline"_pair_meam_sw_spline.html,
@ -1074,6 +1085,7 @@ package"_Section_start.html#start_3.
"sph/taitwater/morris"_pair_sph_taitwater_morris.html,
"srp"_pair_srp.html,
"table/rx"_pair_table_rx.html,
"tdpd"_pair_meso.html,
"tersoff/table (o)"_pair_tersoff.html,
"thole"_pair_thole.html,
"tip4p/long/soft (o)"_pair_lj_soft.html :tb(c=4,ea=c)

View File

@ -112,7 +112,7 @@ Package, Description, Doc page, Example, Library
"REPLICA"_#REPLICA, multi-replica methods, "Section 6.6.5"_Section_howto.html#howto_5, tad, -
"RIGID"_#RIGID, rigid bodies and constraints, "fix rigid"_fix_rigid.html, rigid, -
"SHOCK"_#SHOCK, shock loading methods, "fix msst"_fix_msst.html, -, -
"SNAP"_#SNAP, quantum-fitted potential, "pair snap"_pair_snap.html, snap, -
"SNAP"_#SNAP, quantum-fitted potential, "pair_style snap"_pair_snap.html, snap, -
"SRD"_#SRD, stochastic rotation dynamics, "fix srd"_fix_srd.html, srd, -
"VORONOI"_#VORONOI, Voronoi tesselation, "compute voronoi/atom"_compute_voronoi_atom.html, -, ext :tb(ea=c,ca1=l)
@ -134,6 +134,7 @@ Package, Description, Doc page, Example, Library
"USER-LB"_#USER-LB, Lattice Boltzmann fluid,"fix lb/fluid"_fix_lb_fluid.html, USER/lb, -
"USER-MANIFOLD"_#USER-MANIFOLD, motion on 2d surfaces,"fix manifoldforce"_fix_manifoldforce.html, USER/manifold, -
"USER-MEAMC"_#USER-MEAMC, modified EAM potential (C++), "pair_style meam/c"_pair_meam.html, meam, -
"USER-MESO"_#USER-MESO, mesoscale DPD models, "pair_style edpd"_pair_meso.html, USER/meso, -
"USER-MGPT"_#USER-MGPT, fast MGPT multi-ion potentials, "pair_style mgpt"_pair_mgpt.html, USER/mgpt, -
"USER-MISC"_#USER-MISC, single-file contributions, USER-MISC/README, USER/misc, -
"USER-MOLFILE"_#USER-MOLFILE, "VMD"_vmd_home molfile plug-ins,"dump molfile"_dump_molfile.html, -, ext
@ -1342,7 +1343,7 @@ make machine :pre
[Supporting info:]
src/SNAP: filenames -> commands
"pair snap"_pair_snap.html
"pair_style snap"_pair_snap.html
"compute sna/atom"_compute_sna_atom.html
"compute snad/atom"_compute_sna_atom.html
"compute snav/atom"_compute_sna_atom.html
@ -1556,7 +1557,7 @@ make machine :pre
src/USER-AWPMD: filenames -> commands
src/USER-AWPMD/README
"pair awpmd/cut"_pair_awpmd.html
"pair_style awpmd/cut"_pair_awpmd.html
examples/USER/awpmd :ul
:line
@ -1745,12 +1746,12 @@ src/USER-DPD: filenames -> commands
"fix eos/table/rx"_fix_eos_table_rx.html
"fix shardlow"_fix_shardlow.html
"fix rx"_fix_rx.html
"pair table/rx"_pair_table_rx.html
"pair dpd/fdt"_pair_dpd_fdt.html
"pair dpd/fdt/energy"_pair_dpd_fdt.html
"pair exp6/rx"_pair_exp6_rx.html
"pair multi/lucy"_pair_multi_lucy.html
"pair multi/lucy/rx"_pair_multi_lucy_rx.html
"pair_style table/rx"_pair_table_rx.html
"pair_style dpd/fdt"_pair_dpd_fdt.html
"pair_style dpd/fdt/energy"_pair_dpd_fdt.html
"pair_style exp6/rx"_pair_exp6_rx.html
"pair_style multi/lucy"_pair_multi_lucy.html
"pair_style multi/lucy/rx"_pair_multi_lucy_rx.html
examples/USER/dpd :ul
:line
@ -1785,8 +1786,8 @@ src/USER-DRUDE/README
"fix drude"_fix_drude.html
"fix drude/transform/*"_fix_drude_transform.html
"compute temp/drude"_compute_temp_drude.html
"pair thole"_pair_thole.html
"pair lj/cut/thole/long"_pair_thole.html
"pair_style thole"_pair_thole.html
"pair_style lj/cut/thole/long"_pair_thole.html
examples/USER/drude
tools/drude :ul
@ -1824,8 +1825,8 @@ src/USER-EFF/README
"fix npt/eff"_fix_nh_eff.html
"fix langevin/eff"_fix_langevin_eff.html
"compute temp/eff"_compute_temp_eff.html
"pair eff/cut"_pair_eff.html
"pair eff/inline"_pair_eff.html
"pair_style eff/cut"_pair_eff.html
"pair_style eff/inline"_pair_eff.html
examples/USER/eff
tools/eff/README
tools/eff
@ -2155,11 +2156,47 @@ make machine :pre
src/USER-MEAMC: filenames -> commands
src/USER-MEAMC/README
"pair meam/c"_pair_meam.html
"pair_style meam/c"_pair_meam.html
examples/meam :ul
:line
USER-MESO package :link(USER-MESO),h4
[Contents:]
Several extensions of the the dissipative particle dynamics (DPD)
method. Specifically, energy-conserving DPD (eDPD) that can model
non-isothermal processes, many-body DPD (mDPD) for simulating
vapor-liquid coexistence, and transport DPD (tDPD) for modeling
advection-diffuion-reaction systems. The equations of motion of these
DPD extensions are integrated through a modified velocity-Verlet (MVV)
algorithm.
[Author:] Zhen Li (Division of Applied Mathematics, Brown University)
[Install or un-install:]
make yes-user-meso
make machine :pre
make no-user-meso
make machine :pre
[Supporting info:]
src/USER-MESO: filenames -> commands
src/USER-MESO/README
"atom_style edpd"_atom_style.html
"pair_style edpd"_pair_meso.html
"pair_style mdpd"_pair_meso.html
"pair_style tdpd"_pair_meso.html
"fix mvv/dpd"_fix_mvv.html
examples/USER/meso
http://lammps.sandia.gov/movies.html#mesodpd :ul
:line
USER-MOLFILE package :link(USER-MOLFILE),h4
[Contents:]

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@ -13,17 +13,19 @@ atom_style command :h3
atom_style style args :pre
style = {angle} or {atomic} or {body} or {bond} or {charge} or {dipole} or \
{dpd} or {electron} or {ellipsoid} or {full} or {line} or {meso} or \
{molecular} or {peri} or {smd} or {sphere} or {tri} or \
{template} or {hybrid} :ulb,l
{dpd} or {edpd} or {mdpd} or {tdpd} or {electron} or {ellipsoid} or \
{full} or {line} or {meso} or {molecular} or {peri} or {smd} or \
{sphere} or {tri} or {template} or {hybrid} :ulb,l
args = none for any style except the following
{body} args = bstyle bstyle-args
bstyle = style of body particles
bstyle-args = additional arguments specific to the bstyle
see the "body"_body.html doc page for details
{template} args = template-ID
template-ID = ID of molecule template specified in a separate "molecule"_molecule.html command
{hybrid} args = list of one or more sub-styles, each with their args :pre
{body} args = bstyle bstyle-args
bstyle = style of body particles
bstyle-args = additional arguments specific to the bstyle
see the "body"_body.html doc page for details
{tdpd} arg = Nspecies
Nspecies = # of chemical species
{template} arg = template-ID
template-ID = ID of molecule template specified in a separate "molecule"_molecule.html command
{hybrid} args = list of one or more sub-styles, each with their args :pre
accelerated styles (with same args) = {angle/kk} or {atomic/kk} or {bond/kk} or {charge/kk} or {full/kk} or {molecular/kk} :l
:ule
@ -36,7 +38,8 @@ atom_style full
atom_style body nparticle 2 10
atom_style hybrid charge bond
atom_style hybrid charge body nparticle 2 5
atom_style template myMols :pre
atom_style template myMols
atom_style tdpd 2 :pre
[Description:]
@ -74,6 +77,9 @@ quantities.
{charge} | charge | atomic system with charges |
{dipole} | charge and dipole moment | system with dipolar particles |
{dpd} | internal temperature and internal energies | DPD particles |
{edpd} | temperature and heat capacity | eDPD particles |
{mdpd} | density | mDPD particles |
{tdpd} | chemical concentration | tDPD particles |
{electron} | charge and spin and eradius | electronic force field |
{ellipsoid} | shape, quaternion, angular momentum | aspherical particles |
{full} | molecular + charge | bio-molecules |
@ -145,6 +151,19 @@ properties with internal temperature (dpdTheta), internal conductive
energy (uCond), internal mechanical energy (uMech), and internal
chemical energy (uChem).
The {edpd} style is for energy-conserving dissipative particle
dynamics (eDPD) particles which store a temperature (edpd_temp), and
heat capacity(edpd_cv).
The {mdpd} style is for many-body dissipative particle dynamics (mDPD)
particles which store a density (rho) for considering
density-dependent many-body interactions.
The {tdpd} style is for transport dissipative particle dynamics (tDPD)
particles which store a set of chemical concentration. An integer
"cc_species" is required to specify the number of chemical species
involved in a tDPD system.
The {meso} style is for smoothed particle hydrodynamics (SPH)
particles which store a density (rho), energy (e), and heat capacity
(cv).
@ -284,6 +303,11 @@ force fields"_pair_eff.html.
The {dpd} style is part of the USER-DPD package for dissipative
particle dynamics (DPD).
The {edpd}, {mdpd}, and {tdpd} styles are part of the USER-MESO package
for energy-conserving dissipative particle dynamics (eDPD), many-body
dissipative particle dynamics (mDPD), and transport dissipative particle
dynamics (tDPD), respectively.
The {meso} style is part of the USER-SPH package for smoothed particle
hydrodynamics (SPH). See "this PDF
guide"_USER/sph/SPH_LAMMPS_userguide.pdf to using SPH in LAMMPS.

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@ -7,37 +7,62 @@
:line
compute cluster/atom command :h3
compute fragment/atom command :h3
compute aggregate/atom command :h3
[Syntax:]
compute ID group-ID cluster/atom cutoff :pre
compute ID group-ID cluster/atom cutoff
compute ID group-ID fragment/atom
compute ID group-ID aggregate/atom cutoff :pre
ID, group-ID are documented in "compute"_compute.html command
cluster/atom = style name of this compute command
{cluster/atom} or {fragment/atom} or {aggregate/atom} = style name of this compute command
cutoff = distance within which to label atoms as part of same cluster (distance units) :ul
[Examples:]
compute 1 all cluster/atom 1.0 :pre
compute 1 all cluster/atom 3.5
compute 1 all fragment/atom :pre
compute 1 all aggregate/atom 3.5 :pre
[Description:]
Define a computation that assigns each atom a cluster ID.
Define a computation that assigns each atom a cluster, fragement,
or aggregate ID.
A cluster is defined as a set of atoms, each of which is within the
cutoff distance from one or more other atoms in the cluster. If an
atom has no neighbors within the cutoff distance, then it is a 1-atom
cluster. The ID of every atom in the cluster will be the smallest
atom ID of any atom in the cluster.
cluster.
A fragment is similarly defined as a set of atoms, each of
which has an explicit bond (i.e. defined via a "data file"_read_data.html,
the "create_bonds"_create_bonds.html command, or through fixes like
"fix bond/create"_fix_bond_create.html, "fix bond/swap"_fix_bond_swap.html,
or "fix bond/break"_fix_bond_break.html). The cluster ID or fragment ID
of every atom in the cluster will be set to the smallest atom ID of any atom
in the cluster or fragment, respectively.
An aggregate is defined by combining the rules for clusters and
fragments, i.e. a set of atoms, where each of it is within the cutoff
distance from one or more atoms within a fragment that is part of
the same cluster. This measure can be used to track molecular assemblies
like micelles.
Only atoms in the compute group are clustered and assigned cluster
IDs. Atoms not in the compute group are assigned a cluster ID = 0.
IDs. Atoms not in the compute group are assigned a cluster ID = 0.
For fragments, only bonds where [both] atoms of the bond are included
in the compute group are assigned to fragments, so that only fragmets
are detected where [all] atoms are in the compute group. Thus atoms
may be included in the compute group, yes still have a fragment ID of 0.
The neighbor list needed to compute this quantity is constructed each
time the calculation is performed (i.e. each time a snapshot of atoms
is dumped). Thus it can be inefficient to compute/dump this quantity
too frequently or to have multiple compute/dump commands, each of a
{cluster/atom} style.
For computes {cluster/atom} and {aggregate/atom} the neighbor list needed
to compute this quantity is constructed each time the calculation is
performed (i.e. each time a snapshot of atoms is dumped). Thus it can be
inefficient to compute/dump this quantity too frequently or to have
multiple compute/dump commands, each of a {cluster/atom} or
{aggregate/atom} style.
NOTE: If you have a bonded system, then the settings of
"special_bonds"_special_bonds.html command can remove pairwise

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@ -0,0 +1,62 @@
"LAMMPS WWW Site"_lws - "LAMMPS Documentation"_ld - "LAMMPS Commands"_lc :c
:link(lws,http://lammps.sandia.gov)
:link(ld,Manual.html)
:link(lc,Section_commands.html#comm)
:line
compute edpd/temp/atom command :h3
[Syntax:]
compute ID group-ID edpd/temp/atom :pre
ID, group-ID are documented in "compute"_compute.html command
edpd/temp/atom = style name of this compute command :ul
[Examples:]
compute 1 all edpd/temp/atom :pre
[Description:]
Define a computation that calculates the per-atom temperature
for each eDPD particle in a group.
The temperature is a local temperature derived from the internal energy
of each eDPD particle based on the local equilibrium hypothesis.
For more details please see "(Espanol1997)"_#Espanol1997 and
"(Li2014)"_#Li2014a.
[Output info:]
This compute calculates a per-atom vector, which can be accessed by
any command that uses per-atom values from a compute as input. See
"Section 6.15"_Section_howto.html#howto_15 for an overview of
LAMMPS output options.
The per-atom vector values will be in temperature "units"_units.html.
[Restrictions:]
This compute is part of the USER-MESO package. It is only enabled if
LAMMPS was built with that package. See the "Making
LAMMPS"_Section_start.html#start_3 section for more info.
[Related commands:]
"pair_style edpd"_pair_meso.html
[Default:] none
:line
:link(Espanol1997)
[(Espanol1997)] Espanol, Europhys Lett, 40(6): 631-636 (1997). DOI:
10.1209/epl/i1997-00515-8
:link(Li2014a)
[(Li2014)] Li, Tang, Lei, Caswell, Karniadakis, J Comput Phys, 265:
113-127 (2014). DOI: 10.1016/j.jcp.2014.02.003.

View File

@ -0,0 +1,60 @@
"LAMMPS WWW Site"_lws - "LAMMPS Documentation"_ld - "LAMMPS Commands"_lc :c
:link(lws,http://lammps.sandia.gov)
:link(ld,Manual.html)
:link(lc,Section_commands.html#comm)
:line
compute tdpd/cc/atom command :h3
[Syntax:]
compute ID group-ID tdpd/cc/atom index :pre
ID, group-ID are documented in "compute"_compute.html command
tdpd/cc/atom = style name of this compute command
index = index of chemical species (1 to Nspecies) :ul
[Examples:]
compute 1 all tdpd/cc/atom 2 :pre
[Description:]
Define a computation that calculates the per-atom chemical
concentration of a specified species for each tDPD particle in a
group.
The chemical concentration of each species is defined as the number of
molecules carried by a tDPD particle for dilute solution. For more
details see "(Li2015)"_#Li2015a.
[Output info:]
This compute calculates a per-atom vector, which can be accessed by
any command that uses per-atom values from a compute as input. See
"Section 6.15"_Section_howto.html#howto_15 for an overview of
LAMMPS output options.
The per-atom vector values will be in the units of chemical species
per unit mass.
[Restrictions:]
This compute is part of the USER-MESO package. It is only enabled if
LAMMPS was built with that package. See the "Making
LAMMPS"_Section_start.html#start_3 section for more info.
[Related commands:]
"pair_style tdpd"_pair_meso.html
[Default:] none
:line
:link(Li2015a)
[(Li2015)] Li, Yazdani, Tartakovsky, Karniadakis, J Chem Phys, 143:
014101 (2015). DOI: 10.1063/1.4923254

View File

@ -30,6 +30,7 @@ Computes :h1
compute_displace_atom
compute_dpd
compute_dpd_atom
compute_edpd_temp_atom
compute_erotate_asphere
compute_erotate_rigid
compute_erotate_sphere
@ -95,6 +96,7 @@ Computes :h1
compute_sna_atom
compute_stress_atom
compute_tally
compute_tdpd_cc_atom
compute_temp
compute_temp_asphere
compute_temp_body

101
doc/src/fix_dpd_source.txt Normal file
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@ -0,0 +1,101 @@
"LAMMPS WWW Site"_lws - "LAMMPS Documentation"_ld - "LAMMPS Commands"_lc :c
:link(lws,http://lammps.sandia.gov)
:link(ld,Manual.html)
:link(lc,Section_commands.html#comm)
:line
fix edpd/source command :h3
fix tdpd/source command :h3
[Syntax:]
fix ID group-ID edpd/source keyword values ...
fix ID group-ID tdpd/source cc_index keyword values ... :pre
ID, group-ID are documented in "fix"_fix.html command :ulb,l
edpd/source or tdpd/source = style name of this fix command :l
index (only specified for tdpd/source) = index of chemical species (1 to Nspecies) :l
keyword = {sphere} or {cuboid} :l
{sphere} values = cx,cy,cz,radius,source
cx,cy,cz = x,y,z center of spherical domain (distance units)
radius = radius of a spherical domain (distance units)
source = heat source or concentration source (flux units, see below)
{cuboid} values = cx,cy,cz,dLx,dLy,dLz,source
cx,cy,cz = x,y,z lower left corner of a cuboid domain (distance units)
dLx,dLy,dLz = x,y,z side length of a cuboid domain (distance units)
source = heat source or concentration source (flux units, see below) :pre
:ule
[Examples:]
fix 1 all edpd/source sphere 0.0 0.0 0.0 5.0 0.01
fix 1 all edpd/source cuboid 0.0 0.0 0.0 20.0 10.0 10.0 -0.01
fix 1 all tdpd/source 1 sphere 5.0 0.0 0.0 5.0 0.01
fix 1 all tdpd/source 2 cuboid 0.0 0.0 0.0 20.0 10.0 10.0 0.01 :pre
[Description:]
Fix {edpd/source} adds a heat source as an external heat flux to each
atom in a spherical or cuboid domain, where the {source} is in units
of energy/time. Fix {tdpd/source} adds an external concentration
source of the chemical species specified by {index} as an external
concentration flux for each atom in a spherical or cuboid domain,
where the {source} is in units of mole/volume/time.
This command can be used to give an additional heat/concentration
source term to atoms in a simulation, such as for a simulation of a
heat conduction with a source term (see Fig.12 in "(Li2014)"_#Li2014b)
or diffusion with a source term (see Fig.1 in "(Li2015)"_#Li2015b), as
an analog of a periodic Poiseuille flow problem.
If the {sphere} keyword is used, the {cx,cy,cz,radius} defines a
spherical domain to apply the source flux to.
If the {cuboid} keyword is used, the {cx,cy,cz,dLx,dLy,dLz} defines a
cuboid domain to apply the source flux to.
:line
[Restart, fix_modify, output, run start/stop, minimize info:]
No information about this fix is written to "binary restart
files"_restart.html. None of the "fix_modify"_fix_modify.html options
are relevant to this fix. No global or per-atom quantities are stored
by this fix for access by various "output
commands"_Section_howto.html#howto_15. No parameter of this fix can
be used with the {start/stop} keywords of the "run"_run.html command.
This fix is not invoked during "energy minimization"_minimize.html.
[Restrictions:]
This fix is part of the USER-MESO package. It is only enabled if
LAMMPS was built with that package. See the "Making
LAMMPS"_Section_start.html#start_3 section for more info.
Fix {edpd/source} must be used with the "pair_style
edpd"_pair_meso.html command. Fix {tdpd/source} must be used with the
"pair_style tdpd"_pair_meso.html command.
[Related commands:]
"pair_style edpd"_pair_meso.html, "pair_style tdpd"_pair_meso.html,
"compute edpd/temp/atom"_compute_edpd_temp_atom.html, "compute
tdpd/cc/atom"_compute_tdpd_cc_atom.html
[Default:] none
:line
:link(Li2014b)
[(Li2014)] Z. Li, Y.-H. Tang, H. Lei, B. Caswell and G.E. Karniadakis,
"Energy-conserving dissipative particle dynamics with
temperature-dependent properties", J. Comput. Phys., 265: 113-127
(2014). DOI: 10.1016/j.jcp.2014.02.003
:link(Li2015b)
[(Li2015)] Z. Li, A. Yazdani, A. Tartakovsky and G.E. Karniadakis,
"Transport dissipative particle dynamics model for mesoscopic
advection-diffusion-reaction problems", J. Chem. Phys., 143: 014101
(2015). DOI: 10.1063/1.4923254

97
doc/src/fix_mvv_dpd.txt Normal file
View File

@ -0,0 +1,97 @@
"LAMMPS WWW Site"_lws - "LAMMPS Documentation"_ld - "LAMMPS Commands"_lc :c
:link(lws,http://lammps.sandia.gov)
:link(ld,Manual.html)
:link(lc,Section_commands.html#comm)
:line
fix mvv/dpd command :h3
fix mvv/edpd command :h3
fix mvv/tdpd command :h3
[Syntax:]
fix ID group-ID mvv/dpd lambda :pre
fix ID group-ID mvv/edpd lambda :pre
fix ID group-ID mvv/tdpd lambda :pre
ID, group-ID are documented in "fix"_fix.html command
mvv/dpd, mvv/edpd, mvv/tdpd = style name of this fix command
lambda = (optional) relaxation parameter (unitless) :ul
[Examples:]
fix 1 all mvv/dpd
fix 1 all mvv/dpd 0.5
fix 1 all mvv/edpd
fix 1 all mvv/edpd 0.5
fix 1 all mvv/tdpd
fix 1 all mvv/tdpd 0.5 :pre
[Description:]
Perform time integration using the modified velocity-Verlet (MVV)
algorithm to update position and velocity (fix mvv/dpd), or position,
velocity and temperature (fix mvv/edpd), or position, velocity and
concentration (fix mvv/tdpd) for particles in the group each timestep.
The modified velocity-Verlet (MVV) algorithm aims to improve the
stability of the time integrator by using an extrapolated version of
the velocity for the force evaluation:
:c,image(Eqs/fix_mvv_dpd.jpg)
where the parameter <font size="4">&lambda;</font> depends on the
specific choice of DPD parameters, and needs to be tuned on a
case-by-case basis. Specification of a {lambda} value is opttional.
If specified, the setting must be from 0.0 to 1.0. If not specified,
a default value of 0.5 is used, which effectively reproduces the
standard velocity-Verlet (VV) scheme. For more details, see
"Groot"_#Groot2.
Fix {mvv/dpd} updates the position and velocity of each atom. It can
be used with the "pair_style mdpd"_pair_meso.html command or other
pair styles such as "pair dpd"_pair_dpd.html.
Fix {mvv/edpd} updates the per-atom temperature, in addition to
position and velocity, and must be used with the "pair_style
edpd"_pair_meso.html command.
Fix {mvv/tdpd} updates the per-atom chemical concentration, in
addition to position and velocity, and must be used with the
"pair_style tdpd"_pair_meso.html command.
:line
[Restart, fix_modify, output, run start/stop, minimize info:]
No information about this fix is written to "binary restart
files"_restart.html. None of the "fix_modify"_fix_modify.html options
are relevant to this fix. No global or per-atom quantities are stored
by this fix for access by various "output
commands"_Section_howto.html#howto_15. No parameter of this fix can
be used with the {start/stop} keywords of the "run"_run.html command.
This fix is not invoked during "energy minimization"_minimize.html.
[Restrictions:]
This fix is part of the USER-MESO package. It is only enabled if
LAMMPS was built with that package. See the "Making
LAMMPS"_Section_start.html#start_3 section for more info.
[Related commands:]
"pair_style mdpd"_pair_meso.html, "pair_style edpd"_pair_meso.html,
"pair_style tdpd"_pair_meso.html
[Default:]
The default value for the optional {lambda} parameter is 0.5.
:line
:link(Groot2)
[(Groot)] Groot and Warren, J Chem Phys, 107: 4423-4435 (1997). DOI:
10.1063/1.474784

View File

@ -90,9 +90,14 @@ file specified by {qfile}. The file has the following format
...
Ntype chi eta gamma zeta qcore :pre
There is one line per atom type with the following parameters.
There have to be parameters given for every atom type. Wildcard entries
are possible using the same syntax as elsewhere in LAMMPS
(i.e., n*m, n*, *m, *). Later entries will overwrite previous ones.
Empty lines or any text following the pound sign (#) are ignored.
Each line starts with the atom type followed by five parameters.
Only a subset of the parameters is used by each QEq style as described
below, thus the others can be set to 0.0 if desired.
below, thus the others can be set to 0.0 if desired, but all five
entries per line are required.
{chi} = electronegativity in energy units
{eta} = self-Coulomb potential in energy units

View File

@ -50,17 +50,17 @@ fix ees_cube all wall/region/ees myCube 1.0 1.0 2.5 :pre
Fix {wall/ees} bounds the simulation domain on one or more of its
faces with a flat wall that interacts with the ellipsoidal atoms in the
group by generating a force on the atom in a direction perpendicular to
the wall and a torque parallel with the wall.  The energy of
the wall and a torque parallel with the wall. The energy of
wall-particle interactions E is given by:
:c,image(Eqs/fix_wall_ees.jpg)
Introduced by Babadi and Ejtehadi in "(Babadi)"_#BabadiEjtehadi. Here,
{r} is the distance from the particle to the wall at position {coord},
and Rc is the {cutoff} distance at which the  particle and wall no
longer interact. Also,  sigma_n is the distance between center of
ellipsoid and the nearest point of its surface to the wall  The energy
of the wall (see the image below).
and Rc is the {cutoff} distance at which the particle and wall no
longer interact. Also, sigma_n is the distance between center of
ellipsoid and the nearest point of its surface to the wall. The energy
of the wall is:
:c,image(JPG/fix_wall_ees_image.jpg)
@ -68,21 +68,22 @@ Details of using this command and specifications are the same as
fix/wall command. You can also find an example in USER/ees/ under
examples/ directory.
The prefactor {epsilon} can be thought of as an
effective Hamaker constant with energy units for the strength of the
ellipsoid-wall interaction.  More specifically, the {epsilon} pre-factor
= 8 * pi^2 * rho_wall * rho_ellipsoid * epsilon
* sigma_a * sigma_b * sigma_c, where epsilon is the LJ parameters for
the constituent LJ particles and sigma_a, sigma_b, and sigma_c are radii
of ellipsoidal particles. Rho_wall and rho_ellipsoid are the number
The prefactor {epsilon} can be thought of as an
effective Hamaker constant with energy units for the strength of the
ellipsoid-wall interaction. More specifically, the {epsilon} pre-factor
= 8 * pi^2 * rho_wall * rho_ellipsoid * epsilon
* sigma_a * sigma_b * sigma_c, where epsilon is the LJ parameters for
the constituent LJ particles and sigma_a, sigma_b, and sigma_c are radii
of ellipsoidal particles. Rho_wall and rho_ellipsoid are the number
density of the constituent particles, in the wall and ellipsoid
respectively, in units of 1/volume.
NOTE: You must insure that r is always bigger than sigma_n for
all particles in the group, or LAMMPS will generate an error.  This
all particles in the group, or LAMMPS will generate an error. This
means you cannot start your simulation with particles touching the wall
position {coord} (r = sigma_n) or with particles penetrating the wall (0 =< r < sigma_n) or with particles on the wrong side of the
wall (r < 0).
position {coord} (r = sigma_n) or with particles penetrating the wall
(0 =< r < sigma_n) or with particles on the wrong side of the
wall (r < 0).
Fix {wall/region/ees} treats the surface of the geometric region defined
@ -93,7 +94,7 @@ Other details of this command are the same as for the "fix
wall/region"_fix_wall_region.html command. One may also find an example
of using this fix in the examples/USER/misc/ees/ directory.
[Restrictions:]
[Restrictions:]
This fix is part of the USER-MISC package. It is only enabled if
LAMMPS was built with that package. See the "Making

View File

@ -33,6 +33,7 @@ Fixes :h1
fix_drude
fix_drude_transform
fix_dpd_energy
fix_dpd_source
fix_dt_reset
fix_efield
fix_ehex
@ -71,6 +72,7 @@ Fixes :h1
fix_move
fix_mscg
fix_msst
fix_mvv_dpd
fix_neb
fix_nh
fix_nh_eff

View File

@ -21,6 +21,7 @@ Section_python.html
Section_errors.html
Section_history.html
tutorial_bash_on_windows.html
tutorial_drude.html
tutorial_github.html
tutorial_pylammps.html
@ -156,6 +157,7 @@ fix_controller.html
fix_deform.html
fix_deposit.html
fix_dpd_energy.html
fix_dpd_source.html
fix_drag.html
fix_drude.html
fix_drude_transform.html
@ -197,6 +199,7 @@ fix_momentum.html
fix_move.html
fix_mscg.html
fix_msst.html
fix_mvv_dpd.html
fix_neb.html
fix_nh.html
fix_nh_eff.html
@ -315,6 +318,7 @@ compute_dipole_chunk.html
compute_displace_atom.html
compute_dpd.html
compute_dpd_atom.html
compute_edpd_temp_atom.html
compute_erotate_asphere.html
compute_erotate_rigid.html
compute_erotate_sphere.html
@ -380,6 +384,7 @@ compute_smd_vol.html
compute_sna_atom.html
compute_stress_atom.html
compute_tally.html
compute_tdpd_cc_atom.html
compute_temp.html
compute_temp_asphere.html
compute_temp_body.html
@ -457,6 +462,7 @@ pair_mdf.html
pair_meam.html
pair_meam_spline.html
pair_meam_sw_spline.html
pair_meso.html
pair_mgpt.html
pair_mie.html
pair_momb.html
@ -644,4 +650,3 @@ USER/atc/man_unfix_flux.html
USER/atc/man_unfix_nodes.html
USER/atc/man_write_atom_weights.html
USER/atc/man_write_restart.html

View File

@ -36,7 +36,7 @@ pair_coeff 1 1 1.0 1.0 :pre
[Description:]
Style {dpd} computes a force field for dissipative particle dynamics
(DPD) following the exposition in "(Groot)"_#Groot.
(DPD) following the exposition in "(Groot)"_#Groot1.
Style {dpd/tstat} invokes a DPD thermostat on pairwise interactions,
which is equivalent to the non-conservative portion of the DPD force
@ -196,7 +196,7 @@ langevin"_fix_langevin.html, "pair_style srp"_pair_srp.html
:line
:link(Groot)
:link(Groot1)
[(Groot)] Groot and Warren, J Chem Phys, 107, 4423-35 (1997).
:link(Afshar)

277
doc/src/pair_meso.txt Normal file
View File

@ -0,0 +1,277 @@
"LAMMPS WWW Site"_lws - "LAMMPS Documentation"_ld - "LAMMPS Commands"_lc :c
:link(lws,http://lammps.sandia.gov)
:link(ld,Manual.html)
:link(lc,Section_commands.html#comm)
:line
pair_style edpd command :h3
pair_style mdpd command :h3
pair_style mdpd/rhosum command :h3
pair_style tdpd command :h3
[Syntax:]
pair_style style args :pre
style = {edpd} or {mdpd} or {mdpd/rhosum} or {tdpd} :ulb,l
args = list of arguments for a particular style :l
{edpd} args = cutoff seed
cutoff = global cutoff for eDPD interactions (distance units)
seed = random # seed (integer) (if <= 0, eDPD will use current time as the seed)
{mdpd} args = T cutoff seed
T = temperature (temperature units)
cutoff = global cutoff for mDPD interactions (distance units)
seed = random # seed (integer) (if <= 0, mDPD will use current time as the seed)
{mdpd/rhosum} args =
{tdpd} args = T cutoff seed
T = temperature (temperature units)
cutoff = global cutoff for tDPD interactions (distance units)
seed = random # seed (integer) (if <= 0, tDPD will use current time as the seed) :pre
:ule
[Examples:]
pair_style edpd 1.58 9872598
pair_coeff * * 18.75 4.5 0.41 1.58 1.42E-5 2.0 1.58
pair_coeff 1 1 18.75 4.5 0.41 1.58 1.42E-5 2.0 1.58 power 10.54 -3.66 3.44 -4.10
pair_coeff 1 1 18.75 4.5 0.41 1.58 1.42E-5 2.0 1.58 power 10.54 -3.66 3.44 -4.10 kappa -0.44 -3.21 5.04 0.00 :pre
pair_style hybrid/overlay mdpd/rhosum mdpd 1.0 1.0 65689
pair_coeff 1 1 mdpd/rhosum 0.75
pair_coeff 1 1 mdpd -40.0 25.0 18.0 1.0 0.75 :pre
pair_style tdpd 1.0 1.58 935662
pair_coeff * * 18.75 4.5 0.41 1.58 1.58 1.0 1.0E-5 2.0
pair_coeff 1 1 18.75 4.5 0.41 1.58 1.58 1.0 1.0E-5 2.0 3.0 1.0E-5 2.0 :pre
[Description:]
The {edpd} style computes the pairwise interactions and heat fluxes
for eDPD particles following the formulations in
"(Li2014_JCP)"_#Li2014_JCP and "Li2015_CC"_#Li2015_CC. The time
evolution of an eDPD particle is governed by the conservation of
momentum and energy given by
:c,image(Eqs/pair_edpd_gov.jpg)
where the three components of <font size="4">F<sub>i</sub></font>
including the conservative force <font
size="4">F<sub>ij</sub><sup>C</sup></font>, dissipative force <font
size="4">F<sub>ij</sub><sup>D</sup></font> and random force <font
size="4">F<sub>ij</sub><sup>R</sup></font> are expressed as
:c,image(Eqs/pair_edpd_force.jpg)
in which the exponent of the weighting function <font
size="4"><i>s</i></font> can be defined as a temperature-dependent
variable. The heat flux between particles accounting for the
collisional heat flux <font size="4">q<sup>C</sup></font>, viscous
heat flux <font size="4">q<sup>V</sup></font>, and random heat flux
<font size="4">q<sup>R</sup></font> are given by
:c,image(Eqs/pair_edpd_heat.jpg)
where the mesoscopic heat friction <font size="4">&kappa;</font> is given by
:c,image(Eqs/pair_edpd_kappa.jpg)
with <font size="4">&upsilon;</font> being the kinematic
viscosity. For more details, see Eq.(15) in "(Li2014_JCP)"_#Li2014_JCP.
The following coefficients must be defined in eDPD system for each
pair of atom types via the "pair_coeff"_pair_coeff.html command as in
the examples above.
A (force units)
gamma (force/velocity units)
power_f (positive real)
cutoff (distance units)
kappa (thermal conductivity units)
power_T (positive real)
cutoff_T (distance units)
optional keyword = power or kappa :ul
The keyword {power} or {kappa} is optional. Both "power" and "kappa"
require 4 parameters <font size="4">c<sub>1</sub>, c<sub>2</sub>,
c<sub>4</sub>, c<sub>4</sub></font> showing the temperature dependence
of the exponent <center><font size="4"> <i>s</i>(<i>T</i>) =
power_f*(1+c<sub>1</sub>*(T-1)+c<sub>2</sub>*(T-1)<sup>2</sup>
+c<sub>3</sub>*(T-1)<sup>3</sup>+c<sub>4</sub>*(T-1)<sup>4</sup>)</font></center>
and of the mesoscopic heat friction <center><font size="4">
<i>s<sub>T</sub>(T)</i> =
kappa*(1+c<sub>1</sub>*(T-1)+c<sub>2</sub>*(T-1)<sup>2</sup>
+c<sub>3</sub>*(T-1)<sup>3</sup>+c<sub>4</sub>*(T-1)<sup>4</sup>)</font></center>
If the keyword {power} or {kappa} is not specified, the eDPD system
will use constant power_f and kappa, which is independent to
temperature changes.
:line
The {mdpd/rhosum} style computes the local particle mass density rho
for mDPD particles by kernel function interpolation.
The following coefficients must be defined for each pair of atom types
via the "pair_coeff"_pair_coeff.html command as in the examples above.
cutoff (distance units) :ul
:line
The {mdpd} style computes the many-body interactions between mDPD
particles following the formulations in
"(Li2013_POF)"_#Li2013_POF. The dissipative and random forces are in
the form same as the classical DPD, but the conservative force is
local density dependent, which are given by
:c,image(Eqs/pair_mdpd_force.jpg)
where the first term in <font size="4">F<sup>C</sup></font> with a
negative coefficient A < 0 stands for an attractive force within an
interaction range <font size="4">r<sub>c</sub></font>, and the second
term with B > 0 is the density-dependent repulsive force within an
interaction range <font size="4">r<sub>d</sub></font>.
The following coefficients must be defined for each pair of atom types via the
"pair_coeff"_pair_coeff.html command as in the examples above.
A (force units)
B (force units)
gamma (force/velocity units)
cutoff_c (distance units)
cutoff_d (distance units) :ul
:line
The {tdpd} style computes the pairwise interactions and chemical
concentration fluxes for tDPD particles following the formulations in
"(Li2015_JCP)"_#Li2015_JCP. The time evolution of a tDPD particle is
governed by the conservation of momentum and concentration given by
:c,image(Eqs/pair_tdpd_gov.jpg)
where the three components of <font size="4">F<sub>i</sub></font>
including the conservative force <font
size="4">F<sub>ij</sub><sup>C</sup></font>, dissipative force <font
size="4">F<sub>ij</sub><sup>D</sup></font> and random force <font
size="4">F<sub>ij</sub><sup>R</sup></font> are expressed as
:c,image(Eqs/pair_tdpd_force.jpg)
The concentration flux between two tDPD particles includes the Fickian
flux <font size="4">Q<sub>ij</sub><sup>D</sup></font> and random flux
<font size="4">Q<sub>ij</sub><sup>R</sup></font>, which are given by
:c,image(Eqs/pair_tdpd_flux.jpg)
where the parameters kappa and epsilon determine the strength of the
Fickian and random fluxes. <font size="4"><i>m</i><sub>s</sub></font>
is the mass of a single solute molecule. In general, <font
size="4"><i>m</i><sub>s</sub></font> is much smaller than the mass of
a tDPD particle <font size="4"><i>m</i></font>. For more details, see
"(Li2015_JCP)"_#Li2015_JCP.
The following coefficients must be defined for each pair of atom types via the
"pair_coeff"_pair_coeff.html command as in the examples above.
A (force units)
gamma (force/velocity units)
power_f (positive real)
cutoff (distance units)
cutoff_CC (distance units)
kappa_i (diffusivity units)
epsilon_i (diffusivity units)
power_cc_i (positive real) :ul
The last 3 values must be repeated Nspecies times, so that values for
each of the Nspecies chemical species are specified, as indicated by
the "I" suffix. In the first pair_coeff example above for pair_style
tdpd, Nspecies = 1. In the second example, Nspecies = 2, so 3
additional coeffs are specified (for species 2).
:line
[Example scripts]
There are example scripts for using all these pair styles in
examples/USER/meso. The example for an eDPD simulation models heat
conduction with source terms analog of periodic Poiseuille flow
problem. The setup follows Fig.12 in "(Li2014_JCP)"_#Li2014_JCP. The
output of the short eDPD simulation (about 2 minutes on a single core)
gives a temperature and density profiles as
:c,image(JPG/examples_edpd.jpg)
The example for a mDPD simulation models the oscillations of a liquid
droplet started from a liquid film. The mDPD parameters are adopted
from "(Li2013_POF)"_#Li2013_POF. The short mDPD run (about 2 minutes
on a single core) generates a particle trajectory which can
be visualized as follows.
:c,image(JPG/examples_mdpd_first.jpg,JPG/examples_mdpd.gif)
:c,image(JPG/examples_mdpd_last.jpg)
The first image is the initial state of the simulation. If you
click it a GIF movie should play in your browser. The second image
is the final state of the simulation.
The example for a tDPD simulation computes the effective diffusion
coefficient of a tDPD system using a method analogous to the periodic
Poiseuille flow. The tDPD system is specified with two chemical
species, and the setup follows Fig.1 in
"(Li2015_JCP)"_#Li2015_JCP. The output of the short tDPD simulation
(about one and a half minutes on a single core) gives the
concentration profiles of the two chemical species as
:c,image(JPG/examples_tdpd.jpg)
:line
[Mixing, shift, table, tail correction, restart, rRESPA info]:
The styles {edpd}, {mdpd}, {mdpd/rhosum} and {tdpd} do not support
mixing. Thus, coefficients for all I,J pairs must be specified explicitly.
The styles {edpd}, {mdpd}, {mdpd/rhosum} and {tdpd} do not support
the "pair_modify"_pair_modify.html shift, table, and tail options.
The styles {edpd}, {mdpd}, {mdpd/rhosum} and {tdpd} do not write
information to "binary restart files"_restart.html. Thus, you need
to re-specify the pair_style and pair_coeff commands in an input script
that reads a restart file.
[Restrictions:]
The pair styles {edpd}, {mdpd}, {mdpd/rhosum} and {tdpd} are part of
the USER-MESO package. It is only enabled if LAMMPS was built with
that package. See the "Making LAMMPS"_Section_start.html#start_3
section for more info.
[Related commands:]
"pair_coeff"_pair_coeff.html, "fix mvv/dpd"_fix_mvv_dpd.html,
"fix mvv/edpd"_fix_mvv_dpd.html, "fix mvv/tdpd"_fix_mvv_dpd.html,
"fix edpd/source"_fix_dpd_source.html, "fix tdpd/source"_fix_dpd_source.html,
"compute edpd/temp/atom"_compute_edpd_temp_atom.html,
"compute tdpd/cc/atom"_compute_tdpd_cc_atom.html
[Default:] none
:line
:link(Li2014_JCP)
[(Li2014_JCP)] Li, Tang, Lei, Caswell, Karniadakis, J Comput Phys,
265: 113-127 (2014). DOI: 10.1016/j.jcp.2014.02.003.
:link(Li2015_CC)
[(Li2015_CC)] Li, Tang, Li, Karniadakis, Chem Commun, 51: 11038-11040
(2015). DOI: 10.1039/C5CC01684C.
:link(Li2013_POF)
[(Li2013_POF)] Li, Hu, Wang, Ma, Zhou, Phys Fluids, 25: 072103 (2013).
DOI: 10.1063/1.4812366.
:link(Li2015_JCP)
[(Li2015_JCP)] Li, Yazdani, Tartakovsky, Karniadakis, J Chem Phys,
143: 014101 (2015). DOI: 10.1063/1.4923254.

View File

@ -10,8 +10,7 @@ pair_style snap command :h3
[Syntax:]
pair_style snap
:pre
pair_style snap :pre
[Examples:]
@ -20,17 +19,16 @@ pair_coeff * * InP.snapcoeff In P InP.snapparam In In P P :pre
[Description:]
Pair style {snap} computes interactions
using the spectral neighbor analysis potential (SNAP)
"(Thompson)"_#Thompson20142. Like the GAP framework of Bartok et al.
"(Bartok2010)"_#Bartok20102, "(Bartok2013)"_#Bartok2013
which uses bispectrum components
Pair style {snap} computes interactions using the spectral
neighbor analysis potential (SNAP) "(Thompson)"_#Thompson20142.
Like the GAP framework of Bartok et al. "(Bartok2010)"_#Bartok20102,
"(Bartok2013)"_#Bartok2013 which uses bispectrum components
to characterize the local neighborhood of each atom
in a very general way. The mathematical definition of the
bispectrum calculation used by SNAP is identical
to that used by "compute sna/atom"_compute_sna_atom.html.
In SNAP, the total energy is decomposed into a sum over
atom energies. The energy of atom {i } is
atom energies. The energy of atom {i} is
expressed as a weighted sum over bispectrum components.
:c,image(Eqs/pair_snap.jpg)

View File

@ -58,6 +58,7 @@ Pair Styles :h1
pair_meam
pair_meam_spline
pair_meam_sw_spline
pair_meso
pair_mgpt
pair_mie
pair_momb

View File

@ -374,10 +374,9 @@ needed if new bonds (angles, dihedrals, impropers) will be added to
the system when a simulation runs, e.g. by using the "fix
bond/create"_fix_bond_create.html command. Using this header flag
is deprecated; please use the {extra/bond/per/atom} keyword (and
correspondingly for angles, dihedrals and impropers) in the
read_data command instead. Either will pre-allocate space in LAMMPS
data structures for storing the new bonds (angles,
dihedrals, impropers).
correspondingly for angles, dihedrals and impropers) in the read_data
command instead. Either will pre-allocate space in LAMMPS data
structures for storing the new bonds (angles, dihedrals, impropers).
The "extra special per atom" setting is typically only needed if new
bonds/angles/etc will be added to the system, e.g. by using the "fix
@ -547,6 +546,9 @@ bond: atom-ID molecule-ID atom-type x y z
charge: atom-ID atom-type q x y z
dipole: atom-ID atom-type q x y z mux muy muz
dpd: atom-ID atom-type theta x y z
edpd: atom-ID atom-type edpd_temp edpd_cv x y z
mdpd: atom-ID atom-type x y z
tdpd: atom-ID atom-type x y z cc1 cc2 ... ccNspecies
electron: atom-ID atom-type q spin eradius x y z
ellipsoid: atom-ID atom-type ellipsoidflag density x y z
full: atom-ID molecule-ID atom-type q x y z
@ -566,12 +568,15 @@ The per-atom values have these meanings and units, listed alphabetically:
atom-ID = integer ID of atom
atom-type = type of atom (1-Ntype)
bodyflag = 1 for body particles, 0 for point particles
cc = chemical concentration for tDPD particles for each species (mole/volume units)
contact-radius = ??? (distance units)
cs_re,cs_im = real/imaginary parts of wavepacket coefficients
cv = heat capacity (need units) for SPH particles
density = density of particle (mass/distance^3 or mass/distance^2 or mass/distance units, depending on dimensionality of particle)
diameter = diameter of spherical atom (distance units)
e = energy (need units) for SPH particles
edpd_temp = temperature for eDPD particles (temperature units)
edpd_cv = volumetric heat capacity for eDPD particles (energy/temperature/volume units)
ellipsoidflag = 1 for ellipsoidal particles, 0 for point particles
eradius = electron radius (or fixed-core radius)
etag = integer ID of electron that each wavepacket belongs to

View File

@ -24,7 +24,7 @@ keyword = {type} or {type/fraction} or {mol} or {x} or {y} or {z} or \
{bond} or {angle} or {dihedral} or {improper} or \
{meso/e} or {meso/cv} or {meso/rho} or \
{smd/contact/radius} or {smd/mass/density} or {dpd/theta} or \
{i_name} or {d_name} :l
{edpd/temp} or {edpd/cv} or {cc} or {i_name} or {d_name} :l
{type} value = atom type
value can be an atom-style variable (see below)
{type/fraction} values = type fraction seed
@ -98,6 +98,13 @@ keyword = {type} or {type/fraction} or {mol} or {x} or {y} or {z} or \
{dpd/theta} value = internal temperature of DPD particles (temperature units)
value can be an atom-style variable (see below)
value can be NULL which sets internal temp of each particle to KE temp
{edpd/temp} value = temperature of eDPD particles (temperature units)
value can be an atom-style variable (see below)
{edpd/cv} value = volumetric heat capacity of eDPD particles (energy/temperature/volume units)
value can be an atom-style variable (see below)
{cc} values = index cc
index = index of a chemical species (1 to Nspecies)
cc = chemical concentration of tDPD particles for a species (mole/volume units)
{i_name} value = value for custom integer vector with name
{d_name} value = value for custom floating-point vector with name :pre
:ule
@ -418,6 +425,19 @@ value >= 0.0, the internal temperature is set to that value. If it is
< 0.0, the computation of Tkin is performed and the internal
temperature is set to that value.
Keywords {edpd/temp} and {edpd/cv} set the temperature and volumetric
heat capacity of an eDPD particle as defined by the USER-MESO package.
Currently, only "atom_style edpd"_atom_style.html defines particles
with these attributes. The values for the temperature and heat
capacity must be positive.
Keyword {cc} sets the chemical concentration of a tDPD particle for a
specified species as defined by the USER-MESO package. Currently, only
"atom_style tdpd"_atom_style.html defines particles with this
attribute. An integer for "index" selects a chemical species (1 to
Nspecies) where Nspecies is set by the atom_style command. The value
for the chemical concentration must be >= 0.0.
Keywords {i_name} and {d_name} refer to custom integer and
floating-point properties that have been added to each atom via the
"fix property/atom"_fix_property_atom.html command. When that command

40
examples/USER/meso/README Normal file
View File

@ -0,0 +1,40 @@
This directory contains input scripts for performing
simulations with these models:
eDPD - energy-conserving dissipative particle dynamics
mDPD - many-body dissipative particle dynamics
tDPD - transport dissipative particle dynamics
1) eDPD: The input script in.mdpd is an example simulation of
measuring the thermal conductivity by heat conduction analog of
periodic Poiseuille flow. The initial eDPD system is randomly filled
by many eDPD particles, and a set command "edpd/temp" gives the
initial temperature and a set command "edpd/cv" gives the heat
capacity of eDPD particles. A non-contact heat source/sink term is
applied by a fix command "edpd/source". A compute command
"edpd/temp/atom" obtain the temperature on each eDPD particle. The
simulation will generate a file named "temp.profile" showing the
temperature profile. For details please see online LAMMPS
documentation and Fig.12 in the paper Z. Li, et al. J Comput Phys,
2014, 265: 113-127. DOI: 10.1016/j.jcp.2014.02.003
2) mDPD: The input script "in.mdpd" is an example simulation of
oscillations of a free liquid droplet. The initial configuration is a
liquid film whose particles are in a fcc lattice created by the
command "create atoms". Then the liquid film has a tendency to form a
spherical droplet under the effect of surface tension. For details
please see online LAMMPS documentation and the paper Z. Li, et
al. Phys Fluids, 2013, 25: 072103. DOI: 10.1063/1.4812366
3) tDPD: The input script in.tdpd is an example simulation of
computing the effective diffusion coefficient of a tDPD system using a
method analogous to the periodic Poiseuille flow. Command "atom_style
tdpd 2" specifies the tDPD system with two chemical species. The
initial tDPD system is randomly filled by many tDPD particles, and a
set "cc" command gives initial concentration for each chemical
species. Fix commands "tdpd/source" add source terms and compute
commands "tdpd/cc/atom" obtain the chemical concentration on each tDPD
particle. The simulation will generate a file named "cc.profile"
showing the concentration profiles of the two chemical species. For
details please see online LAMMPS documentation and Fig.1 in the paper
Z. Li, et al. J Chem Phys, 2015, 143: 014101. DOI: 10.1063/1.4923254

View File

@ -0,0 +1,54 @@
########################################################################
### Heat conduction analog of periodic Poiseuille flow problem ###
### using energy-conserving DPD (eDPD) simulation ###
### ###
### Created : Zhen Li (zhen_li@brown.edu) ###
### Division of Applied Mathematics, Brown University. ###
### ###
### mDPD system setup follows Fig.12 in the publication: ###
### Z. Li, Y.-H. Tang, H. Lei, B. Caswell and G.E. Karniadakis. ###
### "Energy-conserving dissipative particle dynamics with ###
### temperature-dependent properties". J. Comput. Phys., ###
### 2014, 265: 113-127. DOI: 10.1016/j.jcp.2014.02.003 ###
########################################################################
units lj
dimension 3
boundary p p p
neighbor 0.2 bin
neigh_modify every 1 delay 0 check yes
atom_style edpd
region edpd block -10 10 -10 10 -5 5 units box
create_box 1 edpd
create_atoms 1 random 16000 276438 NULL
mass 1 1.0
set atom * edpd/temp 1.0
set atom * edpd/cv 1.0E5
pair_style edpd 1.58 9872598
#pair_coeff 1 1 18.75 4.5 0.41 1.58 1.45E-5 2.0 1.58
pair_coeff 1 1 18.75 4.5 0.41 1.58 1.41E-5 2.0 1.58 &
power 10.54 -3.66 3.44 -4.10 &
kappa -0.44 -3.21 5.04 0.00
compute mythermo all temp
thermo 100
thermo_modify temp mythermo
thermo_modify flush yes
velocity all create 1.0 432982 loop local dist gaussian
fix mvv all mvv/edpd 0.5
fix upper all edpd/source cuboid 0.0 5.0 0.0 20.0 10.0 10.0 0.01
fix lower all edpd/source cuboid 0.0 -5.0 0.0 20.0 10.0 10.0 -0.01
timestep 0.01
run 500
reset_timestep 0
compute temp all edpd/temp/atom
compute ccT all chunk/atom bin/1d y 0.0 1.0
fix stat all ave/chunk 1 500 500 ccT c_temp density/number norm sample file temp.profile
run 500

View File

@ -0,0 +1,142 @@
LAMMPS (11 Aug 2017)
########################################################################
### Heat conduction analog of periodic Poiseuille flow problem ###
### using energy-conserving DPD (eDPD) simulation ###
### ###
### Created : Zhen Li (zhen_li@brown.edu) ###
### Division of Applied Mathematics, Brown University. ###
### ###
### mDPD system setup follows Fig.12 in the publication: ###
### Z. Li, Y.-H. Tang, H. Lei, B. Caswell and G.E. Karniadakis. ###
### "Energy-conserving dissipative particle dynamics with ###
### temperature-dependent properties". J. Comput. Phys., ###
### 2014, 265: 113-127. DOI: 10.1016/j.jcp.2014.02.003 ###
########################################################################
units lj
dimension 3
boundary p p p
neighbor 0.2 bin
neigh_modify every 1 delay 0 check yes
atom_style edpd
region edpd block -10 10 -10 10 -5 5 units box
create_box 1 edpd
Created orthogonal box = (-10 -10 -5) to (10 10 5)
1 by 1 by 1 MPI processor grid
create_atoms 1 random 16000 276438 NULL
Created 16000 atoms
mass 1 1.0
set atom * edpd/temp 1.0
16000 settings made for edpd/temp
set atom * edpd/cv 1.0E5
16000 settings made for edpd/cv
pair_style edpd 1.58 9872598
#pair_coeff 1 1 18.75 4.5 0.41 1.58 1.45E-5 2.0 1.58
pair_coeff 1 1 18.75 4.5 0.41 1.58 1.41E-5 2.0 1.58 power 10.54 -3.66 3.44 -4.10 kappa -0.44 -3.21 5.04 0.00
compute mythermo all temp
thermo 100
thermo_modify temp mythermo
thermo_modify flush yes
velocity all create 1.0 432982 loop local dist gaussian
fix mvv all mvv/edpd 0.5
fix upper all edpd/source cuboid 0.0 5.0 0.0 20.0 10.0 10.0 0.01
fix lower all edpd/source cuboid 0.0 -5.0 0.0 20.0 10.0 10.0 -0.01
timestep 0.01
run 500
Neighbor list info ...
update every 1 steps, delay 0 steps, check yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 1.78
ghost atom cutoff = 1.78
binsize = 0.89, bins = 23 23 12
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair edpd, perpetual
attributes: half, newton on
pair build: half/bin/atomonly/newton
stencil: half/bin/3d/newton
bin: standard
Per MPI rank memory allocation (min/avg/max) = 11.64 | 11.64 | 11.64 Mbytes
Step Temp E_pair E_mol TotEng Press
0 1 48.948932 0 50.448838 201.73366
100 1.0069712 43.754293 0 45.264656 199.5369
200 0.98667561 43.716052 0 45.195973 196.72854
300 1.0036944 43.706299 0 45.211746 195.35714
400 1.0024228 43.697014 0 45.200554 197.0062
500 0.99968161 43.687445 0 45.186873 193.80596
Loop time of 80.7995 on 1 procs for 500 steps with 16000 atoms
Performance: 5346.567 tau/day, 6.188 timesteps/s
99.9% CPU use with 1 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 75.106 | 75.106 | 75.106 | 0.0 | 92.95
Neigh | 4.9836 | 4.9836 | 4.9836 | 0.0 | 6.17
Comm | 0.31199 | 0.31199 | 0.31199 | 0.0 | 0.39
Output | 0.00048232 | 0.00048232 | 0.00048232 | 0.0 | 0.00
Modify | 0.29985 | 0.29985 | 0.29985 | 0.0 | 0.37
Other | | 0.09751 | | | 0.12
Nlocal: 16000 ave 16000 max 16000 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 14091 ave 14091 max 14091 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 749111 ave 749111 max 749111 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 749111
Ave neighs/atom = 46.8194
Neighbor list builds = 181
Dangerous builds = 0
reset_timestep 0
compute temp all edpd/temp/atom
compute ccT all chunk/atom bin/1d y 0.0 1.0
fix stat all ave/chunk 1 500 500 ccT c_temp density/number norm sample file temp.profile
run 500
Per MPI rank memory allocation (min/avg/max) = 12.14 | 12.14 | 12.14 Mbytes
Step Temp E_pair E_mol TotEng Press
0 0.99968161 43.687397 0 45.186825 196.38426
100 1.0041443 43.668196 0 45.174318 195.38066
200 0.99628392 43.666173 0 45.160505 197.84675
300 1.0029116 43.66224 0 45.166513 199.67414
400 0.99922193 43.64406 0 45.142799 196.94404
500 0.99355431 43.623266 0 45.113505 195.94136
Loop time of 80.7742 on 1 procs for 500 steps with 16000 atoms
Performance: 5348.242 tau/day, 6.190 timesteps/s
99.9% CPU use with 1 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 75.073 | 75.073 | 75.073 | 0.0 | 92.94
Neigh | 4.8786 | 4.8786 | 4.8786 | 0.0 | 6.04
Comm | 0.31086 | 0.31086 | 0.31086 | 0.0 | 0.38
Output | 0.00045919 | 0.00045919 | 0.00045919 | 0.0 | 0.00
Modify | 0.4139 | 0.4139 | 0.4139 | 0.0 | 0.51
Other | | 0.09731 | | | 0.12
Nlocal: 16000 ave 16000 max 16000 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 14091 ave 14091 max 14091 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 749667 ave 749667 max 749667 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 749667
Ave neighs/atom = 46.8542
Neighbor list builds = 178
Dangerous builds = 0
Please see the log.cite file for references relevant to this simulation
Total wall time: 0:02:41

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@ -0,0 +1,142 @@
LAMMPS (11 Aug 2017)
########################################################################
### Heat conduction analog of periodic Poiseuille flow problem ###
### using energy-conserving DPD (eDPD) simulation ###
### ###
### Created : Zhen Li (zhen_li@brown.edu) ###
### Division of Applied Mathematics, Brown University. ###
### ###
### mDPD system setup follows Fig.12 in the publication: ###
### Z. Li, Y.-H. Tang, H. Lei, B. Caswell and G.E. Karniadakis. ###
### "Energy-conserving dissipative particle dynamics with ###
### temperature-dependent properties". J. Comput. Phys., ###
### 2014, 265: 113-127. DOI: 10.1016/j.jcp.2014.02.003 ###
########################################################################
units lj
dimension 3
boundary p p p
neighbor 0.2 bin
neigh_modify every 1 delay 0 check yes
atom_style edpd
region edpd block -10 10 -10 10 -5 5 units box
create_box 1 edpd
Created orthogonal box = (-10 -10 -5) to (10 10 5)
2 by 2 by 1 MPI processor grid
create_atoms 1 random 16000 276438 NULL
Created 16000 atoms
mass 1 1.0
set atom * edpd/temp 1.0
16000 settings made for edpd/temp
set atom * edpd/cv 1.0E5
16000 settings made for edpd/cv
pair_style edpd 1.58 9872598
#pair_coeff 1 1 18.75 4.5 0.41 1.58 1.45E-5 2.0 1.58
pair_coeff 1 1 18.75 4.5 0.41 1.58 1.41E-5 2.0 1.58 power 10.54 -3.66 3.44 -4.10 kappa -0.44 -3.21 5.04 0.00
compute mythermo all temp
thermo 100
thermo_modify temp mythermo
thermo_modify flush yes
velocity all create 1.0 432982 loop local dist gaussian
fix mvv all mvv/edpd 0.5
fix upper all edpd/source cuboid 0.0 5.0 0.0 20.0 10.0 10.0 0.01
fix lower all edpd/source cuboid 0.0 -5.0 0.0 20.0 10.0 10.0 -0.01
timestep 0.01
run 500
Neighbor list info ...
update every 1 steps, delay 0 steps, check yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 1.78
ghost atom cutoff = 1.78
binsize = 0.89, bins = 23 23 12
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair edpd, perpetual
attributes: half, newton on
pair build: half/bin/atomonly/newton
stencil: half/bin/3d/newton
bin: standard
Per MPI rank memory allocation (min/avg/max) = 4.969 | 4.979 | 4.985 Mbytes
Step Temp E_pair E_mol TotEng Press
0 1 48.948932 0 50.448838 199.51547
100 1.0106415 43.744371 0 45.260239 196.39598
200 1.0053215 43.714413 0 45.222301 195.35298
300 0.99886399 43.713356 0 45.211559 196.74821
400 1.0035264 43.699086 0 45.204282 195.47446
500 1.0025285 43.698051 0 45.20175 197.27042
Loop time of 21.165 on 4 procs for 500 steps with 16000 atoms
Performance: 20411.046 tau/day, 23.624 timesteps/s
99.9% CPU use with 4 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 18.713 | 19.101 | 19.41 | 6.0 | 90.25
Neigh | 1.2687 | 1.2925 | 1.3177 | 1.5 | 6.11
Comm | 0.33013 | 0.66337 | 1.0747 | 34.3 | 3.13
Output | 0.00023484 | 0.00028092 | 0.00036526 | 0.0 | 0.00
Modify | 0.073931 | 0.075277 | 0.076306 | 0.3 | 0.36
Other | | 0.03227 | | | 0.15
Nlocal: 4000 ave 4067 max 3930 min
Histogram: 1 1 0 0 0 0 0 0 0 2
Nghost: 5997.5 ave 6052 max 5943 min
Histogram: 1 0 1 0 0 0 0 1 0 1
Neighs: 187388 ave 193157 max 181221 min
Histogram: 1 1 0 0 0 0 0 0 0 2
Total # of neighbors = 749552
Ave neighs/atom = 46.847
Neighbor list builds = 181
Dangerous builds = 0
reset_timestep 0
compute temp all edpd/temp/atom
compute ccT all chunk/atom bin/1d y 0.0 1.0
fix stat all ave/chunk 1 500 500 ccT c_temp density/number norm sample file temp.profile
run 500
Per MPI rank memory allocation (min/avg/max) = 5.221 | 5.23 | 5.236 Mbytes
Step Temp E_pair E_mol TotEng Press
0 1.0025285 43.69801 0 45.201708 194.00452
100 0.9885969 43.679927 0 45.16273 196.28442
200 1.0028463 43.663067 0 45.167242 198.25592
300 1.0027516 43.648817 0 45.152851 198.82226
400 0.99695312 43.641469 0 45.136805 197.97499
500 0.98202292 43.627163 0 45.100105 199.16319
Loop time of 21.576 on 4 procs for 500 steps with 16000 atoms
Performance: 20022.203 tau/day, 23.174 timesteps/s
99.8% CPU use with 4 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 18.438 | 19.121 | 19.812 | 14.1 | 88.62
Neigh | 1.2568 | 1.2885 | 1.325 | 2.5 | 5.97
Comm | 0.29482 | 1.0219 | 1.7352 | 63.9 | 4.74
Output | 0.00027728 | 0.00029719 | 0.0003531 | 0.0 | 0.00
Modify | 0.11153 | 0.11265 | 0.1135 | 0.2 | 0.52
Other | | 0.03194 | | | 0.15
Nlocal: 4000 ave 4092 max 3899 min
Histogram: 2 0 0 0 0 0 0 0 0 2
Nghost: 5974 ave 6019 max 5915 min
Histogram: 1 0 0 1 0 0 0 0 0 2
Neighs: 187414 ave 196149 max 178418 min
Histogram: 2 0 0 0 0 0 0 0 0 2
Total # of neighbors = 749658
Ave neighs/atom = 46.8536
Neighbor list builds = 181
Dangerous builds = 0
Please see the log.cite file for references relevant to this simulation
Total wall time: 0:00:42

View File

@ -0,0 +1,24 @@
# Chunk-averaged data for fix stat and group density/number
# Timestep Number-of-chunks Total-count
# Chunk Coord1 Ncount c_temp density/number
500 20 16000
1 -9.5 801.636 0.986368 4.00818
2 -8.5 809.788 0.966281 4.04894
3 -7.5 819.754 0.952764 4.09877
4 -6.5 820.364 0.944592 4.10182
5 -5.5 826.146 0.940968 4.13073
6 -4.5 819.52 0.941415 4.0976
7 -3.5 815.182 0.945887 4.07591
8 -2.5 817.168 0.95487 4.08584
9 -1.5 817.282 0.969225 4.08641
10 -0.5 804.204 0.989552 4.02102
11 0.5 793.266 1.01015 3.96633
12 1.5 789.056 1.0308 3.94528
13 2.5 784.344 1.04568 3.92172
14 3.5 780.592 1.05508 3.90296
15 4.5 772.218 1.05968 3.86109
16 5.5 776.968 1.06003 3.88484
17 6.5 780.858 1.05612 3.90429
18 7.5 786.174 1.04752 3.93087
19 8.5 788.922 1.03347 3.94461
20 9.5 796.558 1.01278 3.98279

View File

@ -0,0 +1,24 @@
# Chunk-averaged data for fix stat and group density/number
# Timestep Number-of-chunks Total-count
# Chunk Coord1 Ncount c_temp density/number
500 20 16000
1 -9.5 801.642 0.986089 4.00821
2 -8.5 819.168 0.966072 4.09584
3 -7.5 817.382 0.952718 4.08691
4 -6.5 818 0.944633 4.09
5 -5.5 817.806 0.941105 4.08903
6 -4.5 826.11 0.941499 4.13055
7 -3.5 821.946 0.945922 4.10973
8 -2.5 816.202 0.954889 4.08101
9 -1.5 813.202 0.969281 4.06601
10 -0.5 798.904 0.989463 3.99452
11 0.5 798.056 1.01005 3.99028
12 1.5 793.114 1.03073 3.96557
13 2.5 782.812 1.04569 3.91406
14 3.5 775.69 1.05498 3.87845
15 4.5 778.094 1.05965 3.89047
16 5.5 778.856 1.06002 3.89428
17 6.5 780.51 1.05621 3.90255
18 7.5 780.518 1.04782 3.90259
19 8.5 789.698 1.03348 3.94849
20 9.5 792.29 1.01261 3.96145

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@ -0,0 +1,52 @@
########################################################################
#### 3D droplet oscilation using many-body DPD simulation ###
#### ###
#### Created : Zhen Li (zhen_li@brown.edu) ###
#### Division of Applied Mathematics, Brown University. ###
#### ###
#### mDPD parameters follow the choice of the publication: ###
#### Z. Li et al. "Three dimensional flow structures in a moving ###
#### droplet on substrate: a dissipative particle dynamics study" ###
#### Physics of Fluids, 2013, 25: 072103. DOI: 10.1063/1.4812366 ###
########################################################################
units lj
dimension 3
boundary p p p
neighbor 0.3 bin
neigh_modify every 1 delay 0 check yes
atom_style mdpd
region mdpd block -25 25 -10 10 -10 10 units box
create_box 1 mdpd
lattice fcc 6
region film block -20 20 -7.5 7.5 -2.0 2.0 units box
create_atoms 1 region film
pair_style hybrid/overlay mdpd/rhosum mdpd 1.0 1.0 9872598
pair_coeff 1 1 mdpd/rhosum 0.75
pair_coeff 1 1 mdpd -40 25 18.0 1.0 0.75
mass 1 1.0
compute mythermo all temp
thermo 100
thermo_modify temp mythermo
thermo_modify flush yes
velocity all create 1.0 38497 loop local dist gaussian
fix mvv all mvv/dpd
#dump mydump all atom 100 atom.lammpstrj
#dump jpg all image 200 image.*.jpg type type zoom 5 adiam 0.5 &
# view 90 90 box no 0 size 600 200
#dump_modify jpg pad 4
#dump avi all movie 200 movie.avi type type zoom 5 adiam 0.5 &
# view 90 90 box no 0 size 600 200
#dump_modify avi pad 4
timestep 0.01
run 4000

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@ -0,0 +1,147 @@
LAMMPS (11 Aug 2017)
########################################################################
#### 3D droplet oscilation using many-body DPD simulation ###
#### ###
#### Created : Zhen Li (zhen_li@brown.edu) ###
#### Division of Applied Mathematics, Brown University. ###
#### ###
#### mDPD parameters follow the choice of the publication: ###
#### Z. Li et al. "Three dimensional flow structures in a moving ###
#### droplet on substrate: a dissipative particle dynamics study" ###
#### Physics of Fluids, 2013, 25: 072103. DOI: 10.1063/1.4812366 ###
########################################################################
units lj
dimension 3
boundary p p p
neighbor 0.3 bin
neigh_modify every 1 delay 0 check yes
atom_style mdpd
region mdpd block -25 25 -10 10 -10 10 units box
create_box 1 mdpd
Created orthogonal box = (-25 -10 -10) to (25 10 10)
1 by 1 by 1 MPI processor grid
lattice fcc 6
Lattice spacing in x,y,z = 0.87358 0.87358 0.87358
region film block -20 20 -7.5 7.5 -2.0 2.0 units box
create_atoms 1 region film
Created 14333 atoms
pair_style hybrid/overlay mdpd/rhosum mdpd 1.0 1.0 9872598
pair_coeff 1 1 mdpd/rhosum 0.75
pair_coeff 1 1 mdpd -40 25 18.0 1.0 0.75
mass 1 1.0
compute mythermo all temp
thermo 100
thermo_modify temp mythermo
thermo_modify flush yes
velocity all create 1.0 38497 loop local dist gaussian
fix mvv all mvv/dpd
dump mydump all atom 100 atom.lammpstrj
#dump jpg all image 200 image.*.jpg type type zoom 5 adiam 0.5 # view 90 90 box no 0 size 600 200
#dump_modify jpg pad 4
#dump avi all movie 200 movie.avi type type zoom 5 adiam 0.5 # view 90 90 box no 0 size 600 200
#dump_modify avi pad 4
timestep 0.01
run 4000
Neighbor list info ...
update every 1 steps, delay 0 steps, check yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 1.3
ghost atom cutoff = 1.3
binsize = 0.65, bins = 77 31 31
2 neighbor lists, perpetual/occasional/extra = 2 0 0
(1) pair mdpd/rhosum, perpetual
attributes: full, newton on
pair build: full/bin/atomonly
stencil: full/bin/3d
bin: standard
(2) pair mdpd, perpetual, half/full from (1)
attributes: half, newton on
pair build: halffull/newton
stencil: none
bin: none
Per MPI rank memory allocation (min/avg/max) = 9.931 | 9.931 | 9.931 Mbytes
Step Temp E_pair E_mol TotEng Press
0 1 -13.346542 0 -11.846647 -6.8495478
100 1.0321029 -7.2846779 0 -5.7366316 -0.77640205
200 1.042287 -6.9534532 0 -5.3901317 -0.27750815
300 1.0583027 -6.8483105 0 -5.2609672 -0.30347708
400 1.0493719 -6.8648608 0 -5.2909127 -0.15312495
500 1.0723786 -6.8341085 0 -5.2256528 0.017227511
600 1.0545695 -6.8152957 0 -5.2335517 -0.024362439
700 1.0507193 -6.8076033 0 -5.2316344 -0.07101536
800 1.0531856 -6.9378568 0 -5.3581886 -0.053943939
900 1.0442995 -6.8501126 0 -5.2837726 -0.13347942
1000 1.0335049 -6.8883554 0 -5.3382062 -0.18420426
1100 1.0287276 -6.8298226 0 -5.2868389 -0.12081558
1200 1.0322527 -6.9462828 0 -5.3980117 -0.18047625
1300 1.0599443 -6.9449975 0 -5.355192 -0.011763589
1400 1.0560932 -6.845479 0 -5.2614498 0.032130055
1500 1.0432786 -6.9035877 0 -5.338779 -0.10268662
1600 1.064183 -6.9116836 0 -5.3155205 -0.060722129
1700 1.0586249 -6.8768278 0 -5.2890013 0.037005566
1800 1.0576064 -7.0060193 0 -5.4197204 -0.036211254
1900 1.0595141 -6.838741 0 -5.2495807 -0.12395681
2000 1.0650509 -6.897976 0 -5.3005111 0.003594807
2100 1.0768273 -6.8874245 0 -5.2722962 0.033283489
2200 1.0511606 -6.9823162 0 -5.4056854 0.015008427
2300 1.0461138 -6.8820601 0 -5.3129988 0.064646933
2400 1.0485369 -6.9437148 0 -5.3710191 -0.16534939
2500 1.0507221 -6.9394786 0 -5.3635054 -0.098289859
2600 1.0518352 -6.8947578 0 -5.3171152 -0.011666785
2700 1.0402369 -6.9273377 0 -5.3670913 0.035267073
2800 1.0426109 -6.912024 0 -5.3482168 0.049597305
2900 1.0358928 -6.9574778 0 -5.4037471 -0.063216561
3000 1.0351023 -6.9844192 0 -5.4318742 -0.10323465
3100 1.0255005 -6.9382486 0 -5.4001052 -0.073954735
3200 1.0150616 -6.9843183 0 -5.4618321 -0.095136405
3300 1.0118112 -6.9522082 0 -5.4345973 -0.12686179
3400 1.0071522 -6.970158 0 -5.4595351 -0.012487475
3500 1.0041758 -6.9773019 0 -5.4711433 -0.098027653
3600 1.0189298 -6.9393039 0 -5.4110158 0.061631719
3700 1.012442 -6.9341423 0 -5.4155852 0.10442772
3800 1.0021246 -6.9594374 0 -5.4563553 -0.081535223
3900 1.0165002 -6.9045321 0 -5.3798882 -0.0088283303
4000 1.0077099 -6.9145511 0 -5.4030918 0.048349691
Loop time of 135.409 on 1 procs for 4000 steps with 14333 atoms
Performance: 25522.736 tau/day, 29.540 timesteps/s
99.9% CPU use with 1 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 93.074 | 93.074 | 93.074 | 0.0 | 68.74
Neigh | 40.192 | 40.192 | 40.192 | 0.0 | 29.68
Comm | 0.19625 | 0.19625 | 0.19625 | 0.0 | 0.14
Output | 0.41756 | 0.41756 | 0.41756 | 0.0 | 0.31
Modify | 1.0706 | 1.0706 | 1.0706 | 0.0 | 0.79
Other | | 0.4581 | | | 0.34
Nlocal: 14333 ave 14333 max 14333 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 11 ave 11 max 11 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 401803 ave 401803 max 401803 min
Histogram: 1 0 0 0 0 0 0 0 0 0
FullNghs: 803606 ave 803606 max 803606 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 803606
Ave neighs/atom = 56.0668
Neighbor list builds = 1050
Dangerous builds = 0
Please see the log.cite file for references relevant to this simulation
Total wall time: 0:02:15

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@ -0,0 +1,147 @@
LAMMPS (11 Aug 2017)
########################################################################
#### 3D droplet oscilation using many-body DPD simulation ###
#### ###
#### Created : Zhen Li (zhen_li@brown.edu) ###
#### Division of Applied Mathematics, Brown University. ###
#### ###
#### mDPD parameters follow the choice of the publication: ###
#### Z. Li et al. "Three dimensional flow structures in a moving ###
#### droplet on substrate: a dissipative particle dynamics study" ###
#### Physics of Fluids, 2013, 25: 072103. DOI: 10.1063/1.4812366 ###
########################################################################
units lj
dimension 3
boundary p p p
neighbor 0.3 bin
neigh_modify every 1 delay 0 check yes
atom_style mdpd
region mdpd block -25 25 -10 10 -10 10 units box
create_box 1 mdpd
Created orthogonal box = (-25 -10 -10) to (25 10 10)
4 by 1 by 1 MPI processor grid
lattice fcc 6
Lattice spacing in x,y,z = 0.87358 0.87358 0.87358
region film block -20 20 -7.5 7.5 -2.0 2.0 units box
create_atoms 1 region film
Created 14333 atoms
pair_style hybrid/overlay mdpd/rhosum mdpd 1.0 1.0 9872598
pair_coeff 1 1 mdpd/rhosum 0.75
pair_coeff 1 1 mdpd -40 25 18.0 1.0 0.75
mass 1 1.0
compute mythermo all temp
thermo 100
thermo_modify temp mythermo
thermo_modify flush yes
velocity all create 1.0 38497 loop local dist gaussian
fix mvv all mvv/dpd
dump mydump all atom 100 atom.lammpstrj
#dump jpg all image 200 image.*.jpg type type zoom 5 adiam 0.5 # view 90 90 box no 0 size 600 200
#dump_modify jpg pad 4
#dump avi all movie 200 movie.avi type type zoom 5 adiam 0.5 # view 90 90 box no 0 size 600 200
#dump_modify avi pad 4
timestep 0.01
run 4000
Neighbor list info ...
update every 1 steps, delay 0 steps, check yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 1.3
ghost atom cutoff = 1.3
binsize = 0.65, bins = 77 31 31
2 neighbor lists, perpetual/occasional/extra = 2 0 0
(1) pair mdpd/rhosum, perpetual
attributes: full, newton on
pair build: full/bin/atomonly
stencil: full/bin/3d
bin: standard
(2) pair mdpd, perpetual, half/full from (1)
attributes: half, newton on
pair build: halffull/newton
stencil: none
bin: none
Per MPI rank memory allocation (min/avg/max) = 6.265 | 6.655 | 7.045 Mbytes
Step Temp E_pair E_mol TotEng Press
0 1 -13.346542 0 -11.846647 -6.9757225
100 1.0406108 -7.2500697 0 -5.6892624 -0.80306477
200 1.0535506 -6.9452928 0 -5.3650772 -0.39911584
300 1.0644295 -6.8599907 0 -5.2634577 -0.2997968
400 1.0780123 -6.9471342 0 -5.3302286 -0.06274869
500 1.0672153 -6.8269984 0 -5.2262872 0.021251762
600 1.0634304 -6.8366569 0 -5.2416226 -0.021863333
700 1.0544807 -6.8272074 0 -5.2455967 -0.0064688066
800 1.0556172 -6.8859788 0 -5.3026634 0.023983333
900 1.0436201 -6.9246523 0 -5.3593313 -0.12409618
1000 1.0617016 -6.8632331 0 -5.2707919 -0.1145505
1100 1.0323831 -6.951554 0 -5.4030874 -0.030031884
1200 1.0407785 -6.931048 0 -5.3699892 -0.018362136
1300 1.0380953 -6.8785296 0 -5.3214953 -0.099308737
1400 1.0418898 -6.8998 0 -5.3370743 -0.14199421
1500 1.0487254 -6.9671212 0 -5.3941429 -0.12132644
1600 1.0561042 -6.8948881 0 -5.3108424 -0.09627292
1700 1.0524479 -6.9531441 0 -5.3745823 -0.11959782
1800 1.0541197 -6.9219819 0 -5.3409126 0.032964029
1900 1.0531221 -6.8805815 0 -5.3010085 0.030124685
2000 1.0531819 -6.8612868 0 -5.2816242 -0.076876781
2100 1.0757791 -6.919875 0 -5.3063189 -0.04060439
2200 1.069423 -6.9005754 0 -5.2965527 0.015347467
2300 1.0403109 -6.9015402 0 -5.3411827 0.0034687897
2400 1.0547448 -6.9325539 0 -5.3505471 -0.021202325
2500 1.0404195 -6.8494675 0 -5.2889472 0.086947847
2600 1.0499828 -6.9861392 0 -5.4112749 -0.018079308
2700 1.0294278 -6.8525151 0 -5.3084811 0.16911472
2800 1.0220652 -6.8993978 0 -5.366407 0.064820531
2900 1.0347904 -6.9322703 0 -5.3801929 -0.11384964
3000 1.0391372 -6.9519088 0 -5.3933117 0.003050577
3100 1.0335828 -7.0090074 0 -5.4587413 -0.17366664
3200 1.0211896 -6.9421289 0 -5.4104513 0.025299853
3300 1.0019232 -6.9426488 0 -5.4398688 -0.098334724
3400 1.0203541 -6.9310981 0 -5.4006737 -0.0015544982
3500 1.0076794 -6.9519932 0 -5.4405796 -0.056956902
3600 1.0086525 -6.9620979 0 -5.4492247 0.020014884
3700 1.0046112 -7.0011625 0 -5.4943508 -0.083936527
3800 1.0096867 -6.9470382 0 -5.4326138 -0.089521759
3900 1.0074482 -6.9959414 0 -5.4848745 -0.11873698
4000 1.01222 -6.9535694 0 -5.4353454 0.042191466
Loop time of 63.0327 on 4 procs for 4000 steps with 14333 atoms
Performance: 54828.695 tau/day, 63.459 timesteps/s
98.8% CPU use with 4 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 16.591 | 29.795 | 42.814 | 236.6 | 47.27
Neigh | 2.0347 | 10.239 | 18.555 | 255.6 | 16.24
Comm | 0.70099 | 6.0601 | 11.386 | 207.4 | 9.61
Output | 0.20713 | 0.40902 | 0.61087 | 31.5 | 0.65
Modify | 0.058089 | 0.27033 | 0.4851 | 40.7 | 0.43
Other | | 16.26 | | | 25.79
Nlocal: 3583.25 ave 7207 max 0 min
Histogram: 2 0 0 0 0 0 0 0 0 2
Nghost: 1055.75 ave 2131 max 0 min
Histogram: 2 0 0 0 0 0 0 0 0 2
Neighs: 100549 ave 202192 max 0 min
Histogram: 2 0 0 0 0 0 0 0 0 2
FullNghs: 201098 ave 404372 max 0 min
Histogram: 2 0 0 0 0 0 0 0 0 2
Total # of neighbors = 804390
Ave neighs/atom = 56.1215
Neighbor list builds = 1049
Dangerous builds = 0
Please see the log.cite file for references relevant to this simulation
Total wall time: 0:01:03

View File

@ -0,0 +1,24 @@
# Chunk-averaged data for fix stat and group c_cc2
# Timestep Number-of-chunks Total-count
# Chunk Coord1 Ncount c_cc1 c_cc2
100 20 16000
1 -9.5 797.17 0.986661 1.0077
2 -8.5 802.61 0.967974 1.02003
3 -7.5 795.46 0.957045 1.02873
4 -6.5 806.46 0.951271 1.03428
5 -5.5 802.34 0.94898 1.03692
6 -4.5 799.84 0.949378 1.03673
7 -3.5 798.4 0.952505 1.03374
8 -2.5 800.36 0.959322 1.02778
9 -1.5 797.65 0.971516 1.01867
10 -0.5 808.88 0.990644 1.00626
11 0.5 786.29 1.00924 0.993828
12 1.5 807.16 1.02831 0.981436
13 2.5 797.54 1.04071 0.972184
14 3.5 799.67 1.04749 0.966258
15 4.5 799.61 1.05063 0.963256
16 5.5 806.11 1.05105 0.963052
17 6.5 803.67 1.04877 0.965688
18 7.5 797.39 1.04305 0.971187
19 8.5 801.85 1.03208 0.97993
20 9.5 791.54 1.01351 0.992209

View File

@ -0,0 +1,24 @@
# Chunk-averaged data for fix stat and group c_cc2
# Timestep Number-of-chunks Total-count
# Chunk Coord1 Ncount c_cc1 c_cc2
100 20 16000
1 -9.5 806.92 0.986675 1.00766
2 -8.5 798.01 0.96792 1.02003
3 -7.5 805.43 0.956909 1.02883
4 -6.5 800.54 0.951207 1.03432
5 -5.5 794.14 0.948967 1.03691
6 -4.5 799.75 0.949379 1.03672
7 -3.5 799.65 0.952492 1.03374
8 -2.5 799.94 0.959331 1.02778
9 -1.5 800.96 0.971664 1.01861
10 -0.5 803.97 0.99074 1.00622
11 0.5 800.66 1.00949 0.993673
12 1.5 779.22 1.02824 0.981461
13 2.5 809.13 1.04056 0.972274
14 3.5 805.23 1.04747 0.966272
15 4.5 795.95 1.05061 0.96327
16 5.5 796.4 1.05105 0.963035
17 6.5 806.1 1.04883 0.965621
18 7.5 806.41 1.04305 0.971224
19 8.5 792.2 1.03211 0.979955
20 9.5 799.39 1.01362 0.992156

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@ -0,0 +1,54 @@
########################################################################
### Pure diffusion with a reaction source term analog of a periodic ###
### Poiseuille flow problem using transport DPD (tDPD) simulation ###
### ###
### Created : Zhen Li (zhen_li@brown.edu) ###
### Division of Applied Mathematics, Brown University. ###
### ###
### tDPD system setup follows Fig.1 in the publication: ###
### Z. Li, A. Yazdani, A. Tartakovsky and G.E. Karniadakis. ###
### "Transport dissipative particle dynamics model for mesoscopic ###
### advection-diffusion-reaction problems. J. Chem. Phys., ###
### 2015, 143: 014101. DOI: 10.1063/1.4923254 ###
########################################################################
units lj
dimension 3
boundary p p p
neighbor 0.2 bin
neigh_modify every 1 delay 0 check yes
atom_style tdpd 2
region tdpd block -10 10 -10 10 -5 5 units box
create_box 1 tdpd
create_atoms 1 random 16000 276438 NULL
mass 1 1.0
set atom * cc 1 1.0
set atom * cc 2 1.0
pair_style tdpd 1.0 1.58 9872598
pair_coeff 1 1 18.75 4.5 0.41 1.58 1.58 1.0 1.0E-5 2.0 3.0 1.0E-5 2.0
compute mythermo all temp
thermo 50
thermo_modify temp mythermo
thermo_modify flush yes
velocity all create 1.0 432982 loop local dist gaussian
fix mvv all mvv/tdpd 0.5
fix upper1 all tdpd/source 1 cuboid 0.0 5.0 0.0 20.0 10.0 10.0 0.01
fix lower1 all tdpd/source 1 cuboid 0.0 -5.0 0.0 20.0 10.0 10.0 -0.01
fix upper2 all tdpd/source 2 cuboid 0.0 5.0 0.0 20.0 10.0 10.0 -0.01
fix lower2 all tdpd/source 2 cuboid 0.0 -5.0 0.0 20.0 10.0 10.0 0.01
timestep 0.01
run 500
reset_timestep 0
compute cc1 all tdpd/cc/atom 1
compute cc2 all tdpd/cc/atom 2
compute bin all chunk/atom bin/1d y 0.0 1.0
fix stat all ave/chunk 1 100 100 bin c_cc1 c_cc2 norm sample file cc.profile
run 100

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LAMMPS (11 Aug 2017)
########################################################################
### Pure diffusion with a reaction source term analog of a periodic ###
### Poiseuille flow problem using transport DPD (tDPD) simulation ###
### ###
### Created : Zhen Li (zhen_li@brown.edu) ###
### Division of Applied Mathematics, Brown University. ###
### ###
### tDPD system setup follows Fig.1 in the publication: ###
### Z. Li, A. Yazdani, A. Tartakovsky and G.E. Karniadakis. ###
### "Transport dissipative particle dynamics model for mesoscopic ###
### advection-diffusion-reaction problems. J. Chem. Phys., ###
### 2015, 143: 014101. DOI: 10.1063/1.4923254 ###
########################################################################
units lj
dimension 3
boundary p p p
neighbor 0.2 bin
neigh_modify every 1 delay 0 check yes
atom_style tdpd 2
region tdpd block -10 10 -10 10 -5 5 units box
create_box 1 tdpd
Created orthogonal box = (-10 -10 -5) to (10 10 5)
1 by 1 by 1 MPI processor grid
create_atoms 1 random 16000 276438 NULL
Created 16000 atoms
mass 1 1.0
set atom * cc 1 1.0
16000 settings made for cc index 1
set atom * cc 2 1.0
16000 settings made for cc index 2
pair_style tdpd 1.0 1.58 9872598
pair_coeff 1 1 18.75 4.5 0.41 1.58 1.58 1.0 1.0E-5 2.0 3.0 1.0E-5 2.0
compute mythermo all temp
thermo 50
thermo_modify temp mythermo
thermo_modify flush yes
velocity all create 1.0 432982 loop local dist gaussian
fix mvv all mvv/tdpd 0.5
fix upper1 all tdpd/source 1 cuboid 0.0 5.0 0.0 20.0 10.0 10.0 0.01
fix lower1 all tdpd/source 1 cuboid 0.0 -5.0 0.0 20.0 10.0 10.0 -0.01
fix upper2 all tdpd/source 2 cuboid 0.0 5.0 0.0 20.0 10.0 10.0 -0.01
fix lower2 all tdpd/source 2 cuboid 0.0 -5.0 0.0 20.0 10.0 10.0 0.01
timestep 0.01
run 500
Neighbor list info ...
update every 1 steps, delay 0 steps, check yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 1.78
ghost atom cutoff = 1.78
binsize = 0.89, bins = 23 23 12
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair tdpd, perpetual
attributes: half, newton on
pair build: half/bin/atomonly/newton
stencil: half/bin/3d/newton
bin: standard
Per MPI rank memory allocation (min/avg/max) = 11.3 | 11.3 | 11.3 Mbytes
Step Temp E_pair E_mol TotEng Press
0 1 48.948932 0 50.448838 202.19166
50 0.99837766 43.949877 0 45.447349 195.80936
100 0.99846831 43.756995 0 45.254604 198.22348
150 1.0026903 43.72408 0 45.228021 196.61676
200 1.0063144 43.722388 0 45.231765 194.17954
250 1.0032304 43.721864 0 45.226615 197.85829
300 0.9932656 43.703526 0 45.193331 196.57406
350 1.0002916 43.720498 0 45.220841 193.55346
400 0.99475486 43.722965 0 45.215004 196.81546
450 1.0011803 43.712447 0 45.214124 200.46118
500 1.0009006 43.708984 0 45.210241 197.38953
Loop time of 96.0326 on 1 procs for 500 steps with 16000 atoms
Performance: 4498.474 tau/day, 5.207 timesteps/s
99.9% CPU use with 1 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 90.083 | 90.083 | 90.083 | 0.0 | 93.80
Neigh | 5.049 | 5.049 | 5.049 | 0.0 | 5.26
Comm | 0.34141 | 0.34141 | 0.34141 | 0.0 | 0.36
Output | 0.00092816 | 0.00092816 | 0.00092816 | 0.0 | 0.00
Modify | 0.45991 | 0.45991 | 0.45991 | 0.0 | 0.48
Other | | 0.09865 | | | 0.10
Nlocal: 16000 ave 16000 max 16000 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 14091 ave 14091 max 14091 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 749379 ave 749379 max 749379 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 749379
Ave neighs/atom = 46.8362
Neighbor list builds = 183
Dangerous builds = 0
reset_timestep 0
compute cc1 all tdpd/cc/atom 1
compute cc2 all tdpd/cc/atom 2
compute bin all chunk/atom bin/1d y 0.0 1.0
fix stat all ave/chunk 1 100 100 bin c_cc1 c_cc2 norm sample file cc.profile
run 100
Per MPI rank memory allocation (min/avg/max) = 11.8 | 11.8 | 11.8 Mbytes
Step Temp E_pair E_mol TotEng Press
0 1.0009006 43.708984 0 45.210241 199.3205
50 1.0007276 43.704844 0 45.205842 197.77053
100 1.0039032 43.714201 0 45.219961 197.31118
Loop time of 19.0326 on 1 procs for 100 steps with 16000 atoms
Performance: 4539.577 tau/day, 5.254 timesteps/s
99.9% CPU use with 1 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 17.842 | 17.842 | 17.842 | 0.0 | 93.74
Neigh | 0.98674 | 0.98674 | 0.98674 | 0.0 | 5.18
Comm | 0.066013 | 0.066013 | 0.066013 | 0.0 | 0.35
Output | 0.00016284 | 0.00016284 | 0.00016284 | 0.0 | 0.00
Modify | 0.11795 | 0.11795 | 0.11795 | 0.0 | 0.62
Other | | 0.02012 | | | 0.11
Nlocal: 16000 ave 16000 max 16000 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 14126 ave 14126 max 14126 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 748927 ave 748927 max 748927 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 748927
Ave neighs/atom = 46.8079
Neighbor list builds = 37
Dangerous builds = 0
Please see the log.cite file for references relevant to this simulation
Total wall time: 0:01:55

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@ -0,0 +1,146 @@
LAMMPS (11 Aug 2017)
########################################################################
### Pure diffusion with a reaction source term analog of a periodic ###
### Poiseuille flow problem using transport DPD (tDPD) simulation ###
### ###
### Created : Zhen Li (zhen_li@brown.edu) ###
### Division of Applied Mathematics, Brown University. ###
### ###
### tDPD system setup follows Fig.1 in the publication: ###
### Z. Li, A. Yazdani, A. Tartakovsky and G.E. Karniadakis. ###
### "Transport dissipative particle dynamics model for mesoscopic ###
### advection-diffusion-reaction problems. J. Chem. Phys., ###
### 2015, 143: 014101. DOI: 10.1063/1.4923254 ###
########################################################################
units lj
dimension 3
boundary p p p
neighbor 0.2 bin
neigh_modify every 1 delay 0 check yes
atom_style tdpd 2
region tdpd block -10 10 -10 10 -5 5 units box
create_box 1 tdpd
Created orthogonal box = (-10 -10 -5) to (10 10 5)
2 by 2 by 1 MPI processor grid
create_atoms 1 random 16000 276438 NULL
Created 16000 atoms
mass 1 1.0
set atom * cc 1 1.0
16000 settings made for cc index 1
set atom * cc 2 1.0
16000 settings made for cc index 2
pair_style tdpd 1.0 1.58 9872598
pair_coeff 1 1 18.75 4.5 0.41 1.58 1.58 1.0 1.0E-5 2.0 3.0 1.0E-5 2.0
compute mythermo all temp
thermo 50
thermo_modify temp mythermo
thermo_modify flush yes
velocity all create 1.0 432982 loop local dist gaussian
fix mvv all mvv/tdpd 0.5
fix upper1 all tdpd/source 1 cuboid 0.0 5.0 0.0 20.0 10.0 10.0 0.01
fix lower1 all tdpd/source 1 cuboid 0.0 -5.0 0.0 20.0 10.0 10.0 -0.01
fix upper2 all tdpd/source 2 cuboid 0.0 5.0 0.0 20.0 10.0 10.0 -0.01
fix lower2 all tdpd/source 2 cuboid 0.0 -5.0 0.0 20.0 10.0 10.0 0.01
timestep 0.01
run 500
Neighbor list info ...
update every 1 steps, delay 0 steps, check yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 1.78
ghost atom cutoff = 1.78
binsize = 0.89, bins = 23 23 12
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair tdpd, perpetual
attributes: half, newton on
pair build: half/bin/atomonly/newton
stencil: half/bin/3d/newton
bin: standard
Per MPI rank memory allocation (min/avg/max) = 4.814 | 4.823 | 4.829 Mbytes
Step Temp E_pair E_mol TotEng Press
0 1 48.948932 0 50.448838 199.65978
50 1.0153476 43.948796 0 45.471722 198.3346
100 1.0064284 43.754875 0 45.264424 197.5308
150 0.99609985 43.726751 0 45.220807 197.50623
200 1.0016604 43.720283 0 45.22268 197.81129
250 1.0054979 43.718568 0 45.22672 195.79405
300 0.9997618 43.716617 0 45.216166 197.84788
350 0.99170101 43.72093 0 45.208389 196.07711
400 1.0043692 43.71648 0 45.22294 199.55247
450 1.0086263 43.709988 0 45.222833 198.20516
500 1.0029076 43.717879 0 45.222146 197.26281
Loop time of 24.5533 on 4 procs for 500 steps with 16000 atoms
Performance: 17594.412 tau/day, 20.364 timesteps/s
99.9% CPU use with 4 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 22.236 | 22.418 | 22.736 | 4.0 | 91.30
Neigh | 1.2759 | 1.2883 | 1.3077 | 1.1 | 5.25
Comm | 0.35749 | 0.69526 | 0.88462 | 24.1 | 2.83
Output | 0.00043321 | 0.00050318 | 0.00070691 | 0.0 | 0.00
Modify | 0.11555 | 0.11648 | 0.11888 | 0.4 | 0.47
Other | | 0.03473 | | | 0.14
Nlocal: 4000 ave 4012 max 3982 min
Histogram: 1 0 0 0 0 1 0 0 0 2
Nghost: 5986.25 ave 6016 max 5956 min
Histogram: 1 0 0 0 1 0 1 0 0 1
Neighs: 187309 ave 188264 max 186087 min
Histogram: 1 0 0 0 1 0 0 1 0 1
Total # of neighbors = 749235
Ave neighs/atom = 46.8272
Neighbor list builds = 180
Dangerous builds = 0
reset_timestep 0
compute cc1 all tdpd/cc/atom 1
compute cc2 all tdpd/cc/atom 2
compute bin all chunk/atom bin/1d y 0.0 1.0
fix stat all ave/chunk 1 100 100 bin c_cc1 c_cc2 norm sample file cc.profile
run 100
Per MPI rank memory allocation (min/avg/max) = 5.065 | 5.074 | 5.082 Mbytes
Step Temp E_pair E_mol TotEng Press
0 1.0029076 43.717879 0 45.222146 198.45789
50 1.0077982 43.713264 0 45.224867 196.56183
100 1.0036823 43.708022 0 45.213451 196.00815
Loop time of 4.79577 on 4 procs for 100 steps with 16000 atoms
Performance: 18015.870 tau/day, 20.852 timesteps/s
99.9% CPU use with 4 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 4.3481 | 4.39 | 4.4398 | 1.7 | 91.54
Neigh | 0.25477 | 0.25675 | 0.25963 | 0.4 | 5.35
Comm | 0.059327 | 0.11194 | 0.15608 | 11.0 | 2.33
Output | 0.00011206 | 0.00011748 | 0.00011992 | 0.0 | 0.00
Modify | 0.030417 | 0.030622 | 0.030739 | 0.1 | 0.64
Other | | 0.006301 | | | 0.13
Nlocal: 4000 ave 4010 max 3987 min
Histogram: 1 0 0 0 0 1 1 0 0 1
Nghost: 5985.25 ave 6025 max 5959 min
Histogram: 2 0 0 0 0 1 0 0 0 1
Neighs: 187304 ave 188092 max 186449 min
Histogram: 1 0 0 0 0 2 0 0 0 1
Total # of neighbors = 749216
Ave neighs/atom = 46.826
Neighbor list builds = 38
Dangerous builds = 0
Please see the log.cite file for references relevant to this simulation
Total wall time: 0:00:29

View File

@ -9,8 +9,8 @@ import sys,os,subprocess
# help message
help = """
Syntax from src dir: make lib-gpu args="-m machine -h hdir -a arch -p precision -e esuffix -m -o osuffix"
Syntax from lib dir: python Install.py -m machine -h hdir -a arch -p precision -e esuffix -m -o osuffix
Syntax from src dir: make lib-gpu args="-m machine -h hdir -a arch -p precision -e esuffix -b -o osuffix"
Syntax from lib dir: python Install.py -m machine -h hdir -a arch -p precision -e esuffix -b -o osuffix
specify one or more options, order does not matter

View File

@ -1,5 +1,22 @@
# Change Log
## [2.04.00](https://github.com/kokkos/kokkos/tree/2.04.00) (2017-08-16)
[Full Changelog](https://github.com/kokkos/kokkos/compare/2.03.13...2.04.00)
**Implemented enhancements:**
- Added ROCm backend to support AMD GPUs
- Kokkos::complex\<T\> behaves slightly differently from std::complex\<T\> [\#1011](https://github.com/kokkos/kokkos/issues/1011)
- Kokkos::Experimental::Crs constructor arguments were in the wrong order [\#992](https://github.com/kokkos/kokkos/issues/992)
- Work graph construction ease-of-use (one lambda for count and fill) [\#991](https://github.com/kokkos/kokkos/issues/991)
- when\_all returns pointer of futures (improved interface) [\#990](https://github.com/kokkos/kokkos/issues/990)
- Allow assignment of LayoutLeft to LayoutRight or vice versa for rank-0 Views [\#594](https://github.com/kokkos/kokkos/issues/594)
- Changed the meaning of Kokkos\_ENABLE\_CXX11\_DISPATCH\_LAMBDA [\#1035](https://github.com/kokkos/kokkos/issues/1035)
**Fixed bugs:**
- memory pool default constructor does not properly set member variables. [\#1007](https://github.com/kokkos/kokkos/issues/1007)
## [2.03.13](https://github.com/kokkos/kokkos/tree/2.03.13) (2017-07-27)
[Full Changelog](https://github.com/kokkos/kokkos/compare/2.03.05...2.03.13)

View File

@ -4,10 +4,16 @@
KOKKOS_PATH=../../lib/kokkos
CXXFLAGS=$(CCFLAGS)
# Options: Cuda,OpenMP,Pthreads,Qthreads,Serial
# Options: Cuda,ROCm,OpenMP,Pthreads,Qthreads,Serial
KOKKOS_DEVICES ?= "OpenMP"
#KOKKOS_DEVICES ?= "Pthreads"
# Options: KNC,SNB,HSW,Kepler,Kepler30,Kepler32,Kepler35,Kepler37,Maxwell,Maxwell50,Maxwell52,Maxwell53,Pascal60,Pascal61,ARMv80,ARMv81,ARMv8-ThunderX,BGQ,Power7,Power8,Power9,KNL,BDW,SKX
# Options:
# Intel: KNC,KNL,SNB,HSW,BDW,SKX
# NVIDIA: Kepler,Kepler30,Kepler32,Kepler35,Kepler37,Maxwell,Maxwell50,Maxwell52,Maxwell53,Pascal60,Pascal61
# ARM: ARMv80,ARMv81,ARMv8-ThunderX
# IBM: BGQ,Power7,Power8,Power9
# AMD-GPUS: Kaveri,Carrizo,Fiji,Vega
# AMD-CPUS: AMDAVX,Ryzen,Epyc
KOKKOS_ARCH ?= ""
# Options: yes,no
KOKKOS_DEBUG ?= "no"
@ -43,8 +49,8 @@ KOKKOS_INTERNAL_CUDA_USE_UVM := $(strip $(shell echo $(KOKKOS_CUDA_OPTIONS) | gr
KOKKOS_INTERNAL_CUDA_USE_RELOC := $(strip $(shell echo $(KOKKOS_CUDA_OPTIONS) | grep "rdc" | wc -l))
KOKKOS_INTERNAL_CUDA_USE_LAMBDA := $(strip $(shell echo $(KOKKOS_CUDA_OPTIONS) | grep "enable_lambda" | wc -l))
# Check for Kokkos Host Execution Spaces one of which must be on.
KOKKOS_INTERNAL_USE_OPENMPTARGET := $(strip $(shell echo $(KOKKOS_DEVICES) | grep OpenMPTarget | wc -l))
KOKKOS_INTERNAL_USE_OPENMP := $(strip $(shell echo $(subst OpenMPTarget,,$(KOKKOS_DEVICES)) | grep OpenMP | wc -l))
KOKKOS_INTERNAL_USE_PTHREADS := $(strip $(shell echo $(KOKKOS_DEVICES) | grep Pthread | wc -l))
KOKKOS_INTERNAL_USE_QTHREADS := $(strip $(shell echo $(KOKKOS_DEVICES) | grep Qthreads | wc -l))
@ -60,6 +66,8 @@ endif
# Check for other Execution Spaces.
KOKKOS_INTERNAL_USE_CUDA := $(strip $(shell echo $(KOKKOS_DEVICES) | grep Cuda | wc -l))
KOKKOS_INTERNAL_USE_ROCM := $(strip $(shell echo $(KOKKOS_DEVICES) | grep ROCm | wc -l))
KOKKOS_INTERNAL_USE_OPENMPTARGET := $(strip $(shell echo $(KOKKOS_DEVICES) | grep OpenMPTarget | wc -l))
ifeq ($(KOKKOS_INTERNAL_USE_CUDA), 1)
KOKKOS_INTERNAL_NVCC_PATH := $(shell which nvcc)
@ -87,6 +95,7 @@ ifneq ($(MPICH_CXX),)
endif
KOKKOS_INTERNAL_COMPILER_CLANG := $(strip $(shell $(CXX) --version 2>&1 | grep clang | wc -l))
KOKKOS_INTERNAL_COMPILER_APPLE_CLANG := $(strip $(shell $(CXX) --version 2>&1 | grep "apple-darwin" | wc -l))
KOKKOS_INTERNAL_COMPILER_HCC := $(strip $(shell $(CXX) --version 2>&1 | grep HCC | wc -l))
ifeq ($(KOKKOS_INTERNAL_COMPILER_CLANG), 2)
KOKKOS_INTERNAL_COMPILER_CLANG = 1
@ -99,6 +108,10 @@ endif
ifeq ($(KOKKOS_INTERNAL_COMPILER_APPLE_CLANG), 1)
KOKKOS_INTERNAL_COMPILER_CLANG = 0
endif
# AMD HCC passes both clang and hcc test so turn off clang
ifeq ($(KOKKOS_INTERNAL_COMPILER_HCC), 1)
KOKKOS_INTENAL_COMPILER_CLANG = 0
endif
ifeq ($(KOKKOS_INTERNAL_COMPILER_CLANG), 1)
KOKKOS_INTERNAL_COMPILER_CLANG_VERSION := $(shell clang --version | grep version | cut -d ' ' -f3 | tr -d '.')
@ -183,8 +196,12 @@ else
ifeq ($(KOKKOS_INTERNAL_COMPILER_CRAY), 1)
KOKKOS_INTERNAL_CXX11_FLAG := -hstd=c++11
else
KOKKOS_INTERNAL_CXX11_FLAG := --std=c++11
KOKKOS_INTERNAL_CXX1Z_FLAG := --std=c++1z
ifeq ($(KOKKOS_INTERNAL_COMPILER_HCC), 1)
KOKKOS_INTERNAL_CXX11_FLAG :=
else
KOKKOS_INTERNAL_CXX11_FLAG := --std=c++11
KOKKOS_INTERNAL_CXX1Z_FLAG := --std=c++1z
endif
endif
endif
endif
@ -259,6 +276,13 @@ KOKKOS_INTERNAL_USE_ARCH_IBM := $(strip $(shell echo $(KOKKOS_INTERNAL_USE_ARCH_
# AMD based.
KOKKOS_INTERNAL_USE_ARCH_AMDAVX := $(strip $(shell echo $(KOKKOS_ARCH) | grep AMDAVX | wc -l))
KOKKOS_INTERNAL_USE_ARCH_RYZEN := $(strip $(shell echo $(KOKKOS_ARCH) | grep Ryzen | wc -l))
KOKKOS_INTERNAL_USE_ARCH_EPYC := $(strip $(shell echo $(KOKKOS_ARCH) | grep Epyc | wc -l))
KOKKOS_INTERNAL_USE_ARCH_KAVERI := $(strip $(shell echo $(KOKKOS_ARCH) | grep Kaveri | wc -l))
KOKKOS_INTERNAL_USE_ARCH_CARRIZO := $(strip $(shell echo $(KOKKOS_ARCH) | grep Carrizo | wc -l))
KOKKOS_INTERNAL_USE_ARCH_FIJI := $(strip $(shell echo $(KOKKOS_ARCH) | grep Fiji | wc -l))
KOKKOS_INTERNAL_USE_ARCH_VEGA := $(strip $(shell echo $(KOKKOS_ARCH) | grep Vega | wc -l))
KOKKOS_INTERNAL_USE_ARCH_GFX901 := $(strip $(shell echo $(KOKKOS_ARCH) | grep gfx901 | wc -l))
# Any AVX?
KOKKOS_INTERNAL_USE_ARCH_SSE42 := $(strip $(shell echo $(KOKKOS_INTERNAL_USE_ARCH_WSM) | bc ))
@ -271,6 +295,7 @@ KOKKOS_INTERNAL_USE_ARCH_AVX512XEON := $(strip $(shell echo $(KOKKOS_INTERNAL_US
KOKKOS_INTERNAL_USE_ISA_X86_64 := $(strip $(shell echo $(KOKKOS_INTERNAL_USE_ARCH_WSM)+$(KOKKOS_INTERNAL_USE_ARCH_SNB)+$(KOKKOS_INTERNAL_USE_ARCH_HSW)+$(KOKKOS_INTERNAL_USE_ARCH_BDW)+$(KOKKOS_INTERNAL_USE_ARCH_KNL)+$(KOKKOS_INTERNAL_USE_ARCH_SKX) | bc ))
KOKKOS_INTERNAL_USE_ISA_KNC := $(strip $(shell echo $(KOKKOS_INTERNAL_USE_ARCH_KNC) | bc ))
KOKKOS_INTERNAL_USE_ISA_POWERPCLE := $(strip $(shell echo $(KOKKOS_INTERNAL_USE_ARCH_POWER8)+$(KOKKOS_INTERNAL_USE_ARCH_POWER9) | bc ))
KOKKOS_INTERNAL_USE_ISA_POWERPCBE := $(strip $(shell echo $(KOKKOS_INTERNAL_USE_ARCH_POWER7) | bc ))
# Decide whether we can support transactional memory
KOKKOS_INTERNAL_USE_TM := $(strip $(shell echo $(KOKKOS_INTERNAL_USE_ARCH_BDW)+$(KOKKOS_INTERNAL_USE_ARCH_SKX) | bc ))
@ -319,8 +344,12 @@ ifeq ($(KOKKOS_INTERNAL_USE_CUDA), 1)
tmp := $(shell echo "\#define KOKKOS_HAVE_CUDA 1" >> KokkosCore_config.tmp )
endif
ifeq ($(KOKKOS_INTERNAL_USE_ROCM), 1)
tmp := $(shell echo '\#define KOKKOS_ENABLE_ROCM 1' >> KokkosCore_config.tmp)
endif
ifeq ($(KOKKOS_INTERNAL_USE_OPENMPTARGET), 1)
tmp := $(shell echo '\#define KOKKOS_ENABLE_OPENMPTARGET 1' >> KokkosCore_config.tmp)
tmp := $(shell echo '\#define KOKKOS_ENABLE_OPENMPTARGET 1' >> KokkosCore_config.tmp)
endif
ifeq ($(KOKKOS_INTERNAL_USE_OPENMP), 1)
@ -363,6 +392,12 @@ ifeq ($(KOKKOS_INTERNAL_USE_ISA_POWERPCLE), 1)
tmp := $(shell echo "\#endif" >> KokkosCore_config.tmp )
endif
ifeq ($(KOKKOS_INTERNAL_USE_ISA_POWERPCBE), 1)
tmp := $(shell echo "\#ifndef __CUDA_ARCH__" >> KokkosCore_config.tmp )
tmp := $(shell echo "\#define KOKKOS_USE_ISA_POWERPCBE" >> KokkosCore_config.tmp )
tmp := $(shell echo "\#endif" >> KokkosCore_config.tmp )
endif
tmp := $(shell echo "/* General Settings */" >> KokkosCore_config.tmp)
ifeq ($(KOKKOS_INTERNAL_ENABLE_CXX11), 1)
KOKKOS_CXXFLAGS += $(KOKKOS_INTERNAL_CXX11_FLAG)
@ -561,6 +596,18 @@ ifeq ($(KOKKOS_INTERNAL_USE_ARCH_AVX), 1)
endif
endif
ifeq ($(KOKKOS_INTERNAL_USE_ARCH_POWER7), 1)
tmp := $(shell echo "\#define KOKKOS_ARCH_POWER7 1" >> KokkosCore_config.tmp )
ifeq ($(KOKKOS_INTERNAL_COMPILER_PGI), 1)
else
# Assume that this is a really a GNU compiler or it could be XL on P8.
KOKKOS_CXXFLAGS += -mcpu=power7 -mtune=power7
KOKKOS_LDFLAGS += -mcpu=power7 -mtune=power7
endif
endif
ifeq ($(KOKKOS_INTERNAL_USE_ARCH_POWER8), 1)
tmp := $(shell echo "\#define KOKKOS_ARCH_POWER8 1" >> KokkosCore_config.tmp )
@ -742,7 +789,49 @@ ifeq ($(KOKKOS_INTERNAL_USE_CUDA), 1)
endif
endif
# Figure out the architecture flag for ROCm.
ifeq ($(KOKKOS_INTERNAL_USE_ROCM), 1)
# Lets start with adding architecture defines
ifeq ($(KOKKOS_INTERNAL_USE_ARCH_KAVERI), 1)
tmp := $(shell echo "\#define KOKKOS_ARCH_ROCM 701" >> KokkosCore_config.tmp )
tmp := $(shell echo "\#define KOKKOS_ARCH_KAVERI 1" >> KokkosCore_config.tmp )
KOKKOS_INTERNAL_ROCM_ARCH_FLAG := --amdgpu-target=gfx701
endif
ifeq ($(KOKKOS_INTERNAL_USE_ARCH_CARRIZO), 1)
tmp := $(shell echo "\#define KOKKOS_ARCH_ROCM 801" >> KokkosCore_config.tmp )
tmp := $(shell echo "\#define KOKKOS_ARCH_CARRIZO 1" >> KokkosCore_config.tmp )
KOKKOS_INTERNAL_ROCM_ARCH_FLAG := --amdgpu-target=gfx801
endif
ifeq ($(KOKKOS_INTERNAL_USE_ARCH_FIJI), 1)
tmp := $(shell echo "\#define KOKKOS_ARCH_ROCM 803" >> KokkosCore_config.tmp )
tmp := $(shell echo "\#define KOKKOS_ARCH_FIJI 1" >> KokkosCore_config.tmp )
KOKKOS_INTERNAL_ROCM_ARCH_FLAG := --amdgpu-target=gfx803
endif
ifeq ($(KOKKOS_INTERNAL_USE_ARCH_VEGA), 1)
tmp := $(shell echo "\#define KOKKOS_ARCH_ROCM 900" >> KokkosCore_config.tmp )
tmp := $(shell echo "\#define KOKKOS_ARCH_VEGA 1" >> KokkosCore_config.tmp )
KOKKOS_INTERNAL_ROCM_ARCH_FLAG := --amdgpu-target=gfx900
endif
ifeq ($(KOKKOS_INTERNAL_USE_ARCH_GFX901), 1)
tmp := $(shell echo "\#define KOKKOS_ARCH_ROCM 901" >> KokkosCore_config.tmp )
tmp := $(shell echo "\#define KOKKOS_ARCH_GFX901 1" >> KokkosCore_config.tmp )
KOKKOS_INTERNAL_ROCM_ARCH_FLAG := --amdgpu-target=gfx901
endif
KOKKOS_INTERNAL_HCC_PATH := $(shell which $(CXX))
ROCM_HCC_PATH ?= $(KOKKOS_INTERNAL_HCC_PATH:/bin/clang++=)
KOKKOS_CXXFLAGS += $(shell $(ROCM_HCC_PATH)/bin/hcc-config --cxxflags)
KOKKOS_LDFLAGS += $(shell $(ROCM_HCC_PATH)/bin/hcc-config --ldflags) -lhc_am -lm
KOKKOS_LDFLAGS += $(KOKKOS_INTERNAL_ROCM_ARCH_FLAG)
KOKKOS_SRC += $(wildcard $(KOKKOS_PATH)/core/src/ROCm/*.cpp)
KOKKOS_HEADERS += $(wildcard $(KOKKOS_PATH)/core/src/ROCm/*.hpp)
endif
KOKKOS_INTERNAL_LS_CONFIG := $(shell ls KokkosCore_config.h 2>&1)
ifeq ($(KOKKOS_INTERNAL_LS_CONFIG), KokkosCore_config.h)
KOKKOS_INTERNAL_NEW_CONFIG := $(strip $(shell diff KokkosCore_config.h KokkosCore_config.tmp | grep define | wc -l))
else

View File

@ -42,6 +42,17 @@ Kokkos_Cuda_Locks.o: $(KOKKOS_CPP_DEPENDS) $(KOKKOS_PATH)/core/src/Cuda/Kokkos_C
$(CXX) $(KOKKOS_CPPFLAGS) $(KOKKOS_CXXFLAGS) $(CXXFLAGS) -c $(KOKKOS_PATH)/core/src/Cuda/Kokkos_Cuda_Locks.cpp
endif
ifeq ($(KOKKOS_INTERNAL_USE_ROCM), 1)
Kokkos_ROCm_Exec.o: $(KOKKOS_CPP_DEPENDS) $(KOKKOS_PATH)/core/src/ROCm/Kokkos_ROCm_Exec.cpp
$(CXX) $(KOKKOS_CPPFLAGS) $(KOKKOS_CXXFLAGS) $(CXXFLAGS) -c $(KOKKOS_PATH)/core/src/ROCm/Kokkos_ROCm_Exec.cpp
Kokkos_ROCm_Space.o: $(KOKKOS_CPP_DEPENDS) $(KOKKOS_PATH)/core/src/ROCm/Kokkos_ROCm_Space.cpp
$(CXX) $(KOKKOS_CPPFLAGS) $(KOKKOS_CXXFLAGS) $(CXXFLAGS) -c $(KOKKOS_PATH)/core/src/ROCm/Kokkos_ROCm_Space.cpp
Kokkos_ROCm_Task.o: $(KOKKOS_CPP_DEPENDS) $(KOKKOS_PATH)/core/src/ROCm/Kokkos_ROCm_Task.cpp
$(CXX) $(KOKKOS_CPPFLAGS) $(KOKKOS_CXXFLAGS) $(CXXFLAGS) -c $(KOKKOS_PATH)/core/src/ROCm/Kokkos_ROCm_Task.cpp
Kokkos_ROCm_Impl.o: $(KOKKOS_CPP_DEPENDS) $(KOKKOS_PATH)/core/src/ROCm/Kokkos_ROCm_Impl.cpp
$(CXX) $(KOKKOS_CPPFLAGS) $(KOKKOS_CXXFLAGS) $(CXXFLAGS) -c $(KOKKOS_PATH)/core/src/ROCm/Kokkos_ROCm_Impl.cpp
endif
ifeq ($(KOKKOS_INTERNAL_USE_PTHREADS), 1)
Kokkos_ThreadsExec_base.o: $(KOKKOS_CPP_DEPENDS) $(KOKKOS_PATH)/core/src/Threads/Kokkos_ThreadsExec_base.cpp
$(CXX) $(KOKKOS_CPPFLAGS) $(KOKKOS_CXXFLAGS) $(CXXFLAGS) -c $(KOKKOS_PATH)/core/src/Threads/Kokkos_ThreadsExec_base.cpp

View File

@ -80,6 +80,9 @@ Other compilers working:
X86:
Cygwin 2.1.0 64bit with gcc 4.9.3
Limited testing of the following compilers on POWER7+ systems:
GCC 4.8.5 (on RHEL7.1 POWER7+)
Known non-working combinations:
Power8:
Pthreads backend
@ -171,3 +174,22 @@ Contributions to Kokkos are welcome. In order to do so, please open an issue
where a feature request or bug can be discussed. Then issue a pull request
with your contribution. Pull requests must be issued against the develop branch.
===========================================================================
====Citing Kokkos==========================================================
===========================================================================
If you publish work which mentions Kokkos, please cite the following paper:
@article{CarterEdwards20143202,
title = "Kokkos: Enabling manycore performance portability through polymorphic memory access patterns ",
journal = "Journal of Parallel and Distributed Computing ",
volume = "74",
number = "12",
pages = "3202 - 3216",
year = "2014",
note = "Domain-Specific Languages and High-Level Frameworks for High-Performance Computing ",
issn = "0743-7315",
doi = "https://doi.org/10.1016/j.jpdc.2014.07.003",
url = "http://www.sciencedirect.com/science/article/pii/S0743731514001257",
author = "H. Carter Edwards and Christian R. Trott and Daniel Sunderland"
}

View File

@ -0,0 +1,140 @@
Summary:
- Step 1: Testing Kokkos itself using test_all_sandia
- Step 2: Testing of Kokkos integrated into Trilinos (config/trilinos-integration/*.sh)
- Step 3: Locally update CHANGELOG, merge into master, edit config/master_history.txt
- Step 4: Locally snapshot new master into corresponding Trilinos branch (develop or temporary), push with checking-test-sems.sh
- Step 5: Push local Kokkos master to GitHub (need Owner approval)
Steps 1, 2, and 4 include testing that may fail. These failures must be fixed either by pull requests to Kokkos develop, or by creating a new Trilinos branch for parts of Trilinos that must be updated. This is what usually takes the most time.
// -------------------------------------------------------------------------------- //
Step 1: The following should be repeated on enough machines to cover all
supported compilers. Those machines are:
kokkos-dev
??? <- TODO: identify other machines
1.1. Clone kokkos develop branch (or just switch to it)
git clone -b develop git@github.com:kokkos/kokkos.git
cd kokkos
1.2. Create a testing directory
mkdir testing
cd testing
1.3. Run the test_all_sandia script with no options to test all compilers
nohup ../config/test_all_sandia &
tail -f nohup.out # to watch progress
// -------------------------------------------------------------------------------- //
Step 2:
2.1. Build and test Trilinos with 4 different configurations; Run scripts for white and shepard that are provided in kokkos/config/trilinos-integration. These scripts load their own modules/environment, so don't require preparation. You can run all four at the same time, use separate directories for each.
mkdir serial
cd serial
nohup KOKKOS_PATH/config/trilinos-integration/shepard_jenkins_run_script_serial_intel &
2.2. Compare the compile errors and test failures between updated and pristine versions. There may be compile failures that happen in both, tests that fail in both, and there may be tests that only fail some times (thus, rerun tests manually as needed).
// -------------------------------------------------------------------------------- //
Step 3: This step should be run on kokkos-dev
3.1. If you don't have a GitHub token already, generate one for yourself (this will give you TOKEN):
https://github.com/settings/tokens
3.2. Get a clean copy of the Kokkos develop branch
git clone -b develop git@github.com:kokkos/kokkos.git
cd kokkos
3.3. Generate the initial changelog. Use the most recent tag as OLDTAG (`git tag -l` can show you all tags). The NEWTAG is the new version number, e.g. "2.04.00". RUN THIS OUTSIDE THE KOKKOS SOURCE TREE!
module load ruby/2.3.1/gcc/5.3.0
gitthub_changelog_generator kokkos/kokkos --token TOKEN --no-pull-requests --include-labels 'InDevelop' --enhancement-labels 'enhancement,Feature Request' --future-release 'NEWTAG' --between-tags 'NEWTAG,OLDTAG'
cat CHANGELOG.md
3.4. Manually cleanup and commit the change log. Pushing to develop requires Owner permission.
(Copy the new section from the generated CHANGELOG.md to KOKKOS_PATH/CHANGELOG.md)
(Make desired changes to CHANGELOG.md to enhance clarity (remove issues not noteworthy))
(Commit and push the CHANGELOG.md to develop)
3.5. Merge develop into master. DO NOT FAST-FORWARD THE MERGE!!!!
(From kokkos directory):
git checkout master
git merge --no-ff origin/develop
3.6. Update the tag in kokkos/config/master_history.txt
Tag description: MajorNumber.MinorNumber.WeeksSinceMinorNumberUpdate
Tag field widths: #.#.##
date description: month:day:year
date field widths: ##:##:####
master description: SHA1 of previous master commit (use `git log`?)
develop description: SHA1 of merged develop branch
SHA1 field width: ######## (8 chars)
# Append to config/master_history.txt:
tag: 2.03.13 date: 07:27:2017 master: da314444 develop: 29ccb58a
git commit --amend -a
3.7. Create the new tag:
git tag -a #.#.##
(type the following into the tag message (same as for step 4.3))
tag: #.#.##
date: mm/dd/yyyy
master: sha1
develop: sha1
3.8. DO NOT PUSH YET !!!
// -------------------------------------------------------------------------------- //
Step 4: This step can be done on any SEMS machine (e.g. kokkos-dev). Actually, the checkin step requires lots of disk space and RAM. Use ceerws1113 if you have access to it.
4.1 Clone the Trilinos corresponding branch (or just switch to it)
git clone -b develop git@github.com:trilinos/Trilinos.git
TRILINOS_PATH=$PWD/Trilinos
4.2 Snapshot Kokkos into Trilinos - this requires python/2.7.9 and that both Trilinos and Kokkos be clean - no untracked or modified files. Run the following outside of the Kokkos and Trilinos source trees.
module load sems-python/2.7.9
python KOKKOS_PATH/config/snapshot.py KOKKOS_PATH TRILINOS_PATH/packages
4.3. Run checkin-test to push to trilinos using the CI build modules (gcc/4.9.3)
cd TRILINOS_PATH
mkdir CHECKIN
cd CHECKIN
nohup ../cmake/std/sems/checkin-test-sems.sh --do-all --push &
4.4. If there are failures, fix and backtrack. Otherwise, go to next step
// -------------------------------------------------------------------------------- //
Step 5: Push Kokkos master to GitHub (requires Owner permission).
cd KOKKOS_PATH
git push --follow-tags origin master

View File

@ -8,3 +8,4 @@ tag: 2.02.15 date: 02:10:2017 master: 8c64cd93 develop: 28dea8b6
tag: 2.03.00 date: 04:25:2017 master: 120d9ce7 develop: 015ba641
tag: 2.03.05 date: 05:27:2017 master: 36b92f43 develop: 79073186
tag: 2.03.13 date: 07:27:2017 master: da314444 develop: 29ccb58a
tag: 2.04.00 date: 08:16:2017 master: 54eb75c0 develop: 32fb8ee1

View File

@ -167,7 +167,6 @@ if [ "$MACHINE" = "sems" ]; then
"intel/15.0.2 $BASE_MODULE_LIST $INTEL_BUILD_LIST icpc $INTEL_WARNING_FLAGS"
"intel/16.0.1 $BASE_MODULE_LIST $INTEL_BUILD_LIST icpc $INTEL_WARNING_FLAGS"
"intel/16.0.3 $BASE_MODULE_LIST $INTEL_BUILD_LIST icpc $INTEL_WARNING_FLAGS"
"intel/17.0.1 $BASE_MODULE_LIST $INTEL_BUILD_LIST icpc $INTEL_WARNING_FLAGS"
"clang/3.6.1 $BASE_MODULE_LIST $CLANG_BUILD_LIST clang++ $CLANG_WARNING_FLAGS"
"clang/3.7.1 $BASE_MODULE_LIST $CLANG_BUILD_LIST clang++ $CLANG_WARNING_FLAGS"
"clang/3.8.1 $BASE_MODULE_LIST $CLANG_BUILD_LIST clang++ $CLANG_WARNING_FLAGS"

View File

@ -1,15 +1,15 @@
#if !defined(KOKKOS_MACROS_HPP) || defined(KOKKOS_CORE_CONFIG_H)
#error "Don't include KokkosCore_config.h directly; include Kokkos_Macros.hpp instead."
#else
#define KOKKOS_CORE_CONFIG_H
#endif
/* The trivial 'src/build_common.sh' creates a config
* that must stay in sync with this file.
*/
#cmakedefine KOKKOS_FOR_SIERRA
#ifndef KOKKOS_FOR_SIERRA
#if !defined(KOKKOS_FOR_SIERRA)
#if !defined(KOKKOS_MACROS_HPP) || defined(KOKKOS_CORE_CONFIG_H)
#error "Don't include KokkosCore_config.h directly; include Kokkos_Macros.hpp instead."
#else
#define KOKKOS_CORE_CONFIG_H
#endif
#cmakedefine KOKKOS_HAVE_CUDA
#cmakedefine KOKKOS_HAVE_OPENMP
@ -93,12 +93,6 @@
#cmakedefine KOKKOS_ARCH_PASCAL60 1
#cmakedefine KOKKOS_ARCH_PASCAL61 1
// Don't forbid users from defining this macro on the command line,
// but still make sure that CMake logic can control its definition.
#ifndef KOKKOS_HAVE_CXX11_DISPATCH_LAMBDA
#cmakedefine KOKKOS_HAVE_CXX11_DISPATCH_LAMBDA 1
#endif
// TODO: These are currently not used in Kokkos. Should they be removed?
#cmakedefine KOKKOS_HAVE_MPI
#cmakedefine KOKKOS_HAVE_CUSPARSE
@ -107,4 +101,4 @@
#cmakedefine KOKKOS_USING_DEPRECATED_VIEW
#cmakedefine KOKKOS_HAVE_CXX11
#endif // KOKKOS_FOR_SIERRA
#endif // !defined(KOKKOS_FOR_SIERRA)

View File

@ -9,30 +9,6 @@ TRIBITS_ADD_OPTION_AND_DEFINE(
ASSERT_DEFINED(${PROJECT_NAME}_ENABLE_CXX11)
ASSERT_DEFINED(${PACKAGE_NAME}_ENABLE_CUDA)
# Kokkos_ENABLE_CXX11_DISPATCH_LAMBDA governs whether Kokkos allows
# use of lambdas at the outer level of parallel dispatch (that is, as
# the argument to an outer parallel_for, parallel_reduce, or
# parallel_scan). This works with non-CUDA execution spaces if C++11
# is enabled. It does not currently work with public releases of
# CUDA. If that changes, please change the default here to ON if CUDA
# and C++11 are ON.
IF (${PROJECT_NAME}_ENABLE_CXX11)
IF (${PACKAGE_NAME}_ENABLE_CUDA)
SET(Kokkos_ENABLE_CXX11_DISPATCH_LAMBDA_DEFAULT OFF)
ELSE ()
SET(Kokkos_ENABLE_CXX11_DISPATCH_LAMBDA_DEFAULT ON)
ENDIF ()
ELSE ()
SET(Kokkos_ENABLE_CXX11_DISPATCH_LAMBDA_DEFAULT OFF)
ENDIF ()
TRIBITS_ADD_OPTION_AND_DEFINE(
Kokkos_ENABLE_CXX11_DISPATCH_LAMBDA
KOKKOS_HAVE_CXX11_DISPATCH_LAMBDA
"Whether Kokkos allows use of lambdas at the outer level of parallel dispatch (that is, as the argument to an outer parallel_for, parallel_reduce, or parallel_scan). This requires C++11. It also does not currently work with public releases of CUDA. As a result, even if C++11 is enabled, this will be OFF by default if CUDA is enabled. If this option is ON, the macro KOKKOS_HAVE_CXX11_DISPATCH_LAMBDA will be defined. For compatibility with Kokkos' Makefile build system, it is also possible to define that macro on the command line."
${Kokkos_ENABLE_CXX11_DISPATCH_LAMBDA_DEFAULT}
)
TRIBITS_CONFIGURE_FILE(${PACKAGE_NAME}_config.h)
INCLUDE_DIRECTORIES(${CMAKE_CURRENT_BINARY_DIR})

View File

@ -152,10 +152,10 @@ public:
KOKKOS_INLINE_FUNCTION pointer data() { return pointer(0) ; }
KOKKOS_INLINE_FUNCTION const_pointer data() const { return const_pointer(0); }
~Array() = default ;
Array() = default ;
Array( const Array & ) = default ;
Array & operator = ( const Array & ) = default ;
KOKKOS_FUNCTION_DEFAULTED ~Array() = default ;
KOKKOS_FUNCTION_DEFAULTED Array() = default ;
KOKKOS_FUNCTION_DEFAULTED Array( const Array & ) = default ;
KOKKOS_FUNCTION_DEFAULTED Array & operator = ( const Array & ) = default ;
// Some supported compilers are not sufficiently C++11 compliant
// for default move constructor and move assignment operator.
@ -209,7 +209,7 @@ public:
KOKKOS_INLINE_FUNCTION pointer data() { return m_elem ; }
KOKKOS_INLINE_FUNCTION const_pointer data() const { return m_elem ; }
~Array() = default ;
KOKKOS_FUNCTION_DEFAULTED ~Array() = default ;
Array() = delete ;
Array( const Array & rhs ) = delete ;
@ -278,7 +278,7 @@ public:
KOKKOS_INLINE_FUNCTION pointer data() { return m_elem ; }
KOKKOS_INLINE_FUNCTION const_pointer data() const { return m_elem ; }
~Array() = default ;
KOKKOS_FUNCTION_DEFAULTED ~Array() = default ;
Array() = delete ;
Array( const Array & ) = delete ;

View File

@ -80,6 +80,11 @@
// Compiling NVIDIA device code, must use Cuda atomics:
#define KOKKOS_ENABLE_CUDA_ATOMICS
#elif defined(KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_ROCM_GPU)
#define KOKKOS_ENABLE_ROCM_ATOMICS
#endif
#if ! defined( KOKKOS_ENABLE_GNU_ATOMICS ) && \
@ -154,6 +159,19 @@ const char * atomic_query_version()
} // namespace Kokkos
#if defined( KOKKOS_ENABLE_ROCM )
#include <ROCm/Kokkos_ROCm_Atomic.hpp>
namespace Kokkos {
namespace Impl {
extern KOKKOS_INLINE_FUNCTION
bool lock_address_rocm_space(void* ptr);
extern KOKKOS_INLINE_FUNCTION
void unlock_address_rocm_space(void* ptr);
}
}
#endif
#ifdef _WIN32
#include "impl/Kokkos_Atomic_Windows.hpp"
#else

View File

@ -107,6 +107,11 @@ public:
re_ (val), im_ (0.0)
{}
// BUG HCC WORKAROUND
KOKKOS_INLINE_FUNCTION complex( const RealType& re, const RealType& im):
re_ (re), im_ (im)
{}
//! Constructor that takes the real and imaginary parts.
template<class RealType1, class RealType2>
KOKKOS_INLINE_FUNCTION complex (const RealType1& re, const RealType2& im) :
@ -227,6 +232,16 @@ public:
return re_;
}
//! Set the imaginary part of this complex number.
KOKKOS_INLINE_FUNCTION void imag (RealType v) {
im_ = v;
}
//! Set the real part of this complex number.
KOKKOS_INLINE_FUNCTION void real (RealType v) {
re_ = v;
}
KOKKOS_INLINE_FUNCTION
complex<RealType>& operator += (const complex<RealType>& src) {
re_ += src.re_;
@ -299,7 +314,7 @@ public:
// Scale (by the "1-norm" of y) to avoid unwarranted overflow.
// If the real part is +/-Inf and the imaginary part is -/+Inf,
// this won't change the result.
const RealType s = ::fabs (y.real ()) + ::fabs (y.imag ());
const RealType s = std::fabs (y.real ()) + std::fabs (y.imag ());
// If s is 0, then y is zero, so x/y == real(x)/0 + i*imag(x)/0.
// In that case, the relation x/y == (x/s) / (y/s) doesn't hold,
@ -537,7 +552,7 @@ operator / (const complex<RealType>& x, const complex<RealType>& y) {
// Scale (by the "1-norm" of y) to avoid unwarranted overflow.
// If the real part is +/-Inf and the imaginary part is -/+Inf,
// this won't change the result.
const RealType s = ::fabs (real (y)) + ::fabs (imag (y));
const RealType s = std::fabs (real (y)) + std::fabs (imag (y));
// If s is 0, then y is zero, so x/y == real(x)/0 + i*imag(x)/0.
// In that case, the relation x/y == (x/s) / (y/s) doesn't hold,

View File

@ -74,6 +74,10 @@
#include <Kokkos_Cuda.hpp>
#endif
#if defined( KOKKOS_ENABLE_ROCM )
#include <Kokkos_ROCm.hpp>
#endif
#include <Kokkos_Pair.hpp>
#include <Kokkos_MemoryPool.hpp>
#include <Kokkos_Array.hpp>

View File

@ -122,6 +122,13 @@ class CudaHostPinnedSpace; ///< Memory space on Host accessible to Cuda GPU
class Cuda; ///< Execution space for Cuda GPU
#endif
#if defined( KOKKOS_ENABLE_ROCM )
namespace Experimental {
class ROCmSpace ; ///< Memory space on ROCm GPU
class ROCm ; ///< Execution space for ROCm GPU
}
#endif
template<class ExecutionSpace, class MemorySpace>
struct Device;
@ -140,6 +147,8 @@ namespace Kokkos {
typedef Cuda DefaultExecutionSpace;
#elif defined ( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_OPENMPTARGET )
typedef Experimental::OpenMPTarget DefaultExecutionSpace ;
#elif defined ( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_ROCM )
typedef Experimental::ROCm DefaultExecutionSpace ;
#elif defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_OPENMP )
typedef OpenMP DefaultExecutionSpace;
#elif defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_THREADS )
@ -185,6 +194,8 @@ namespace Impl {
#if defined( KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_CUDA ) && defined( KOKKOS_ENABLE_CUDA )
typedef Kokkos::CudaSpace ActiveExecutionMemorySpace;
#elif defined( KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_ROCM_GPU )
typedef Kokkos::HostSpace ActiveExecutionMemorySpace ;
#elif defined( KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_HOST )
typedef Kokkos::HostSpace ActiveExecutionMemorySpace;
#else

View File

@ -98,18 +98,18 @@ public:
typedef View<size_type* , array_layout, device_type> row_map_type;
typedef View<DataType* , array_layout, device_type> entries_type;
entries_type entries;
row_map_type row_map;
entries_type entries;
//! Construct an empty view.
Crs () : entries(), row_map() {}
Crs() : row_map(), entries() {}
//! Copy constructor (shallow copy).
Crs (const Crs& rhs) : entries (rhs.entries), row_map (rhs.row_map)
Crs(const Crs& rhs) : row_map(rhs.row_map), entries(rhs.entries)
{}
template<class EntriesType, class RowMapType>
Crs (const EntriesType& entries_,const RowMapType& row_map_) : entries (entries_), row_map (row_map_)
Crs(const RowMapType& row_map_, const EntriesType& entries_) : row_map(row_map_), entries(entries_)
{}
/** \brief Assign to a view of the rhs array.
@ -117,8 +117,8 @@ public:
* then allocated memory is deallocated.
*/
Crs& operator= (const Crs& rhs) {
entries = rhs.entries;
row_map = rhs.row_map;
entries = rhs.entries;
return *this;
}
@ -151,7 +151,7 @@ void get_crs_transpose_counts(
template< class OutCounts,
class InCrs>
void get_crs_row_map_from_counts(
typename OutCounts::value_type get_crs_row_map_from_counts(
OutCounts& out,
InCrs const& in,
std::string const& name = "row_map");
@ -204,18 +204,20 @@ class CrsRowMapFromCounts {
using execution_space = typename InCounts::execution_space;
using value_type = typename OutRowMap::value_type;
using index_type = typename InCounts::size_type;
using last_value_type = Kokkos::View<value_type, execution_space>;
private:
InCounts in;
OutRowMap out;
InCounts m_in;
OutRowMap m_out;
last_value_type m_last_value;
public:
KOKKOS_INLINE_FUNCTION
void operator()(index_type i, value_type& update, bool final_pass) const {
update += in(i);
if (final_pass) {
out(i + 1) = update;
if (i == 0) {
out(0) = 0;
}
if (i < m_in.size()) {
update += m_in(i);
if (final_pass) m_out(i + 1) = update;
} else if (final_pass) {
m_out(0) = 0;
m_last_value() = update;
}
}
KOKKOS_INLINE_FUNCTION
@ -226,12 +228,16 @@ class CrsRowMapFromCounts {
}
using self_type = CrsRowMapFromCounts<InCounts, OutRowMap>;
CrsRowMapFromCounts(InCounts const& arg_in, OutRowMap const& arg_out):
in(arg_in),out(arg_out) {
m_in(arg_in), m_out(arg_out), m_last_value("last_value") {
}
value_type execute() {
using policy_type = RangePolicy<index_type, execution_space>;
using closure_type = Kokkos::Impl::ParallelScan<self_type, policy_type>;
closure_type closure(*this, policy_type(0, in.size()));
closure_type closure(*this, policy_type(0, m_in.size() + 1));
closure.execute();
execution_space::fence();
auto last_value = Kokkos::create_mirror_view(m_last_value);
Kokkos::deep_copy(last_value, m_last_value);
return last_value();
}
};
@ -297,13 +303,14 @@ void get_crs_transpose_counts(
template< class OutRowMap,
class InCounts>
void get_crs_row_map_from_counts(
typename OutRowMap::value_type get_crs_row_map_from_counts(
OutRowMap& out,
InCounts const& in,
std::string const& name) {
out = OutRowMap(ViewAllocateWithoutInitializing(name), in.size() + 1);
Kokkos::Impl::Experimental::
CrsRowMapFromCounts<InCounts, OutRowMap> functor(in, out);
return functor.execute();
}
template< class DataType,
@ -328,6 +335,65 @@ void transpose_crs(
FillCrsTransposeEntries<crs_type, crs_type> entries_functor(in, out);
}
template< class CrsType,
class Functor>
struct CountAndFill {
using data_type = typename CrsType::size_type;
using size_type = typename CrsType::size_type;
using row_map_type = typename CrsType::row_map_type;
using entries_type = typename CrsType::entries_type;
using counts_type = row_map_type;
CrsType m_crs;
Functor m_functor;
counts_type m_counts;
struct Count {};
KOKKOS_INLINE_FUNCTION void operator()(Count, size_type i) const {
m_counts(i) = m_functor(i, nullptr);
}
struct Fill {};
KOKKOS_INLINE_FUNCTION void operator()(Fill, size_type i) const {
auto j = m_crs.row_map(i);
data_type* fill = &(m_crs.entries(j));
m_functor(i, fill);
}
using self_type = CountAndFill<CrsType, Functor>;
CountAndFill(CrsType& crs, size_type nrows, Functor const& f):
m_crs(crs),
m_functor(f)
{
using execution_space = typename CrsType::execution_space;
m_counts = counts_type("counts", nrows);
{
using count_policy_type = RangePolicy<size_type, execution_space, Count>;
using count_closure_type =
Kokkos::Impl::ParallelFor<self_type, count_policy_type>;
const count_closure_type closure(*this, count_policy_type(0, nrows));
closure.execute();
}
auto nentries = Kokkos::Experimental::
get_crs_row_map_from_counts(m_crs.row_map, m_counts);
m_counts = counts_type();
m_crs.entries = entries_type("entries", nentries);
{
using fill_policy_type = RangePolicy<size_type, execution_space, Fill>;
using fill_closure_type =
Kokkos::Impl::ParallelFor<self_type, fill_policy_type>;
const fill_closure_type closure(*this, fill_policy_type(0, nrows));
closure.execute();
}
crs = m_crs;
}
};
template< class CrsType,
class Functor>
void count_and_fill_crs(
CrsType& crs,
typename CrsType::size_type nrows,
Functor const& f) {
Kokkos::Experimental::CountAndFill<CrsType, Functor>(crs, nrows, f);
}
}} // namespace Kokkos::Experimental
#endif /* #define KOKKOS_CRS_HPP */

View File

@ -96,6 +96,14 @@
//----------------------------------------------------------------------------
#if defined(KOKKOS_ENABLE_SERIAL) || defined(KOKKOS_ENABLE_THREADS) || \
defined(KOKKOS_ENABLE_OPENMP) || defined(KOKKOS_ENABLE_QTHREADS) || \
defined(KOKKOS_ENABLE_ROCM) || defined(KOKKOS_ENABLE_OPENMPTARGET)
#define KOKKOS_INTERNAL_ENABLE_NON_CUDA_BACKEND
#endif
#define KOKKOS_ENABLE_CXX11_DISPATCH_LAMBDA
#if defined( KOKKOS_ENABLE_CUDA ) && defined( __CUDACC__ )
// Compiling with a CUDA compiler.
//
@ -133,6 +141,9 @@
#if ( CUDA_VERSION < 8000 ) && defined( __NVCC__ )
#define KOKKOS_LAMBDA [=]__device__
#if defined( KOKKOS_INTERNAL_ENABLE_NON_CUDA_BACKEND )
#undef KOKKOS_ENABLE_CXX11_DISPATCH_LAMBDA
#endif
#else
#define KOKKOS_LAMBDA [=]__host__ __device__
@ -141,16 +152,13 @@
#endif
#endif
#define KOKKOS_ENABLE_CXX11_DISPATCH_LAMBDA 1
#endif
#endif // #if defined( KOKKOS_ENABLE_CUDA ) && defined( __CUDACC__ )
#if defined( KOKKOS_ENABLE_CXX11_DISPATCH_LAMBDA )
// Cuda version 8.0 still needs the functor wrapper
#if /* ( CUDA_VERSION < 8000 ) && */ defined( __NVCC__ )
#if defined( __NVCC__ )
#define KOKKOS_IMPL_NEED_FUNCTOR_WRAPPER
#endif
#endif
#endif
#else // !defined(KOKKOS_ENABLE_CUDA_LAMBDA)
#undef KOKKOS_ENABLE_CXX11_DISPATCH_LAMBDA
#endif // !defined(KOKKOS_ENABLE_CUDA_LAMBDA)
#endif // #if defined( KOKKOS_ENABLE_CUDA ) && defined( __CUDACC__ )
//----------------------------------------------------------------------------
// Language info: C++, CUDA, OPENMP
@ -161,8 +169,20 @@
#define KOKKOS_FORCEINLINE_FUNCTION __device__ __host__ __forceinline__
#define KOKKOS_INLINE_FUNCTION __device__ __host__ inline
#define KOKKOS_FUNCTION __device__ __host__
#ifdef KOKKOS_COMPILER_CLANG
#define KOKKOS_FUNCTION_DEFAULTED KOKKOS_FUNCTION
#endif
#endif // #if defined( __CUDA_ARCH__ )
#if defined( KOKKOS_ENABLE_ROCM ) && defined( __HCC__ )
#define KOKKOS_FORCEINLINE_FUNCTION __attribute__((amp,cpu)) inline
#define KOKKOS_INLINE_FUNCTION __attribute__((amp,cpu)) inline
#define KOKKOS_FUNCTION __attribute__((amp,cpu))
#define KOKKOS_LAMBDA [=] __attribute__((amp,cpu))
#define KOKKOS_FUNCTION_DEFAULTED KOKKOS_FUNCTION
#endif
#if defined( _OPENMP )
// Compiling with OpenMP.
// The value of _OPENMP is an integer value YYYYMM
@ -179,15 +199,6 @@
// Host code is compiled again with another compiler.
// Device code is compile to 'ptx'.
#define KOKKOS_COMPILER_NVCC __NVCC__
#else
#if !defined( KOKKOS_ENABLE_CXX11_DISPATCH_LAMBDA )
#if !defined( KOKKOS_ENABLE_CUDA ) // Compiling with clang for Cuda does not work with LAMBDAs either
// CUDA (including version 6.5) does not support giving lambdas as
// arguments to global functions. Thus its not currently possible
// to dispatch lambdas from the host.
#define KOKKOS_ENABLE_CXX11_DISPATCH_LAMBDA 1
#endif
#endif
#endif // #if defined( __NVCC__ )
#if !defined( KOKKOS_LAMBDA )
@ -321,6 +332,10 @@
//#define KOKKOS_ENABLE_PRAGMA_LOOPCOUNT 1
//#define KOKKOS_ENABLE_PRAGMA_VECTOR 1
//#define KOKKOS_ENABLE_PRAGMA_SIMD 1
#if ! defined( KOKKOS_ENABLE_ASM )
#define KOKKOS_ENABLE_ASM 1
#endif
#endif
//----------------------------------------------------------------------------
@ -397,6 +412,10 @@
#define KOKKOS_FUNCTION /**/
#endif
#if !defined( KOKKOS_FUNCTION_DEFAULTED )
#define KOKKOS_FUNCTION_DEFAULTED /**/
#endif
//----------------------------------------------------------------------------
// Define empty macro for restrict if necessary:
@ -424,6 +443,7 @@
// There is zero or one default execution space specified.
#if 1 < ( ( defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_CUDA ) ? 1 : 0 ) + \
( defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_ROCM ) ? 1 : 0 ) + \
( defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_OPENMPTARGET ) ? 1 : 0 ) + \
( defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_OPENMP ) ? 1 : 0 ) + \
( defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_THREADS ) ? 1 : 0 ) + \
@ -435,6 +455,7 @@
// If default is not specified then chose from enabled execution spaces.
// Priority: CUDA, OPENMP, THREADS, QTHREADS, SERIAL
#if defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_CUDA )
#elif defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_ROCM )
#elif defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_OPENMPTARGET )
#elif defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_OPENMP )
#elif defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_THREADS )
@ -442,6 +463,8 @@
#elif defined( KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_SERIAL )
#elif defined( KOKKOS_ENABLE_CUDA )
#define KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_CUDA
#elif defined( KOKKOS_ENABLE_ROCM )
#define KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_ROCM
#elif defined( KOKKOS_ENABLE_OPENMPTARGET )
#define KOKKOS_ENABLE_DEFAULT_DEVICE_TYPE_OPENMPTARGET
#elif defined( KOKKOS_ENABLE_OPENMP )
@ -459,6 +482,8 @@
#if defined( __CUDACC__ ) && defined( __CUDA_ARCH__ ) && defined( KOKKOS_ENABLE_CUDA )
#define KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_CUDA
#elif defined( __HCC__ ) && defined( __HCC_ACCELERATOR__ ) && defined( KOKKOS_ENABLE_ROCM )
#define KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_ROCM_GPU
#else
#define KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_HOST
#endif

View File

@ -233,12 +233,24 @@ public:
//--------------------------------------------------------------------------
MemoryPool() = default ;
MemoryPool( MemoryPool && ) = default ;
MemoryPool( const MemoryPool & ) = default ;
MemoryPool & operator = ( MemoryPool && ) = default ;
MemoryPool & operator = ( const MemoryPool & ) = default ;
MemoryPool()
: m_tracker()
, m_sb_state_array(0)
, m_sb_state_size(0)
, m_sb_size_lg2(0)
, m_max_block_size_lg2(0)
, m_min_block_size_lg2(0)
, m_sb_count(0)
, m_hint_offset(0)
, m_data_offset(0)
, m_unused_padding(0)
{}
/**\brief Allocate a memory pool from 'memspace'.
*
* The memory pool will have at least 'min_total_alloc_size' bytes

View File

@ -1016,7 +1016,7 @@ parallel_reduce( std::string const & arg_label
//------------------------------
#if (KOKKOS_ENABLE_PROFILING)
#if defined(KOKKOS_ENABLE_PROFILING)
uint64_t kpID = 0;
if(Kokkos::Profiling::profileLibraryLoaded()) {
Kokkos::Profiling::beginParallelReduce(arg_label, 0, &kpID);
@ -1042,7 +1042,7 @@ parallel_reduce( std::string const & arg_label
//------------------------------
#if (KOKKOS_ENABLE_PROFILING)
#if defined(KOKKOS_ENABLE_PROFILING)
if(Kokkos::Profiling::profileLibraryLoaded()) {
Kokkos::Profiling::endParallelReduce(kpID);
}

View File

@ -0,0 +1,220 @@
/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#ifndef KOKKOS_ROCM_HPP
#define KOKKOS_ROCM_HPP
#include <Kokkos_Core_fwd.hpp>
#if defined( KOKKOS_ENABLE_ROCM )
#include <ROCm/hc_math_std.hpp>
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
#include <cstddef>
#include <iosfwd>
#include <Kokkos_HostSpace.hpp>
#include <Kokkos_ROCmSpace.hpp>
#include <ROCm/Kokkos_ROCm_Exec.hpp>
#include <Kokkos_ScratchSpace.hpp>
#include <Kokkos_Parallel.hpp>
#include <Kokkos_Layout.hpp>
#include <impl/Kokkos_Tags.hpp>
/*--------------------------------------------------------------------------*/
#include <hc.hpp>
#include <hc_am.hpp>
#include <amp_math.h>
#if defined( __HCC_ACCELERATOR__ )
using namespace ::Concurrency::precise_math ;
#endif
/*--------------------------------------------------------------------------*/
namespace Kokkos {
namespace Impl {
class ROCmExec ;
} // namespace Impl
} // namespace Kokkos
/*--------------------------------------------------------------------------*/
namespace Kokkos {
namespace Experimental {
/// \class ROCm
/// \brief Kokkos device for multicore processors in the host memory space.
class ROCm {
public:
//------------------------------------
//! \name Type declarations that all Kokkos devices must provide.
//@{
//! Tag this class as a kokkos execution space
typedef ROCm execution_space ;
typedef ROCmSpace memory_space ;
typedef Kokkos::Device<execution_space,memory_space> device_type;
typedef LayoutLeft array_layout ;
typedef HostSpace::size_type size_type ;
typedef ScratchMemorySpace< ROCm > scratch_memory_space ;
~ROCm() {}
ROCm();
// explicit ROCm( const int instance_id );
ROCm( ROCm && ) = default ;
ROCm( const ROCm & ) = default ;
ROCm & operator = ( ROCm && ) = default ;
ROCm & operator = ( const ROCm & ) = default ;
//@}
//------------------------------------
//! \name Functions that all Kokkos devices must implement.
//@{
KOKKOS_INLINE_FUNCTION static int in_parallel() {
#if defined( __HCC_ACCELERATOR__ )
return true;
#else
return false;
#endif
}
/** \brief Set the device in a "sleep" state. */
static bool sleep() ;
/** \brief Wake the device from the 'sleep' state. A noop for OpenMP. */
static bool wake() ;
/** \brief Wait until all dispatched functors complete. A noop for OpenMP. */
static void fence() ;
/// \brief Print configuration information to the given output stream.
static void print_configuration( std::ostream & , const bool detail = false );
/// \brief Free any resources being consumed by the device.
static void finalize() ;
/** \brief Initialize the device.
*
*/
struct SelectDevice {
int rocm_device_id ;
SelectDevice() : rocm_device_id(1) {}
explicit SelectDevice( int id ) : rocm_device_id( id+1 ) {}
};
int rocm_device() const { return m_device ; }
bool isAPU();
bool isAPU(int device);
static void initialize( const SelectDevice = SelectDevice());
static int is_initialized();
// static size_type device_arch();
// static size_type detect_device_count();
static int concurrency() ;
static const char* name();
private:
int m_device ;
};
}
} // namespace Kokkos
namespace Kokkos {
namespace Impl {
template<>
struct MemorySpaceAccess
< Kokkos::Experimental::ROCmSpace
, Kokkos::Experimental::ROCm::scratch_memory_space
>
{
enum { assignable = false };
enum { accessible = true };
enum { deepcopy = false };
};
template<>
struct VerifyExecutionCanAccessMemorySpace
< Kokkos::Experimental::ROCm::memory_space
, Kokkos::Experimental::ROCm::scratch_memory_space
>
{
enum { value = true };
KOKKOS_INLINE_FUNCTION static void verify( void ) { }
KOKKOS_INLINE_FUNCTION static void verify( const void * ) { }
};
template<>
struct VerifyExecutionCanAccessMemorySpace
< Kokkos::HostSpace
, Kokkos::Experimental::ROCm::scratch_memory_space
>
{
enum { value = false };
inline static void verify( void ) { Experimental::ROCmSpace::access_error(); }
inline static void verify( const void * p ) { Experimental::ROCmSpace::access_error(p); }
};
} // namespace Experimental
} // namespace Kokkos
#include <ROCm/Kokkos_ROCm_Parallel.hpp>
#include <ROCm/Kokkos_ROCm_Task.hpp>
#endif
#endif

View File

@ -0,0 +1,622 @@
/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#ifndef KOKKOS_ROCMSPACE_HPP
#define KOKKOS_ROCMSPACE_HPP
#include <Kokkos_Core_fwd.hpp>
#if defined( KOKKOS_ENABLE_ROCM )
#include <iosfwd>
#include <typeinfo>
#include <string>
#include <Kokkos_HostSpace.hpp>
/*--------------------------------------------------------------------------*/
namespace Kokkos {
namespace Experimental {
/** \brief ROCm on-device memory management */
class ROCmSpace {
public:
//! Tag this class as a kokkos memory space
typedef ROCmSpace memory_space ;
typedef Kokkos::Experimental::ROCm execution_space ;
typedef Kokkos::Device<execution_space,memory_space> device_type;
typedef unsigned int size_type ;
/*--------------------------------*/
ROCmSpace();
ROCmSpace( ROCmSpace && rhs ) = default ;
ROCmSpace( const ROCmSpace & rhs ) = default ;
ROCmSpace & operator = ( ROCmSpace && rhs ) = default ;
ROCmSpace & operator = ( const ROCmSpace & rhs ) = default ;
~ROCmSpace() = default ;
/**\brief Allocate untracked memory in the rocm space */
void * allocate( const size_t arg_alloc_size ) const ;
/**\brief Deallocate untracked memory in the rocm space */
void deallocate( void * const arg_alloc_ptr
, const size_t arg_alloc_size ) const ;
/**\brief Return Name of the MemorySpace */
static constexpr const char* name() { return m_name; };
/*--------------------------------*/
/** \brief Error reporting for HostSpace attempt to access ROCmSpace */
static void access_error();
static void access_error( const void * const );
private:
int m_device ; ///< Which ROCm device
static constexpr const char* m_name = "ROCm";
friend class Kokkos::Impl::SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void > ;
};
} // namespace Experimental
namespace Impl {
void * rocm_device_allocate(int);
void * rocm_hostpinned_allocate(int);
void rocm_device_free(void * );
/// \brief Initialize lock array for arbitrary size atomics.
///
/// Arbitrary atomics are implemented using a hash table of locks
/// where the hash value is derived from the address of the
/// object for which an atomic operation is performed.
/// This function initializes the locks to zero (unset).
void init_lock_arrays_rocm_space();
/// \brief Retrieve the pointer to the lock array for arbitrary size atomics.
///
/// Arbitrary atomics are implemented using a hash table of locks
/// where the hash value is derived from the address of the
/// object for which an atomic operation is performed.
/// This function retrieves the lock array pointer.
/// If the array is not yet allocated it will do so.
int* atomic_lock_array_rocm_space_ptr(bool deallocate = false);
/// \brief Retrieve the pointer to the scratch array for team and thread private global memory.
///
/// Team and Thread private scratch allocations in
/// global memory are aquired via locks.
/// This function retrieves the lock array pointer.
/// If the array is not yet allocated it will do so.
int* scratch_lock_array_rocm_space_ptr(bool deallocate = false);
/// \brief Retrieve the pointer to the scratch array for unique identifiers.
///
/// Unique identifiers in the range 0-ROCm::concurrency
/// are provided via locks.
/// This function retrieves the lock array pointer.
/// If the array is not yet allocated it will do so.
int* threadid_lock_array_rocm_space_ptr(bool deallocate = false);
}
} // namespace Kokkos
/*--------------------------------------------------------------------------*/
/*--------------------------------------------------------------------------*/
namespace Kokkos {
namespace Experimental {
/** \brief Host memory that is accessible to ROCm execution space
* through ROCm's host-pinned memory allocation.
*/
class ROCmHostPinnedSpace {
public:
//! Tag this class as a kokkos memory space
/** \brief Memory is in HostSpace so use the HostSpace::execution_space */
typedef HostSpace::execution_space execution_space ;
typedef ROCmHostPinnedSpace memory_space ;
typedef Kokkos::Device<execution_space,memory_space> device_type;
typedef unsigned int size_type ;
/*--------------------------------*/
ROCmHostPinnedSpace();
ROCmHostPinnedSpace( ROCmHostPinnedSpace && rhs ) = default ;
ROCmHostPinnedSpace( const ROCmHostPinnedSpace & rhs ) = default ;
ROCmHostPinnedSpace & operator = ( ROCmHostPinnedSpace && rhs ) = default ;
ROCmHostPinnedSpace & operator = ( const ROCmHostPinnedSpace & rhs ) = default ;
~ROCmHostPinnedSpace() = default ;
/**\brief Allocate untracked memory in the space */
void * allocate( const size_t arg_alloc_size ) const ;
/**\brief Deallocate untracked memory in the space */
void deallocate( void * const arg_alloc_ptr
, const size_t arg_alloc_size ) const ;
/**\brief Return Name of the MemorySpace */
static constexpr const char* name() { return m_name; };
private:
static constexpr const char* m_name = "ROCmHostPinned";
/*--------------------------------*/
};
} // namespace Experimental
} // namespace Kokkos
/*--------------------------------------------------------------------------*/
/*--------------------------------------------------------------------------*/
namespace Kokkos {
namespace Impl {
static_assert( Kokkos::Impl::MemorySpaceAccess< Kokkos::Experimental::ROCmSpace , Kokkos::Experimental::ROCmSpace >::assignable , "" );
//----------------------------------------
template<>
struct MemorySpaceAccess< Kokkos::HostSpace , Kokkos::Experimental::ROCmSpace > {
enum { assignable = false };
enum { accessible = false };
enum { deepcopy = true };
};
template<>
struct MemorySpaceAccess< Kokkos::HostSpace , Kokkos::Experimental::ROCmHostPinnedSpace > {
// HostSpace::execution_space == ROCmHostPinnedSpace::execution_space
enum { assignable = true };
enum { accessible = true };
enum { deepcopy = true };
};
//----------------------------------------
template<>
struct MemorySpaceAccess< Kokkos::Experimental::ROCmSpace , Kokkos::HostSpace > {
enum { assignable = false };
enum { accessible = false };
enum { deepcopy = true };
};
template<>
struct MemorySpaceAccess< Kokkos::Experimental::ROCmSpace , Kokkos::Experimental::ROCmHostPinnedSpace > {
// ROCmSpace::execution_space != ROCmHostPinnedSpace::execution_space
enum { assignable = false };
enum { accessible = true }; // ROCmSpace::execution_space
enum { deepcopy = true };
};
//----------------------------------------
// ROCmHostPinnedSpace::execution_space == HostSpace::execution_space
// ROCmHostPinnedSpace accessible to both ROCm and Host
template<>
struct MemorySpaceAccess< Kokkos::Experimental::ROCmHostPinnedSpace , Kokkos::HostSpace > {
enum { assignable = false }; // Cannot access from ROCm
enum { accessible = true }; // ROCmHostPinnedSpace::execution_space
enum { deepcopy = true };
};
template<>
struct MemorySpaceAccess< Kokkos::Experimental::ROCmHostPinnedSpace , Kokkos::Experimental::ROCmSpace > {
enum { assignable = false }; // Cannot access from Host
enum { accessible = false };
enum { deepcopy = true };
};
};
//----------------------------------------
} // namespace Kokkos::Impl
/*--------------------------------------------------------------------------*/
/*--------------------------------------------------------------------------*/
namespace Kokkos {
namespace Impl {
hc::completion_future DeepCopyAsyncROCm( void * dst , const void * src , size_t n);
template<> struct DeepCopy< Kokkos::Experimental::ROCmSpace , Kokkos::Experimental::ROCmSpace , Kokkos::Experimental::ROCm>
{
DeepCopy( void * dst , const void * src , size_t );
DeepCopy( const Kokkos::Experimental::ROCm & , void * dst , const void * src , size_t );
};
template<> struct DeepCopy< Kokkos::Experimental::ROCmSpace , HostSpace , Kokkos::Experimental::ROCm >
{
DeepCopy( void * dst , const void * src , size_t );
DeepCopy( const Kokkos::Experimental::ROCm & , void * dst , const void * src , size_t );
};
template<> struct DeepCopy< HostSpace , Kokkos::Experimental::ROCmSpace , Kokkos::Experimental::ROCm >
{
DeepCopy( void * dst , const void * src , size_t );
DeepCopy( const Kokkos::Experimental::ROCm & , void * dst , const void * src , size_t );
};
template<class ExecutionSpace> struct DeepCopy< Kokkos::Experimental::ROCmSpace , Kokkos::Experimental::ROCmSpace , ExecutionSpace >
{
inline
DeepCopy( void * dst , const void * src , size_t n )
{ (void) DeepCopy< Kokkos::Experimental::ROCmSpace , Kokkos::Experimental::ROCmSpace , Kokkos::Experimental::ROCm >( dst , src , n ); }
inline
DeepCopy( const ExecutionSpace& exec, void * dst , const void * src , size_t n )
{
exec.fence();
hc::completion_future fut = DeepCopyAsyncROCm (dst,src,n);
fut.wait();
// DeepCopy (dst,src,n);
}
};
template<class ExecutionSpace> struct DeepCopy< Kokkos::Experimental::ROCmSpace , HostSpace , ExecutionSpace >
{
inline
DeepCopy( void * dst , const void * src , size_t n )
{ (void) DeepCopy< Kokkos::Experimental::ROCmSpace , HostSpace , Kokkos::Experimental::ROCm>( dst , src , n ); }
inline
DeepCopy( const ExecutionSpace& exec, void * dst , const void * src , size_t n )
{
exec.fence();
DeepCopy (dst,src,n);
}
};
template<class ExecutionSpace>
struct DeepCopy< HostSpace , Kokkos::Experimental::ROCmSpace , ExecutionSpace >
{
inline
DeepCopy( void * dst , const void * src , size_t n )
{ (void) DeepCopy< HostSpace , Kokkos::Experimental::ROCmSpace , Kokkos::Experimental::ROCm >( dst , src , n ); }
inline
DeepCopy( const ExecutionSpace& exec, void * dst , const void * src , size_t n )
{
exec.fence();
DeepCopy (dst,src,n);
}
};
template<> struct DeepCopy< Kokkos::Experimental::ROCmHostPinnedSpace , Kokkos::Experimental::ROCmHostPinnedSpace , Kokkos::Experimental::ROCm>
{
DeepCopy( void * dst , const void * src , size_t );
DeepCopy( const Kokkos::Experimental::ROCm & , void * dst , const void * src , size_t );
};
template<> struct DeepCopy< Kokkos::Experimental::ROCmHostPinnedSpace , HostSpace , Kokkos::Experimental::ROCm >
{
DeepCopy( void * dst , const void * src , size_t );
DeepCopy( const Kokkos::Experimental::ROCm & , void * dst , const void * src , size_t );
};
template<> struct DeepCopy< HostSpace , Kokkos::Experimental::ROCmHostPinnedSpace , Kokkos::Experimental::ROCm >
{
DeepCopy( void * dst , const void * src , size_t );
DeepCopy( const Kokkos::Experimental::ROCm & , void * dst , const void * src , size_t );
};
template<class ExecutionSpace>
struct DeepCopy< Kokkos::Experimental::ROCmSpace , Kokkos::Experimental::ROCmHostPinnedSpace , ExecutionSpace>
{
inline
DeepCopy( void * dst , const void * src , size_t n )
{ (void) DeepCopy< Kokkos::Experimental::ROCmSpace , HostSpace , Kokkos::Experimental::ROCm >( dst , src , n ); }
inline
DeepCopy( const ExecutionSpace& exec, void * dst , const void * src , size_t n )
{
exec.fence();
hc::completion_future fut = DeepCopyAsyncROCm (dst,src,n);
fut.wait();
// DeepCopyROCm (dst,src,n);
}
};
template<class ExecutionSpace> struct DeepCopy< Kokkos::Experimental::ROCmHostPinnedSpace , Kokkos::Experimental::ROCmSpace , ExecutionSpace >
{
inline
DeepCopy( void * dst , const void * src , size_t n )
{ (void) DeepCopy< HostSpace , Kokkos::Experimental::ROCmSpace , Kokkos::Experimental::ROCm >( dst , src , n ); }
inline
DeepCopy( const ExecutionSpace& exec, void * dst , const void * src , size_t n )
{
exec.fence();
hc::completion_future fut = DeepCopyAsyncROCm (dst,src,n);
fut.wait();
// DeepCopyROCm (dst,src,n);
}
};
template<class ExecutionSpace> struct DeepCopy< Kokkos::Experimental::ROCmHostPinnedSpace , Kokkos::Experimental::ROCmHostPinnedSpace , ExecutionSpace >
{
inline
DeepCopy( void * dst , const void * src , size_t n )
{ (void) DeepCopy< Kokkos::Experimental::ROCmHostPinnedSpace , Kokkos::Experimental::ROCmHostPinnedSpace , Kokkos::Experimental::ROCm >( dst , src , n ); }
inline
DeepCopy( const ExecutionSpace& exec, void * dst , const void * src , size_t n )
{
exec.fence();
// hc::completion_future fut = DeepCopyAsyncROCm (dst,src,n);
// fut.wait();
// DeepCopyAsyncROCm (dst,src,n);
DeepCopy (dst,src,n);
}
};
template<class ExecutionSpace> struct DeepCopy< Kokkos::Experimental::ROCmHostPinnedSpace , HostSpace , ExecutionSpace >
{
inline
DeepCopy( void * dst , const void * src , size_t n )
{ (void) DeepCopy< Kokkos::Experimental::ROCmHostPinnedSpace , HostSpace , Kokkos::Experimental::ROCm>( dst , src , n ); }
inline
DeepCopy( const ExecutionSpace& exec, void * dst , const void * src , size_t n )
{
exec.fence();
DeepCopy (dst,src,n);
}
};
template<class ExecutionSpace>
struct DeepCopy< HostSpace , Kokkos::Experimental::ROCmHostPinnedSpace , ExecutionSpace >
{
inline
DeepCopy( void * dst , const void * src , size_t n )
{ (void) DeepCopy< HostSpace , Kokkos::Experimental::ROCmHostPinnedSpace , Kokkos::Experimental::ROCm >( dst , src , n ); }
inline
DeepCopy( const ExecutionSpace& exec, void * dst , const void * src , size_t n )
{
exec.fence();
DeepCopy (dst,src,n);
}
};
} // namespace Impl
} // namespace Kokkos
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Impl {
/** Running in ROCmSpace attempting to access HostSpace: error */
template<>
struct VerifyExecutionCanAccessMemorySpace< Kokkos::Experimental::ROCmSpace , Kokkos::HostSpace >
{
enum { value = false };
KOKKOS_INLINE_FUNCTION static void verify( void )
{ Kokkos::abort("ROCm code attempted to access HostSpace memory"); }
KOKKOS_INLINE_FUNCTION static void verify( const void * )
{ Kokkos::abort("ROCm code attempted to access HostSpace memory"); }
};
/** Running in ROCmSpace accessing ROCmHostPinnedSpace: ok */
template<>
struct VerifyExecutionCanAccessMemorySpace< Kokkos::Experimental::ROCmSpace , Kokkos::Experimental::ROCmHostPinnedSpace >
{
enum { value = true };
KOKKOS_INLINE_FUNCTION static void verify( void ) { }
KOKKOS_INLINE_FUNCTION static void verify( const void * ) { }
};
/** Running in ROCmSpace attempting to access an unknown space: error */
template< class OtherSpace >
struct VerifyExecutionCanAccessMemorySpace<
typename enable_if< ! is_same<Kokkos::Experimental::ROCmSpace,OtherSpace>::value , Kokkos::Experimental::ROCmSpace >::type ,
OtherSpace >
{
enum { value = false };
KOKKOS_INLINE_FUNCTION static void verify( void )
{ Kokkos::abort("ROCm code attempted to access unknown Space memory"); }
KOKKOS_INLINE_FUNCTION static void verify( const void * )
{ Kokkos::abort("ROCm code attempted to access unknown Space memory"); }
};
//----------------------------------------------------------------------------
/** Running in HostSpace attempting to access ROCmSpace */
template<>
struct VerifyExecutionCanAccessMemorySpace< Kokkos::HostSpace , Kokkos::Experimental::ROCmSpace >
{
enum { value = false };
inline static void verify( void ) { Kokkos::Experimental::ROCmSpace::access_error(); }
inline static void verify( const void * p ) { Kokkos::Experimental::ROCmSpace::access_error(p); }
};
/** Running in HostSpace accessing ROCmHostPinnedSpace is OK */
template<>
struct VerifyExecutionCanAccessMemorySpace< Kokkos::HostSpace , Kokkos::Experimental::ROCmHostPinnedSpace >
{
enum { value = true };
KOKKOS_INLINE_FUNCTION static void verify( void ) {}
KOKKOS_INLINE_FUNCTION static void verify( const void * ) {}
};
} // namespace Impl
} // namespace Kokkos
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Impl {
template<>
class SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >
: public SharedAllocationRecord< void , void >
{
private:
typedef SharedAllocationRecord< void , void > RecordBase ;
SharedAllocationRecord( const SharedAllocationRecord & ) = delete ;
SharedAllocationRecord & operator = ( const SharedAllocationRecord & ) = delete ;
static void deallocate( RecordBase * );
static RecordBase s_root_record ;
const Kokkos::Experimental::ROCmSpace m_space ;
protected:
~SharedAllocationRecord();
SharedAllocationRecord( const Kokkos::Experimental::ROCmSpace & arg_space
, const std::string & arg_label
, const size_t arg_alloc_size
, const RecordBase::function_type arg_dealloc = & deallocate
);
public:
std::string get_label() const ;
static SharedAllocationRecord * allocate( const Kokkos::Experimental::ROCmSpace & arg_space
, const std::string & arg_label
, const size_t arg_alloc_size );
/**\brief Allocate tracked memory in the space */
static
void * allocate_tracked( const Kokkos::Experimental::ROCmSpace & arg_space
, const std::string & arg_label
, const size_t arg_alloc_size );
/**\brief Reallocate tracked memory in the space */
static
void * reallocate_tracked( void * const arg_alloc_ptr
, const size_t arg_alloc_size );
/**\brief Deallocate tracked memory in the space */
static
void deallocate_tracked( void * const arg_alloc_ptr );
static SharedAllocationRecord * get_record( void * arg_alloc_ptr );
static void print_records( std::ostream & , const Kokkos::Experimental::ROCmSpace & , bool detail = false );
};
template<>
class SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >
: public SharedAllocationRecord< void , void >
{
private:
typedef SharedAllocationRecord< void , void > RecordBase ;
SharedAllocationRecord( const SharedAllocationRecord & ) = delete ;
SharedAllocationRecord & operator = ( const SharedAllocationRecord & ) = delete ;
static void deallocate( RecordBase * );
static RecordBase s_root_record ;
const Kokkos::Experimental::ROCmHostPinnedSpace m_space ;
protected:
~SharedAllocationRecord();
SharedAllocationRecord() : RecordBase(), m_space() {}
SharedAllocationRecord( const Kokkos::Experimental::ROCmHostPinnedSpace & arg_space
, const std::string & arg_label
, const size_t arg_alloc_size
, const RecordBase::function_type arg_dealloc = & deallocate
);
public:
std::string get_label() const ;
static SharedAllocationRecord * allocate( const Kokkos::Experimental::ROCmHostPinnedSpace & arg_space
, const std::string & arg_label
, const size_t arg_alloc_size
);
/**\brief Allocate tracked memory in the space */
static
void * allocate_tracked( const Kokkos::Experimental::ROCmHostPinnedSpace & arg_space
, const std::string & arg_label
, const size_t arg_alloc_size );
/**\brief Reallocate tracked memory in the space */
static
void * reallocate_tracked( void * const arg_alloc_ptr
, const size_t arg_alloc_size );
/**\brief Deallocate tracked memory in the space */
static
void deallocate_tracked( void * const arg_alloc_ptr );
static SharedAllocationRecord * get_record( void * arg_alloc_ptr );
static void print_records( std::ostream & , const Kokkos::Experimental::ROCmHostPinnedSpace & , bool detail = false );
};
} // namespace Impl
} // namespace Kokkos
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
#endif /* #if defined( KOKKOS_ENABLE_ROCM ) */
#endif /* #define KOKKOS_ROCMSPACE_HPP */

View File

@ -681,6 +681,67 @@ public:
return f ;
}
template < class F >
KOKKOS_FUNCTION
Future< execution_space >
when_all( int narg , F const func )
{
using input_type = decltype( func(0) );
using future_type = Future< execution_space > ;
using task_base = Kokkos::Impl::TaskBase< void , void , void > ;
static_assert( is_future< input_type >::value
, "Functor must return a Kokkos::Future" );
future_type f ;
if ( 0 == narg ) return f ;
size_t const alloc_size = m_queue->when_all_allocation_size( narg );
f.m_task =
reinterpret_cast< task_base * >( m_queue->allocate( alloc_size ) );
if ( f.m_task ) {
// Reference count starts at two:
// +1 to match decrement when task completes
// +1 for the future
new( f.m_task ) task_base();
f.m_task->m_queue = m_queue ;
f.m_task->m_ref_count = 2 ;
f.m_task->m_alloc_size = alloc_size ;
f.m_task->m_dep_count = narg ;
f.m_task->m_task_type = task_base::Aggregate ;
// Assign dependences, reference counts were already incremented
task_base * volatile * const dep =
f.m_task->aggregate_dependences();
for ( int i = 0 ; i < narg ; ++i ) {
const input_type arg_f = func(i);
if ( 0 != arg_f.m_task ) {
if ( m_queue != static_cast< queue_type * >( arg_f.m_task->m_queue ) ) {
Kokkos::abort("Kokkos when_all Futures must be in the same scheduler" );
}
// Increment reference count to track subsequent assignment.
Kokkos::atomic_increment( &(arg_f.m_task->m_ref_count) );
dep[i] = arg_f.m_task ;
}
}
Kokkos::memory_fence();
m_queue->schedule_aggregate( f.m_task );
// this when_all may be processed at any moment
}
return f ;
}
//----------------------------------------
KOKKOS_INLINE_FUNCTION

View File

@ -2429,6 +2429,7 @@ template < class ValueType >
struct CommonViewAllocProp< void, ValueType >
{
using value_type = ValueType;
using scalar_array_type = ValueType;
template < class ... Views >
CommonViewAllocProp( const Views & ... ) {}

View File

@ -0,0 +1,439 @@
/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#include <hc.hpp>
//#include <hsa_atomic.h>
#ifdef KOKKOS_ENABLE_ROCM_ATOMICS
namespace Kokkos {
//ROCm can do:
//Types int/unsigned int
//variants: atomic_exchange/compare_exchange/fetch_add/fetch_sub/fetch_max/fetch_min/fetch_and/fetch_or/fetch_xor/fetch_inc/fetch_dec
KOKKOS_INLINE_FUNCTION
int atomic_exchange(int* dest, const int& val) {
return hc::atomic_exchange_int(dest, val);
}
KOKKOS_INLINE_FUNCTION
unsigned int atomic_exchange(unsigned int* dest, const unsigned int& val) {
return hc::atomic_exchange_unsigned(dest, val);
}
KOKKOS_INLINE_FUNCTION
int64_t atomic_exchange(int64_t* dest, const int64_t& val) {
return (int64_t)hc::atomic_exchange_uint64((uint64_t*)dest, (const uint64_t&)val);
}
KOKKOS_INLINE_FUNCTION
uint64_t atomic_exchange(uint64_t* dest, const uint64_t& val) {
return hc::atomic_exchange_uint64(dest, val);
}
KOKKOS_INLINE_FUNCTION
long long atomic_exchange(long long* dest, const long long& val) {
return (long long)hc::atomic_exchange_uint64((uint64_t*)dest, (const uint64_t&)val);
}
KOKKOS_INLINE_FUNCTION
unsigned long long atomic_exchange(unsigned long long* dest, const unsigned long long& val) {
return (unsigned long long)hc::atomic_exchange_uint64((uint64_t*)dest, (const uint64_t&)val);
}
KOKKOS_INLINE_FUNCTION
float atomic_exchange(float* dest, const float& val) {
union U {
int i ;
float f ;
KOKKOS_INLINE_FUNCTION U() {};
} idest,ival;
idest.f = *dest;
ival.f = val;
idest.i = hc::atomic_exchange_int((int*)dest, ival.i);
return idest.f;
}
KOKKOS_INLINE_FUNCTION
double atomic_exchange(double* dest, const double& val) {
union U {
uint64_t i ;
double d ;
KOKKOS_INLINE_FUNCTION U() {};
} idest,ival;
idest.d = *dest;
ival.d = val;
idest.i = hc::atomic_exchange_uint64((uint64_t*)dest, ival.i);
return idest.d;
}
KOKKOS_INLINE_FUNCTION
int atomic_compare_exchange(int* dest, int compare, const int& val);
KOKKOS_INLINE_FUNCTION
int64_t atomic_compare_exchange(int64_t* dest, int64_t compare, const int64_t& val);
template<class T>
KOKKOS_INLINE_FUNCTION
T atomic_exchange(T* dest, typename std::enable_if<sizeof(T) == sizeof(int), const T&>::type val) {
union U {
int i ;
T t ;
KOKKOS_INLINE_FUNCTION U() {};
} assume , oldval , newval ;
oldval.t = *dest ;
assume.i = oldval.i ;
newval.t = val ;
atomic_compare_exchange( reinterpret_cast<int*>(dest) , assume.i, newval.i );
return oldval.t ;
}
template<class T>
KOKKOS_INLINE_FUNCTION
T atomic_exchange(T* dest, typename std::enable_if<sizeof(T) != sizeof(int) && sizeof(T) == sizeof(int64_t), const T&>::type val) {
union U {
uint64_t i ;
T t ;
KOKKOS_INLINE_FUNCTION U() {};
} assume , oldval , newval ;
oldval.t = *dest ;
assume.i = oldval.i ;
newval.t = val ;
atomic_compare_exchange( (int64_t*)(dest) , assume.i, newval.i );
return oldval.t ;
}
template<class T>
KOKKOS_INLINE_FUNCTION
T atomic_exchange(T* dest, typename std::enable_if<sizeof(T) != sizeof(int) && sizeof(T) != sizeof(int64_t), const T&>::type val) {
return val;
}
KOKKOS_INLINE_FUNCTION
int atomic_compare_exchange(int* dest, int compare, const int& val) {
return hc::atomic_compare_exchange_int(dest, compare, val);
}
KOKKOS_INLINE_FUNCTION
unsigned int atomic_compare_exchange(unsigned int* dest, unsigned int compare, const unsigned int& val) {
return hc::atomic_compare_exchange_unsigned(dest, compare, val);
}
KOKKOS_INLINE_FUNCTION
int64_t atomic_compare_exchange(int64_t* dest, int64_t compare, const int64_t& val) {
return (int64_t) hc::atomic_compare_exchange_uint64((uint64_t*)dest, (uint64_t)compare, (const uint64_t&)val);
}
KOKKOS_INLINE_FUNCTION
uint64_t atomic_compare_exchange(uint64_t* dest, uint64_t compare, const uint64_t& val) {
return hc::atomic_compare_exchange_uint64(dest, compare, val);
}
KOKKOS_INLINE_FUNCTION
long long atomic_compare_exchange(long long* dest, long long compare, const long long& val) {
return (long long)hc::atomic_compare_exchange_uint64((uint64_t*)(dest), (uint64_t)(compare), (const uint64_t&)(val));
}
KOKKOS_INLINE_FUNCTION
float atomic_compare_exchange(float* dest, float compare, const float& val) {
union U {
int i ;
float f ;
KOKKOS_INLINE_FUNCTION U() {};
} idest,icompare,ival;
idest.f = *dest;
icompare.f = compare;
ival.f = val;
idest.i = hc::atomic_compare_exchange_int(reinterpret_cast<int*>(dest), icompare.i, ival.i);
return idest.f;
}
KOKKOS_INLINE_FUNCTION
double atomic_compare_exchange(double* dest, double compare, const double& val) {
union U {
uint64_t i ;
double d ;
KOKKOS_INLINE_FUNCTION U() {};
} idest,icompare,ival;
idest.d = *dest;
icompare.d = compare;
ival.d = val;
idest.i = hc::atomic_compare_exchange_uint64(reinterpret_cast<uint64_t*>(dest), icompare.i, ival.i);
return idest.d;
}
template<class T>
KOKKOS_INLINE_FUNCTION
T atomic_compare_exchange(volatile T* dest, T compare, typename std::enable_if<sizeof(T) == sizeof(int), const T&>::type val) {
union U {
int i ;
T f ;
KOKKOS_INLINE_FUNCTION U() {};
} idest,icompare,ival;
idest.f = *dest;
icompare.f = compare;
ival.f = val;
idest.i = hc::atomic_compare_exchange_int((int*)(dest), icompare.i, ival.i);
return idest.f;
}
template<class T>
KOKKOS_INLINE_FUNCTION
T atomic_compare_exchange(volatile T* dest, T compare, typename std::enable_if<sizeof(T) == sizeof(int64_t), const T&>::type val) {
union U {
uint64_t i ;
T f ;
KOKKOS_INLINE_FUNCTION U() {};
} idest,icompare,ival;
idest.f = *dest;
icompare.f = compare;
ival.f = val;
idest.i = hc::atomic_compare_exchange_uint64((uint64_t*)(dest), icompare.i, ival.i);
return idest.f;
}
template<class T>
KOKKOS_INLINE_FUNCTION
T atomic_compare_exchange(volatile T* dest, T compare, typename std::enable_if<(sizeof(T) != sizeof(int32_t)) && (sizeof(T) != sizeof(int64_t)), const T&>::type val) {
return val;
}
KOKKOS_INLINE_FUNCTION
int atomic_fetch_add (volatile int * dest, const int& val) {
return hc::atomic_fetch_add((int *)dest, val);
}
KOKKOS_INLINE_FUNCTION
unsigned int atomic_fetch_add(unsigned int* dest, const unsigned int& val) {
return hc::atomic_fetch_add(dest, val);
}
KOKKOS_INLINE_FUNCTION
unsigned long atomic_fetch_add(volatile unsigned long* dest, const unsigned long& val) {
return (unsigned long)hc::atomic_fetch_add((uint64_t *)dest, (const uint64_t)val);
}
KOKKOS_INLINE_FUNCTION
int64_t atomic_fetch_add(volatile int64_t* dest, const int64_t& val) {
return (int64_t)hc::atomic_fetch_add((uint64_t *)dest, (const uint64_t&)val);
}
KOKKOS_INLINE_FUNCTION
char atomic_fetch_add(volatile char * dest, const char& val) {
unsigned int oldval,newval,assume;
oldval = *(int *)dest ;
do {
assume = oldval ;
newval = assume&0x7fffff00 + ((assume&0xff)+val)&0xff ;
oldval = hc::atomic_compare_exchange_unsigned((unsigned int*)dest, assume,newval);
} while ( assume != oldval );
return oldval ;
}
KOKKOS_INLINE_FUNCTION
short atomic_fetch_add(volatile short * dest, const short& val) {
unsigned int oldval,newval,assume;
oldval = *(int *)dest ;
do {
assume = oldval ;
newval = assume&0x7fff0000 + ((assume&0xffff)+val)&0xffff ;
oldval = hc::atomic_compare_exchange_unsigned((unsigned int*)dest, assume,newval);
} while ( assume != oldval );
return oldval ;
}
KOKKOS_INLINE_FUNCTION
long long atomic_fetch_add(volatile long long * dest, const long long& val) {
return (long long)hc::atomic_fetch_add((uint64_t*)dest, (const uint64_t&)val);
}
KOKKOS_INLINE_FUNCTION
int atomic_fetch_sub (volatile int * dest, const int& val) {
return hc::atomic_fetch_sub((int *)dest, val);
}
KOKKOS_INLINE_FUNCTION
unsigned int atomic_fetch_sub(volatile unsigned int* dest, const unsigned int& val) {
return hc::atomic_fetch_sub((unsigned int *)dest, val);
}
KOKKOS_INLINE_FUNCTION
int64_t atomic_fetch_sub(int64_t* dest, const int64_t& val) {
return (int64_t)hc::atomic_fetch_add((uint64_t *)dest, -(const uint64_t&)val);
// return (int64_t)hc::atomic_fetch_sub_uint64((uint64_t*)dest, (const uint64_t&)val);
}
KOKKOS_INLINE_FUNCTION
char atomic_fetch_sub(volatile char * dest, const char& val) {
unsigned int oldval,newval,assume;
oldval = *(int *)dest ;
do {
assume = oldval ;
newval = assume&0x7fffff00 + ((assume&0xff)-val)&0xff ;
oldval = hc::atomic_compare_exchange_unsigned((unsigned int*)dest, assume,newval);
} while ( assume != oldval );
return oldval ;
}
KOKKOS_INLINE_FUNCTION
short atomic_fetch_sub(volatile short * dest, const short& val) {
unsigned int oldval,newval,assume;
oldval = *(int *)dest ;
do {
assume = oldval ;
newval = assume&0x7fff0000 + ((assume&0xffff)-val)&0xffff;
oldval = hc::atomic_compare_exchange_unsigned((unsigned int*)dest, assume,newval);
} while ( assume != oldval );
return oldval ;
}
KOKKOS_INLINE_FUNCTION
long long atomic_fetch_sub(volatile long long * dest, const long long& val) {
return (long long)hc::atomic_fetch_add((uint64_t*)dest, -(const uint64_t&)val);
}
template<class T>
KOKKOS_INLINE_FUNCTION
T atomic_fetch_add(volatile T* dest, typename std::enable_if<sizeof(T) == sizeof(int), const T&>::type val) {
union U {
unsigned int i ;
T t ;
KOKKOS_INLINE_FUNCTION U() {};
} assume , oldval , newval ;
oldval.t = *dest ;
do {
assume.i = oldval.i ;
newval.t = assume.t + val ;
oldval.i = atomic_compare_exchange( (unsigned int*)(dest) , assume.i , newval.i );
} while ( assume.i != oldval.i );
return oldval.t ;
}
template<class T>
KOKKOS_INLINE_FUNCTION
T atomic_fetch_add(volatile T* dest, typename std::enable_if<sizeof(T) != sizeof(int) && sizeof(T) == sizeof(int64_t), const T&>::type val) {
union U {
uint64_t i ;
T t ;
KOKKOS_INLINE_FUNCTION U() {};
} assume , oldval , newval ;
oldval.t = *dest ;
do {
assume.i = oldval.i ;
newval.t = assume.t + val ;
oldval.i = atomic_compare_exchange( (uint64_t*)dest , assume.i , newval.i );
} while ( assume.i != oldval.i );
return oldval.t ;
}
//WORKAROUND
template<class T>
KOKKOS_INLINE_FUNCTION
T atomic_fetch_add(volatile T* dest, typename std::enable_if<sizeof(T) != sizeof(int) && sizeof(T) != sizeof(int64_t), const T&>::type val) {
return val ;
}
template<class T>
KOKKOS_INLINE_FUNCTION
T atomic_fetch_sub(volatile T* dest, typename std::enable_if<sizeof(T) == sizeof(int),T>::type & val) {
union U {
int i ;
T t ;
KOKKOS_INLINE_FUNCTION U() {};
} assume , oldval , newval ;
oldval.t = *dest ;
do {
assume.i = oldval.i ;
newval.t = assume.t - val ;
oldval.i = Kokkos::atomic_compare_exchange( (int*)dest , assume.i , newval.i );
} while ( assume.i != oldval.i );
return oldval.t ;
}
template<class T>
KOKKOS_INLINE_FUNCTION
T atomic_fetch_sub(volatile T* dest, typename std::enable_if<sizeof(T) != sizeof(int) && sizeof(T) == sizeof(int64_t), const T&>::type val) {
union U {
int64_t i ;
T t ;
KOKKOS_INLINE_FUNCTION U() {};
} assume , oldval , newval ;
oldval.t = *dest ;
do {
assume.i = oldval.i ;
newval.t = assume.t - val ;
oldval.i = atomic_compare_exchange( (int64_t*)dest , assume.i , newval.i );
} while ( assume.i != oldval.i );
return oldval.t ;
}
}
#endif

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/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#ifndef GUARD_CORE_KOKKOS_ROCM_CONFIG_HPP
#define GUARD_CORE_KOKKOS_ROCM_CONFIG_HPP
#ifndef KOKKOS_ROCM_HAS_WORKAROUNDS
#define KOKKOS_ROCM_HAS_WORKAROUNDS 1
#endif
#endif

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/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#ifndef KOKKOS_ROCMEXEC_HPP
#define KOKKOS_ROCMEXEC_HPP
#include <algorithm>
#include <typeinfo>
#include <Kokkos_Macros.hpp>
//#include <ROCm/Kokkos_ROCmExec.hpp>
#include <hc.hpp>
#define ROCM_SPACE_ATOMIC_MASK 0x1FFFF
#define ROCM_SPACE_ATOMIC_XOR_MASK 0x15A39
#define ROCM_CONCURRENCY 20480
//#define ROCM_CONCURRENCY 81920 # for fiji
namespace Kokkos {
static int rocm_space_atomic_locks[ROCM_SPACE_ATOMIC_MASK+1];
static int rocm_space_scratch_locks[ROCM_CONCURRENCY];
static int rocm_space_threadid_locks[ROCM_CONCURRENCY];
namespace Impl {
// TODO: mimic cuda implemtation, add dgpu capability
void init_rocm_atomic_lock_array() {
static int is_initialized = 0;
if(!is_initialized)
{
for(int i = 0; i < ROCM_SPACE_ATOMIC_MASK+1; i++)
rocm_space_atomic_locks[i] = 0;
is_initialized = 1;
}
}
void init_rocm_scratch_lock_array() {
static int is_initialized = 0;
if(!is_initialized)
{
for(int i = 0; i < ROCM_CONCURRENCY; i++)
rocm_space_scratch_locks[i] = 0;
is_initialized = 1;
}
}
void init_rocm_threadid_lock_array() {
static int is_initialized = 0;
if(!is_initialized)
{
for(int i = 0; i < ROCM_CONCURRENCY; i++)
rocm_space_threadid_locks[i] = 0;
is_initialized = 1;
}
}
void init_lock_arrays_rocm_space() {
init_rocm_atomic_lock_array();
// init_rocm_scratch_lock_array();
// init_rocm_threadid_lock_array();
}
}
} // namespace Kokkos
#if 0
namespace Kokkos {
namespace Impl {
KOKKOS_INLINE_FUNCTION
bool lock_address_rocm_space(void* ptr) {
#if 0
return(Kokkos::Impl::lock_address_host_space(ptr));
#else
size_t offset = size_t(ptr);
offset = offset >> 2;
offset = offset & ROCM_SPACE_ATOMIC_MASK;
return (0 == hc::atomic_compare_exchange(&rocm_space_atomic_locks[offset],0,1));
#endif
}
KOKKOS_INLINE_FUNCTION
void unlock_address_rocm_space(void* ptr) {
#if 0
Kokkos::Impl::unlock_address_host_space(ptr) ;
#else
size_t offset = size_t(ptr);
offset = offset >> 2;
offset = offset & ROCM_SPACE_ATOMIC_MASK;
hc::atomic_exchange( &rocm_space_atomic_locks[ offset ], 0);
#endif
}
}
} // namespace Kokkos
#endif
#endif /* #ifndef KOKKOS_ROCMEXEC_HPP */

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/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#ifndef KOKKOS_ROCMEXEC_HPP
#define KOKKOS_ROCMEXEC_HPP
#include <algorithm>
#include <typeinfo>
#if defined(__HCC_ACCELERATOR__)
#define printf(...)
#endif
namespace Kokkos {
namespace Impl {
struct ROCmTraits {
// TODO: determine if needed
enum { WavefrontSize = 64 /* 64 */ };
enum { WorkgroupSize = 64 /* 64 */ };
enum { WavefrontIndexMask = 0x001f /* Mask for warpindex */ };
enum { WavefrontIndexShift = 5 /* WarpSize == 1 << WarpShift */ };
enum { SharedMemoryBanks = 32 /* Compute device 2.0 */ };
enum { SharedMemoryCapacity = 0x0C000 /* 48k shared / 16k L1 Cache */ };
enum { SharedMemoryUsage = 0x04000 /* 16k shared / 48k L1 Cache */ };
enum { UpperBoundExtentCount = 65535 /* Hard upper bound */ };
#if 0
KOKKOS_INLINE_FUNCTION static
ROCmSpace::size_type wavefront_count( ROCmSpace::size_type i )
{ return ( i + WavefrontIndexMask ) >> WavefrontIndexShift ; }
KOKKOS_INLINE_FUNCTION static
ROCmSpace::size_type wavefront_align( ROCmSpace::size_type i )
{
enum { Mask = ~ROCmSpace::size_type( WavefrontIndexMask ) };
return ( i + WavefrontIndexMask ) & Mask ;
}
#endif
};
size_t rocm_internal_cu_count();
size_t rocm_internal_maximum_workgroup_count();
size_t * rocm_internal_scratch_flags( const size_t size );
size_t * rocm_internal_scratch_space( const size_t size );
}
} // namespace Kokkos
#define ROCM_SPACE_ATOMIC_MASK 0x1FFFF
#define ROCM_SPACE_ATOMIC_XOR_MASK 0x15A39
//int rocm_space_atomic_locks[ROCM_SPACE_ATOMIC_MASK+1];
extern int
*rocm_space_atomic_locks;
namespace Kokkos {
namespace Impl {
void init_lock_arrays_rocm_space();
void* rocm_resize_scratch_space(size_t bytes, bool force_shrink = false);
// TODO: determine if needed
KOKKOS_INLINE_FUNCTION
bool lock_address_rocm_space(void* ptr) {
#if 0
return(Kokkos::Impl::lock_address_host_space(ptr));
#else
size_t offset = size_t(ptr);
offset = offset >> 2;
offset = offset & ROCM_SPACE_ATOMIC_MASK;
return (0 == hc::atomic_compare_exchange(&rocm_space_atomic_locks[offset],0,1));
#endif
}
KOKKOS_INLINE_FUNCTION
void unlock_address_rocm_space(void* ptr) {
#if 0
Kokkos::Impl::unlock_address_host_space(ptr) ;
#else
size_t offset = size_t(ptr);
offset = offset >> 2;
offset = offset & ROCM_SPACE_ATOMIC_MASK;
hc::atomic_exchange( &rocm_space_atomic_locks[ offset ], 0);
#endif
}
}
} // namespace Kokkos
namespace Kokkos {
namespace Impl {
//extern
//KOKKOS_INLINE_FUNCTION
//void init_lock_arrays_rocm_space();
}
} // namespace Kokkos
#endif /* #ifndef KOKKOS_ROCMEXEC_HPP */

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/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
/*--------------------------------------------------------------------------*/
/* Kokkos interfaces */
#include <Kokkos_Core.hpp>
/* only compile this file if ROCM is enabled for Kokkos */
#ifdef KOKKOS_ENABLE_ROCM
//#include <ROCm/Kokkos_ROCm_Internal.hpp>
#include <impl/Kokkos_Error.hpp>
#include <Kokkos_ROCmSpace.hpp>
#include <ROCm/Kokkos_ROCm_Exec.hpp>
/*--------------------------------------------------------------------------*/
/* Standard 'C' libraries */
#include <stdlib.h>
/* Standard 'C++' libraries */
#include <vector>
#include <iostream>
#include <sstream>
#include <string>
//KOKKOS_INLINE_FUNCTION
// Kokkos::Impl::ROCmLockArraysStruct kokkos_impl_rocm_lock_arrays ;
/*--------------------------------------------------------------------------*/
namespace Kokkos {
namespace Impl {
#if 0
namespace {
__global__
void query_rocm_kernel_arch( int * d_arch )
{
#if defined( __HCC_ACCELERATOR__ )
*d_arch = OCM_ARCH__ ;
#else
*d_arch = 0 ;
#endif
}
/** Query what compute capability is actually launched to the device: */
int rocm_kernel_arch()
{
int * d_arch = 0 ;
rocmMalloc( (void **) & d_arch , sizeof(int) );
query_rocm_kernel_arch<<<1,1>>>( d_arch );
int arch = 0 ;
rocmMemcpy( & arch , d_arch , sizeof(int) , rocmMemcpyDefault );
rocmFree( d_arch );
return arch ;
}
bool rocm_launch_blocking()
{
const char * env = getenv("ROCM_LAUNCH_BLOCKING");
if (env == 0) return false;
return atoi(env);
}
}
#endif
// true device memory allocation, not visible from host
void * rocm_device_allocate(int size)
{
void * ptr;
hc::accelerator acc;
ptr = hc::am_alloc(size,acc,0);
return ptr;
}
// host pinned allocation
// flag = 1, non-coherent, host resident, but with gpu address space pointer
// flag = 2, coherent, host resident, but with host address space pointer
void * rocm_hostpinned_allocate(int size)
{
void * ptr;
hc::accelerator acc;
ptr = hc::am_alloc(size,acc,2);
return ptr;
}
// same free used by all rocm memory allocations
void rocm_device_free(void * ptr)
{
hc::am_free(ptr);
}
KOKKOS_INLINE_FUNCTION
void rocm_device_synchronize()
{
hc::accelerator_view av = hc::accelerator().get_default_view();
hc::completion_future fut = av.create_marker();
fut.wait();
}
void rocm_internal_error_throw( const char * name, const char * file, const int line )
{
#if 0
std::ostringstream out ;
out << name << " error( " << rocmGetErrorName(e) << "): " << rocmGetErrorString(e);
if (file) {
out << " " << file << ":" << line;
}
throw_runtime_exception( out.str() );
#endif
}
//----------------------------------------------------------------------------
// Some significant rocm device properties:
//
// rocmDeviceProp::name : Text label for device
// rocmDeviceProp::major : Device major number
// rocmDeviceProp::minor : Device minor number
// rocmDeviceProp::workgroupSize : number of threads per workgroup
// rocmDeviceProp::multiProcessorCount : number of multiprocessors
// rocmDeviceProp::sharedMemPerBlock : capacity of shared memory per wavefront
// rocmDeviceProp::totalConstMem : capacity of constant memory
// rocmDeviceProp::totalGlobalMem : capacity of global memory
// rocmDeviceProp::maxGridSize[3] : maximum grid size
//
//
// the data we have available from a ROCm accelerator
// std::wstring get_device_path()
// std::wstring get_description()
// unsigned int get_version()
// bool get_has_display()
// size_t get_dedicated_memory()
// bool get_supports_double_precision()
// bool get_supports_limited_double_precision()
// bool get_is_debug()
// bool get_supports_cpu_shared_memory()
// size_t get_max_tile_static_size()
// unsigned int get_cu_count()
// bool has_cpu_accessible_am()
struct rocmDeviceProp {
char name[256];
char description[256];
unsigned int version;
int device_type;
int device_ordinal;
int major;
int minor;
size_t totalGlobalMem;
size_t sharedMemPerWavefront;
int WavefrontSize;
int WorkgroupSize;
int MaxTileCount;
int maxThreadsPerWorkgroup;
int multiProcessorCount;
int canMapHostMemory;
bool APU;
};
void rocmGetDeviceProperties(struct rocmDeviceProp* devProp, int device)
{
std::wstring s;
int i,n;
hc::accelerator acc;
std::vector<hc::accelerator> accv = acc.get_all() ;
hc::accelerator a = accv[device];
s=a.get_device_path();
i = 0;
for(wchar_t c: s)
if((n=std::wctomb(&devProp->name[i],c))>0)
i+=n;
/* assume a CPU */
devProp->version = a.get_version();
devProp->major = a.get_version()>>16; // for CPU, these are meaningless
devProp->minor = a.get_version()&0xff;
devProp->device_ordinal = 0;
/* is this an AMD graphics card */
if((devProp->name[0]=='g') && (devProp->name[1]=='f')
&& (devProp->name[2]=='x')) {
/* for AMD cards, the name has the format gfxMmmO */
devProp->device_type = ((devProp->name[3]-0x30)<<16)
+ ((devProp->name[4]-0x30)<<8)
+ (devProp->name[5]-0x30);
devProp->device_ordinal = devProp->name[6]-0x30;
devProp->major = devProp->name[3]-0x30;
devProp->minor = devProp->name[5]-0x30;
}
s=a.get_description();
i = 0;
for(wchar_t c: s)
if((n=std::wctomb(&devProp->description[i],c))>0)
i+=n;
devProp->totalGlobalMem = a.get_dedicated_memory();
devProp->sharedMemPerWavefront = a.get_max_tile_static_size();
devProp->WavefrontSize = 64;
devProp->WorkgroupSize = 256; // preferred
devProp->MaxTileCount = 409600; // as defined in /opt/rocm/hcc-lc/include/hsa_new.h
devProp->maxThreadsPerWorkgroup = 1024;
devProp->multiProcessorCount = a.get_cu_count();
devProp->canMapHostMemory = a.get_supports_cpu_shared_memory();
// Kaveri has 64KB L2 per CU, 16KB L1, 64KB Vector Regs/SIMD, or 128 regs/thread
// GCN has 64KB LDS per CU
//Kaveri APU is 7:0:0
//Carrizo APU is 8:0:1
devProp->APU = (((devProp->major==7)&&(devProp->minor==0))|
((devProp->major==8)&&(devProp->minor==1)))?true:false;
}
namespace {
class ROCmInternalDevices {
public:
enum { MAXIMUM_DEVICE_COUNT = 64 };
struct rocmDeviceProp m_rocmProp[ MAXIMUM_DEVICE_COUNT ] ;
int m_rocmDevCount ;
ROCmInternalDevices();
static const ROCmInternalDevices & singleton();
};
ROCmInternalDevices::ROCmInternalDevices()
{
hc::accelerator acc;
std::vector<hc::accelerator> accv = acc.get_all() ;
m_rocmDevCount = accv.size();
if(m_rocmDevCount > MAXIMUM_DEVICE_COUNT) {
Kokkos::abort("Sorry, you have more GPUs per node than we thought anybody would ever have. Please report this to github.com/kokkos/kokkos.");
}
for ( int i = 0 ; i < m_rocmDevCount ; ++i ) {
rocmGetDeviceProperties( m_rocmProp + i , i );
}
}
const ROCmInternalDevices & ROCmInternalDevices::singleton()
{
static ROCmInternalDevices* self = nullptr;
if (!self) {
self = new ROCmInternalDevices();
}
return *self;
}
}
//----------------------------------------------------------------------------
class ROCmInternal {
private:
ROCmInternal( const ROCmInternal & );
ROCmInternal & operator = ( const ROCmInternal & );
public:
typedef Kokkos::Experimental::ROCm::size_type size_type ;
int m_rocmDev ;
int m_rocmArch ;
unsigned m_multiProcCount ;
unsigned m_maxWorkgroup ;
unsigned m_maxSharedWords ;
size_type m_scratchSpaceCount ;
size_type m_scratchFlagsCount ;
size_type * m_scratchSpace ;
size_type * m_scratchFlags ;
static int was_finalized;
static ROCmInternal & singleton();
int verify_is_initialized( const char * const label ) const ;
int is_initialized() const
{ return 0 != m_scratchSpace && 0 != m_scratchFlags ; }
void initialize( int rocm_device_id );
void finalize();
void print_configuration( std::ostream & ) const ;
~ROCmInternal();
ROCmInternal()
: m_rocmDev( -1 )
, m_rocmArch( -1 )
, m_multiProcCount( 0 )
, m_maxWorkgroup( 0 )
, m_maxSharedWords( 0 )
, m_scratchSpaceCount( 0 )
, m_scratchFlagsCount( 0 )
, m_scratchSpace( 0 )
, m_scratchFlags( 0 )
{}
size_type * scratch_space( const size_type size );
size_type * scratch_flags( const size_type size );
};
int ROCmInternal::was_finalized = 0;
//----------------------------------------------------------------------------
void ROCmInternal::print_configuration( std::ostream & s ) const
{
const ROCmInternalDevices & dev_info = ROCmInternalDevices::singleton();
#if defined( KOKKOS_ENABLE_ROCM )
s << "macro KOKKOS_ENABLE_ROCM : defined" << std::endl ;
#endif
#if defined( __hcc_version__ )
s << "macro __hcc_version__ = " << __hcc_version__
<< std::endl ;
#endif
for ( int i = 0 ; i < dev_info.m_rocmDevCount ; ++i ) {
s << "Kokkos::Experimental::ROCm[ " << i << " ] "
<< dev_info.m_rocmProp[i].name
<< " version " << (dev_info.m_rocmProp[i].major) << "." << dev_info.m_rocmProp[i].minor
<< ", Total Global Memory: " << human_memory_size(dev_info.m_rocmProp[i].totalGlobalMem)
<< ", Shared Memory per Wavefront: " << human_memory_size(dev_info.m_rocmProp[i].sharedMemPerWavefront);
if ( m_rocmDev == i ) s << " : Selected" ;
s << std::endl ;
}
}
//----------------------------------------------------------------------------
ROCmInternal::~ROCmInternal()
{
if ( m_scratchSpace ||
m_scratchFlags ) {
std::cerr << "Kokkos::Experimental::ROCm ERROR: Failed to call Kokkos::Experimental::ROCm::finalize()"
<< std::endl ;
std::cerr.flush();
}
m_rocmDev = -1 ;
m_rocmArch = -1 ;
m_multiProcCount = 0 ;
m_maxWorkgroup = 0 ;
m_maxSharedWords = 0 ;
m_scratchSpaceCount = 0 ;
m_scratchFlagsCount = 0 ;
m_scratchSpace = 0 ;
m_scratchFlags = 0 ;
}
int ROCmInternal::verify_is_initialized( const char * const label ) const
{
if ( m_rocmDev < 0 ) {
std::cerr << "Kokkos::Experimental::ROCm::" << label << " : ERROR device not initialized" << std::endl ;
}
return 0 <= m_rocmDev ;
}
ROCmInternal & ROCmInternal::singleton()
{
static ROCmInternal* self = nullptr ;
if (!self) {
self = new ROCmInternal();
}
return *self ;
}
void ROCmInternal::initialize( int rocm_device_id )
{
if ( was_finalized ) Kokkos::abort("Calling ROCm::initialize after ROCm::finalize is illegal\n");
if ( is_initialized() ) return;
enum { WordSize = sizeof(size_type) };
if ( ! HostSpace::execution_space::is_initialized() ) {
const std::string msg("ROCm::initialize ERROR : HostSpace::execution_space is not initialized");
throw_runtime_exception( msg );
}
const ROCmInternalDevices & dev_info = ROCmInternalDevices::singleton();
const bool ok_init = 0 == m_scratchSpace || 0 == m_scratchFlags ;
const bool ok_id = 1 <= rocm_device_id &&
rocm_device_id < dev_info.m_rocmDevCount ;
// Need at least a GPU device
const bool ok_dev = ok_id &&
( 1 <= dev_info.m_rocmProp[ rocm_device_id ].major &&
0 <= dev_info.m_rocmProp[ rocm_device_id ].minor );
if ( ok_init && ok_dev ) {
const struct rocmDeviceProp & rocmProp =
dev_info.m_rocmProp[ rocm_device_id ];
m_rocmDev = rocm_device_id ;
// rocmSetDevice( m_rocmDev ) );
Kokkos::Impl::rocm_device_synchronize();
/*
// Query what compute capability architecture a kernel executes:
m_rocmArch = rocm_kernel_arch();
if ( m_rocmArch != rocmProp.major * 100 + rocmProp.minor * 10 ) {
std::cerr << "Kokkos::Experimental::ROCm::initialize WARNING: running kernels compiled for compute capability "
<< ( m_rocmArch / 100 ) << "." << ( ( m_rocmArch % 100 ) / 10 )
<< " on device with compute capability "
<< rocmProp.major << "." << rocmProp.minor
<< " , this will likely reduce potential performance."
<< std::endl ;
}
*/
// number of multiprocessors
m_multiProcCount = rocmProp.multiProcessorCount ;
//----------------------------------
// Maximum number of wavefronts,
// at most one workgroup per thread in a workgroup for reduction.
m_maxSharedWords = rocmProp.sharedMemPerWavefront/ WordSize ;
//----------------------------------
// Maximum number of Workgroups:
m_maxWorkgroup = 5*rocmProp.multiProcessorCount; //TODO: confirm usage and value
//----------------------------------
// Multiblock reduction uses scratch flags for counters
// and scratch space for partial reduction values.
// Allocate some initial space. This will grow as needed.
{
const unsigned reduce_block_count = m_maxWorkgroup * Impl::ROCmTraits::WorkgroupSize ;
(void) scratch_flags( reduce_block_count * 2 * sizeof(size_type) );
(void) scratch_space( reduce_block_count * 16 * sizeof(size_type) );
}
//----------------------------------
}
else {
std::ostringstream msg ;
msg << "Kokkos::Experimental::ROCm::initialize(" << rocm_device_id << ") FAILED" ;
if ( ! ok_init ) {
msg << " : Already initialized" ;
}
if ( ! ok_id ) {
msg << " : Device identifier out of range "
<< "[0.." << (dev_info.m_rocmDevCount-1) << "]" ;
}
else if ( ! ok_dev ) {
msg << " : Device " ;
msg << dev_info.m_rocmProp[ rocm_device_id ].major ;
msg << "." ;
msg << dev_info.m_rocmProp[ rocm_device_id ].minor ;
msg << " Need at least a GPU" ;
msg << std::endl;
}
Kokkos::Impl::throw_runtime_exception( msg.str() );
}
// Init the array for used for arbitrarily sized atomics
Kokkos::Impl::init_lock_arrays_rocm_space();
// Kokkos::Impl::ROCmLockArraysStruct locks;
// locks.atomic = atomic_lock_array_rocm_space_ptr(false);
// locks.scratch = scratch_lock_array_rocm_space_ptr(false);
// locks.threadid = threadid_lock_array_rocm_space_ptr(false);
// rocmMemcpyToSymbol( kokkos_impl_rocm_lock_arrays , & locks , sizeof(ROCmLockArraysStruct) );
}
//----------------------------------------------------------------------------
typedef Kokkos::Experimental::ROCm::size_type ScratchGrain[ Impl::ROCmTraits::WorkgroupSize ] ;
enum { sizeScratchGrain = sizeof(ScratchGrain) };
void rocmMemset( Kokkos::Experimental::ROCm::size_type * ptr , Kokkos::Experimental::ROCm::size_type value , Kokkos::Experimental::ROCm::size_type size)
{
char * mptr = (char * ) ptr;
#if 0
parallel_for_each(hc::extent<1>(size),
[=, &ptr]
(hc::index<1> idx) __HC__
{
int i = idx[0];
ptr[i] = value;
}).wait();
#else
for (int i= 0; i<size ; i++)
{
mptr[i] = (char) value;
}
#endif
}
Kokkos::Experimental::ROCm::size_type *
ROCmInternal::scratch_flags( const Kokkos::Experimental::ROCm::size_type size )
{
if ( verify_is_initialized("scratch_flags") && m_scratchFlagsCount * sizeScratchGrain < size ) {
m_scratchFlagsCount = ( size + sizeScratchGrain - 1 ) / sizeScratchGrain ;
typedef Kokkos::Experimental::Impl::SharedAllocationRecord< Kokkos::HostSpace , void > Record ;
Record * const r = Record::allocate( Kokkos::HostSpace()
, "InternalScratchFlags"
, ( sizeScratchGrain * m_scratchFlagsCount ) );
Record::increment( r );
m_scratchFlags = reinterpret_cast<size_type *>( r->data() );
rocmMemset( m_scratchFlags , 0 , m_scratchFlagsCount * sizeScratchGrain );
}
return m_scratchFlags ;
}
Kokkos::Experimental::ROCm::size_type *
ROCmInternal::scratch_space( const Kokkos::Experimental::ROCm::size_type size )
{
if ( verify_is_initialized("scratch_space") && m_scratchSpaceCount * sizeScratchGrain < size ) {
m_scratchSpaceCount = ( size + sizeScratchGrain - 1 ) / sizeScratchGrain ;
typedef Kokkos::Experimental::Impl::SharedAllocationRecord< Kokkos::HostSpace , void > Record ;
Record * const r = Record::allocate( Kokkos::HostSpace()
, "InternalScratchSpace"
, ( sizeScratchGrain * m_scratchSpaceCount ) );
Record::increment( r );
m_scratchSpace = reinterpret_cast<size_type *>( r->data() );
}
return m_scratchSpace ;
}
//----------------------------------------------------------------------------
void ROCmInternal::finalize()
{
was_finalized = 1;
if ( 0 != m_scratchSpace || 0 != m_scratchFlags ) {
// atomic_lock_array_rocm_space_ptr(false);
// scratch_lock_array_rocm_space_ptr(false);
// threadid_lock_array_rocm_space_ptr(false);
typedef Kokkos::Experimental::Impl::SharedAllocationRecord< HostSpace > RecordROCm ;
typedef Kokkos::Experimental::Impl::SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace > RecordHost ;
RecordROCm::decrement( RecordROCm::get_record( m_scratchFlags ) );
RecordROCm::decrement( RecordROCm::get_record( m_scratchSpace ) );
m_rocmDev = -1 ;
m_multiProcCount = 0 ;
m_maxWorkgroup = 0 ;
m_maxSharedWords = 0 ;
m_scratchSpaceCount = 0 ;
m_scratchFlagsCount = 0 ;
m_scratchSpace = 0 ;
m_scratchFlags = 0 ;
}
}
//----------------------------------------------------------------------------
Kokkos::Experimental::ROCm::size_type rocm_internal_cu_count()
{ return ROCmInternal::singleton().m_multiProcCount ; }
Kokkos::Experimental::ROCm::size_type rocm_internal_maximum_extent_size()
{ return ROCmInternal::singleton().m_maxWorkgroup ; }
Kokkos::Experimental::ROCm::size_type rocm_internal_maximum_shared_words()
{ return ROCmInternal::singleton().m_maxSharedWords ; }
Kokkos::Experimental::ROCm::size_type * rocm_internal_scratch_space( const Kokkos::Experimental::ROCm::size_type size )
{ return ROCmInternal::singleton().scratch_space( size ); }
Kokkos::Experimental::ROCm::size_type * rocm_internal_scratch_flags( const Kokkos::Experimental::ROCm::size_type size )
{ return ROCmInternal::singleton().scratch_flags( size ); }
} // namespace Impl
} // namespace Kokkos
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Experimental {
//ROCm::size_type ROCm::detect_device_count()
//{ return Impl::ROCmInternalDevices::singleton().m_rocmDevCount ; }
int ROCm::concurrency() {
#if defined(KOKKOS_ARCH_KAVERI)
return 8*64*40; // 20480 kaveri
#else
return 32*8*40; // 81920 fiji and hawaii
#endif
}
int ROCm::is_initialized()
{ return Kokkos::Impl::ROCmInternal::singleton().is_initialized(); }
void ROCm::initialize( const ROCm::SelectDevice config )
{
Kokkos::Impl::ROCmInternal::singleton().initialize( config.rocm_device_id );
#if defined(KOKKOS_ENABLE_PROFILING)
Kokkos::Profiling::initialize();
#endif
}
#if 0
std::vector<unsigned>
ROCm::detect_device_arch()
{
const Impl::ROCmInternalDevices & s = Impl::ROCmInternalDevices::singleton();
std::vector<unsigned> output( s.m_rocmDevCount );
for ( int i = 0 ; i < s.m_rocmDevCount ; ++i ) {
output[i] = s.m_rocmProp[i].major * 100 + s.m_rocmProp[i].minor ;
}
return output ;
}
ROCm::size_type ROCm::device_arch()
{
return 1 ;
}
#endif
void ROCm::finalize()
{
Kokkos::Impl::ROCmInternal::singleton().finalize();
#if defined(KOKKOS_ENABLE_PROFILING)
Kokkos::Profiling::finalize();
#endif
}
ROCm::ROCm()
: m_device( Kokkos::Impl::ROCmInternal::singleton().m_rocmDev )
{
Kokkos::Impl::ROCmInternal::singleton().verify_is_initialized( "ROCm instance constructor" );
}
bool ROCm::isAPU(int device) {
const Kokkos::Impl::ROCmInternalDevices & dev_info =
Kokkos::Impl::ROCmInternalDevices::singleton();
return (dev_info.m_rocmProp[device].APU);
}
bool ROCm::isAPU() {
return ROCm::isAPU(rocm_device());
}
//ROCm::ROCm( const int instance_id )
// : m_device( Impl::ROCmInternal::singleton().m_rocmDev )
//{}
void ROCm::print_configuration( std::ostream & s , const bool )
{ Kokkos::Impl::ROCmInternal::singleton().print_configuration( s ); }
bool ROCm::sleep() { return false ; }
bool ROCm::wake() { return true ; }
void ROCm::fence()
{
Kokkos::Impl::rocm_device_synchronize();
}
const char* ROCm::name() { return "ROCm"; }
} // namespace Experimental
} // namespace Kokkos
#endif // KOKKOS_ENABLE_ROCM
//----------------------------------------------------------------------------

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/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#include <type_traits>
#include <Kokkos_Macros.hpp>
#if !defined( KOKKOS_ROCM_INVOKE_H )
#define KOKKOS_ROCM_INVOKE_H
namespace Kokkos {
namespace Impl {
template<class Tag, class F, class... Ts, typename std::enable_if<(!std::is_void<Tag>()), int>::type = 0>
KOKKOS_INLINE_FUNCTION void rocm_invoke(F&& f, Ts&&... xs)
{
f(Tag(), static_cast<Ts&&>(xs)...);
}
template<class Tag, class F, class... Ts, typename std::enable_if<(std::is_void<Tag>()), int>::type = 0>
KOKKOS_INLINE_FUNCTION void rocm_invoke(F&& f, Ts&&... xs)
{
f(static_cast<Ts&&>(xs)...);
}
template<class F, class Tag=void>
struct rocm_invoke_fn
{
F* f;
rocm_invoke_fn(F& f_) : f(&f_)
{}
template<class... Ts>
KOKKOS_INLINE_FUNCTION void operator()(Ts&&... xs) const
{
rocm_invoke<Tag>(*f, static_cast<Ts&&>(xs)...);
}
};
template<class Tag, class F>
KOKKOS_INLINE_FUNCTION rocm_invoke_fn<F, Tag> make_rocm_invoke_fn(F& f)
{
return {f};
}
template<class T>
KOKKOS_INLINE_FUNCTION T& rocm_unwrap(T& x)
{
return x;
}
template<class T>
KOKKOS_INLINE_FUNCTION T& rocm_unwrap(std::reference_wrapper<T> x)
{
return x;
}
template<class F, class T>
struct rocm_capture_fn
{
F f;
T data;
KOKKOS_INLINE_FUNCTION rocm_capture_fn(F f_, T x)
: f(f_), data(x)
{}
template<class... Ts>
KOKKOS_INLINE_FUNCTION void operator()(Ts&&... xs) const
{
f(rocm_unwrap(data), static_cast<Ts&&>(xs)...);
}
};
template<class F, class T>
KOKKOS_INLINE_FUNCTION rocm_capture_fn<F, T> rocm_capture(F f, T x)
{
return {f, x};
}
template<class F, class T, class U, class... Ts>
KOKKOS_INLINE_FUNCTION auto rocm_capture(F f, T x, U y, Ts... xs) -> decltype(rocm_capture(rocm_capture(f, x), y, xs...))
{
return rocm_capture(rocm_capture(f, x), y, xs...);
}
struct rocm_apply_op
{
template<class F, class... Ts>
KOKKOS_INLINE_FUNCTION void operator()(F&& f, Ts&&... xs) const
{
f(static_cast<Ts&&>(xs)...);
}
};
}}
#endif

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/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#if !defined( KOKKOS_ROCM_JOIN_H )
#define KOKKOS_ROCM_JOIN_H
namespace Kokkos {
namespace Impl {
// Adaptor to use ValueJoin with standard algorithms
template<class Joiner, class F>
struct join_operator
{
const F* fp;
template<class T, class U>
T operator()(T x, const U& y) const
{
Joiner::join(*fp, &x, &y);
return x;
}
};
template<class Joiner, class F>
join_operator<Joiner, F> make_join_operator(const F& f)
{
return join_operator<Joiner, F>{&f};
}
}}
#endif

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/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
///////////////////////////////////////////////////////////////////////////////
// AMP REDUCE
//////////////////////////////////////////////////////////////////////////////
#if !defined( KOKKOS_ROCM_AMP_REDUCE_INL )
#define KOKKOS_ROCM_AMP_REDUCE_INL
#include <iostream>
#include <algorithm>
#include <numeric>
#include <cmath>
#include <type_traits>
#include <ROCm/Kokkos_ROCm_Tile.hpp>
#include <ROCm/Kokkos_ROCm_Invoke.hpp>
#include <ROCm/Kokkos_ROCm_Join.hpp>
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
namespace Kokkos {
namespace Impl {
template<class T>
T* reduce_value(T* x, std::true_type) [[hc]]
{
return x;
}
template<class T>
T& reduce_value(T* x, std::false_type) [[hc]]
{
return *x;
}
#if KOKKOS_ROCM_HAS_WORKAROUNDS
struct always_true
{
template<class... Ts>
bool operator()(Ts&&...) const
{
return true;
}
};
#endif
template< class Tag, class F, class ReducerType, class Invoker, class T >
void reduce_enqueue(
const int szElements, // size of the extent
const F & f,
const ReducerType& reducer,
Invoker invoke,
T * const output_result,
int const output_length,
const int team_size=64,
const int vector_size=1,
int const shared_size=0)
{
using namespace hc ;
typedef Kokkos::Impl::if_c< std::is_same<InvalidType,ReducerType>::value, F, ReducerType> ReducerConditional;
typedef typename ReducerConditional::type ReducerTypeFwd;
typedef Kokkos::Impl::FunctorValueTraits< ReducerTypeFwd , Tag > ValueTraits ;
typedef Kokkos::Impl::FunctorValueInit< ReducerTypeFwd , Tag > ValueInit ;
typedef Kokkos::Impl::FunctorValueJoin< ReducerTypeFwd , Tag > ValueJoin ;
typedef Kokkos::Impl::FunctorFinal< ReducerTypeFwd , Tag > ValueFinal ;
typedef typename ValueTraits::pointer_type pointer_type ;
typedef typename ValueTraits::reference_type reference_type ;
if (output_length < 1) return;
assert(output_result != nullptr);
const auto td = get_tile_desc<T>(szElements,output_length,team_size,vector_size, shared_size);
// allocate host and device memory for the results from each team
std::vector<T> result_cpu(td.num_tiles*output_length);
hc::array<T> result(td.num_tiles*output_length);
auto fut = tile_for<T[]>(td, [=,&result](hc::tiled_index<1> t_idx, tile_buffer<T[]> buffer) [[hc]]
{
const auto local = t_idx.local[0];
const auto global = t_idx.global[0];
const auto tile = t_idx.tile[0];
buffer.action_at(local, [&](T* state)
{
ValueInit::init(ReducerConditional::select(f, reducer), state);
invoke(make_rocm_invoke_fn<Tag>(f), t_idx, td, reduce_value(state, std::is_pointer<reference_type>()));
});
t_idx.barrier.wait();
// Reduce within a tile using multiple threads.
// even though buffer.size is always 64, the value 64 must be hard coded below
// due to a compiler bug
// for(std::size_t s = 1; s < buffer.size(); s *= 2)
for(std::size_t s = 1; s < 64; s *= 2)
{
const std::size_t index = 2 * s * local;
// if (index < buffer.size())
if (index < 64)
{
buffer.action_at(index, index + s, [&](T* x, T* y)
{
ValueJoin::join(ReducerConditional::select(f, reducer), x, y);
});
}
t_idx.barrier.wait();
}
// Store the tile result in the global memory.
if (local == 0)
{
#if KOKKOS_ROCM_HAS_WORKAROUNDS
// Workaround for assigning from LDS memory: std::copy should work
// directly
buffer.action_at(0, [&](T* x)
{
#if ROCM15
// new ROCM 15 address space changes aren't implemented in std algorithms yet
auto * src = reinterpret_cast<char *>(x);
auto * dest = reinterpret_cast<char *>(result.data()+tile*output_length);
for(int i=0; i<sizeof(T);i++) dest[i] = src[i];
#else
// Workaround: copy_if used to avoid memmove
std::copy_if(x, x+output_length, result.data()+tile*output_length, always_true{} );
#endif
});
#else
std::copy(buffer, buffer+output_length, result.data()+tile*output_length);
#endif
}
});
ValueInit::init(ReducerConditional::select(f, reducer), output_result);
fut.wait();
copy(result,result_cpu.data());
for(std::size_t i=0;i<td.num_tiles;i++)
ValueJoin::join(ReducerConditional::select(f, reducer), output_result, result_cpu.data()+i*output_length);
ValueFinal::final( ReducerConditional::select(f, reducer) , output_result );
}
}} //end of namespace Kokkos::Impl
#endif /* #if !defined( KOKKOS_ROCM_AMP_REDUCE_INL ) */

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/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#ifndef KOKKOS_ROCM_REDUCESCAN_HPP
#define KOKKOS_ROCM_REDUCESCAN_HPP
#include <Kokkos_Macros.hpp>
/* only compile this file if ROCM is enabled for Kokkos */
#if defined( __HCC__ ) && defined( KOKKOS_ENABLE_ROCM )
//#include <utility>
#include <Kokkos_Parallel.hpp>
#include <impl/Kokkos_FunctorAdapter.hpp>
#include <impl/Kokkos_Error.hpp>
#include <ROCm/Kokkos_ROCm_Vectorization.hpp>
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Impl {
//----------------------------------------------------------------------------
template< typename T >
KOKKOS_INLINE_FUNCTION
void rocm_shfl( T & out , T const & in , int lane ,
typename std::enable_if< sizeof(int) == sizeof(T) , int >::type width )
{
*reinterpret_cast<int*>(&out) =
__shfl( *reinterpret_cast<int const *>(&in) , lane , width );
}
template< typename T >
KOKKOS_INLINE_FUNCTION
void rocm_shfl( T & out , T const & in , int lane ,
typename std::enable_if
< ( sizeof(int) < sizeof(T) ) && ( 0 == ( sizeof(T) % sizeof(int) ) )
, int >::type width )
{
enum : int { N = sizeof(T) / sizeof(int) };
for ( int i = 0 ; i < N ; ++i ) {
reinterpret_cast<int*>(&out)[i] =
__shfl( reinterpret_cast<int const *>(&in)[i] , lane , width );
}
}
//----------------------------------------------------------------------------
template< typename T >
KOKKOS_INLINE_FUNCTION
void rocm_shfl_down( T & out , T const & in , int delta ,
typename std::enable_if< sizeof(int) == sizeof(T) , int >::type width )
{
*reinterpret_cast<int*>(&out) =
__shfl_down( *reinterpret_cast<int const *>(&in) , delta , width );
}
template< typename T >
KOKKOS_INLINE_FUNCTION
void rocm_shfl_down( T & out , T const & in , int delta ,
typename std::enable_if
< ( sizeof(int) < sizeof(T) ) && ( 0 == ( sizeof(T) % sizeof(int) ) )
, int >::type width )
{
enum : int { N = sizeof(T) / sizeof(int) };
for ( int i = 0 ; i < N ; ++i ) {
reinterpret_cast<int*>(&out)[i] =
__shfl_down( reinterpret_cast<int const *>(&in)[i] , delta , width );
}
}
//----------------------------------------------------------------------------
template< typename T >
KOKKOS_INLINE_FUNCTION
void rocm_shfl_up( T & out , T const & in , int delta ,
typename std::enable_if< sizeof(int) == sizeof(T) , int >::type width )
{
*reinterpret_cast<int*>(&out) =
__shfl_up( *reinterpret_cast<int const *>(&in) , delta , width );
}
template< typename T >
KOKKOS_INLINE_FUNCTION
void rocm_shfl_up( T & out , T const & in , int delta ,
typename std::enable_if
< ( sizeof(int) < sizeof(T) ) && ( 0 == ( sizeof(T) % sizeof(int) ) )
, int >::type width )
{
enum : int { N = sizeof(T) / sizeof(int) };
for ( int i = 0 ; i < N ; ++i ) {
reinterpret_cast<int*>(&out)[i] =
__shfl_up( reinterpret_cast<int const *>(&in)[i] , delta , width );
}
}
#if 0
//----------------------------------------------------------------------------
/** \brief Reduce within a workgroup over team.vector_length(), the "vector" dimension.
*
* This will be called within a nested, intra-team parallel operation.
* Use shuffle operations to avoid conflicts with shared memory usage.
*
* Requires:
* team.vector_length() is power of 2
* team.vector_length() <= 32 (one workgroup)
*
* Cannot use "butterfly" pattern because floating point
* addition is non-associative. Therefore, must broadcast
* the final result.
*/
template< class Reducer >
KOKKOS_INLINE_FUNCTION
void rocm_intra_workgroup_vector_reduce( Reducer const & reducer )
{
static_assert(
std::is_reference< typename Reducer::reference_type >::value , "" );
if ( 1 < team.vector_length() ) {
typename Reducer::value_type tmp ;
for ( int i = team.vector_length() ; ( i >>= 1 ) ; ) {
rocm_shfl_down( tmp , reducer.reference() , i , team.vector_length() );
if ( team.vector_rank() < i ) { reducer.join( reducer.data() , & tmp ); }
}
// Broadcast from root "lane" to all other "lanes"
rocm_shfl( reducer.reference() , reducer.reference() , 0 , team.vector_length() );
}
}
/** \brief Inclusive scan over team.vector_length(), the "vector" dimension.
*
* This will be called within a nested, intra-team parallel operation.
* Use shuffle operations to avoid conflicts with shared memory usage.
*
* Algorithm is concurrent bottom-up reductions in triangular pattern
* where each ROCM thread is the root of a reduction tree from the
* zeroth ROCM thread to itself.
*
* Requires:
* team.vector_length() is power of 2
* team.vector_length() <= 32 (one workgroup)
*/
template< typename ValueType >
KOKKOS_INLINE_FUNCTION
void rocm_intra_workgroup_vector_inclusive_scan( ValueType & local )
{
ValueType tmp ;
// Bottom up:
// [t] += [t-1] if t >= 1
// [t] += [t-2] if t >= 2
// [t] += [t-4] if t >= 4
// ...
for ( int i = 1 ; i < team.vector_length() ; i <<= 1 ) {
rocm_shfl_up( tmp , local , i , team.vector_length() );
if ( i <= team.vector_rank() ) { local += tmp ; }
}
}
#endif
//----------------------------------------------------------------------------
/*
* Algorithmic constraints:
* (a) threads with same team.team_rank() have same value
* (b) team.vector_length() == power of two
* (c) blockDim.z == 1
*/
template< class ValueType , class JoinOp>
KOKKOS_INLINE_FUNCTION
void rocm_intra_workgroup_reduction( const ROCmTeamMember& team,
ValueType& result,
const JoinOp& join) {
unsigned int shift = 1;
int max_active_thread = team.team_size();
//Reduce over values from threads with different team.team_rank()
while(team.vector_length() * shift < 32 ) {
const ValueType tmp = shfl_down(result, team.vector_length()*shift,32u);
//Only join if upper thread is active (this allows non power of two for team.team_size()
if(team.team_rank() + shift < max_active_thread)
join(result , tmp);
shift*=2;
}
result = shfl(result,0,32);
}
template< class ValueType , class JoinOp>
KOKKOS_INLINE_FUNCTION
void rocm_inter_workgroup_reduction( const ROCmTeamMember& team,
ValueType& value,
const JoinOp& join) {
#define STEP_WIDTH 4
tile_static ValueType sh_result[256];
int max_active_thread = team.team_size();
ValueType* result = (ValueType*) & sh_result;
const unsigned step = 256 / team.vector_length();
unsigned shift = STEP_WIDTH;
const int id = team.team_rank()%step==0?team.team_rank()/step:65000;
if(id < STEP_WIDTH ) {
result[id] = value;
}
team.team_barrier();
while (shift<=max_active_thread/step) {
if(shift<=id && shift+STEP_WIDTH>id && team.vector_rank()==0) {
join(result[id%STEP_WIDTH],value);
}
team.team_barrier();
shift+=STEP_WIDTH;
}
value = result[0];
for(int i = 1; (i*step<max_active_thread) && i<STEP_WIDTH; i++)
join(value,result[i]);
}
#if 0
template< class ValueType , class JoinOp>
KOKKOS_INLINE_FUNCTION
void rocm_intra_block_reduction( ROCmTeamMember& team,
ValueType& value,
const JoinOp& join,
const int max_active_thread) {
rocm_intra_workgroup_reduction(team,value,join,max_active_thread);
rocm_inter_workgroup_reduction(team,value,join,max_active_thread);
}
template< class FunctorType , class JoinOp , class ArgTag = void >
KOKKOS_INLINE_FUNCTION
bool rocm_inter_block_reduction( ROCmTeamMember& team,
typename FunctorValueTraits< FunctorType , ArgTag >::reference_type value,
typename FunctorValueTraits< FunctorType , ArgTag >::reference_type neutral,
const JoinOp& join,
ROCm::size_type * const m_scratch_space,
typename FunctorValueTraits< FunctorType , ArgTag >::pointer_type const result,
ROCm::size_type * const m_scratch_flags,
const int max_active_thread) {
#ifdef __ROCM_ARCH__
typedef typename FunctorValueTraits< FunctorType , ArgTag >::pointer_type pointer_type;
typedef typename FunctorValueTraits< FunctorType , ArgTag >::value_type value_type;
//Do the intra-block reduction with shfl operations and static shared memory
rocm_intra_block_reduction(value,join,max_active_thread);
const unsigned id = team.team_rank()*team.vector_length() + team.vector_rank();
//One thread in the block writes block result to global scratch_memory
if(id == 0 ) {
pointer_type global = ((pointer_type) m_scratch_space) + blockIdx.x;
*global = value;
}
//One workgroup of last block performs inter block reduction through loading the block values from global scratch_memory
bool last_block = false;
team.team_barrier();
if ( id < 32 ) {
ROCm::size_type count;
//Figure out whether this is the last block
if(id == 0)
count = Kokkos::atomic_fetch_add(m_scratch_flags,1);
count = Kokkos::shfl(count,0,32);
//Last block does the inter block reduction
if( count == gridDim.x - 1) {
//set flag back to zero
if(id == 0)
*m_scratch_flags = 0;
last_block = true;
value = neutral;
pointer_type const volatile global = (pointer_type) m_scratch_space ;
//Reduce all global values with splitting work over threads in one workgroup
const int step_size = team.vector_length()*team.team_size() < 32 ? team.vector_length()*team.team_size() : 32;
for(int i=id; i<gridDim.x; i+=step_size) {
value_type tmp = global[i];
join(value, tmp);
}
//Perform shfl reductions within the workgroup only join if contribution is valid (allows gridDim.x non power of two and <32)
if (team.vector_length()*team.team_size() > 1) {
value_type tmp = Kokkos::shfl_down(value, 1,32);
if( id + 1 < gridDim.x )
join(value, tmp);
}
if (team.vector_length()*team.team_size() > 2) {
value_type tmp = Kokkos::shfl_down(value, 2,32);
if( id + 2 < gridDim.x )
join(value, tmp);
}
if (team.vector_length()*team.team_size() > 4) {
value_type tmp = Kokkos::shfl_down(value, 4,32);
if( id + 4 < gridDim.x )
join(value, tmp);
}
if (team.vector_length()*team.team_size() > 8) {
value_type tmp = Kokkos::shfl_down(value, 8,32);
if( id + 8 < gridDim.x )
join(value, tmp);
}
if (team.vector_length()*team.team_size() > 16) {
value_type tmp = Kokkos::shfl_down(value, 16,32);
if( id + 16 < gridDim.x )
join(value, tmp);
}
}
}
//The last block has in its thread=0 the global reduction value through "value"
return last_block;
#else
return true;
#endif
}
#endif
#if 0
//----------------------------------------------------------------------------
// See section B.17 of ROCm C Programming Guide Version 3.2
// for discussion of
// __launch_bounds__(maxThreadsPerBlock,minBlocksPerMultiprocessor)
// function qualifier which could be used to improve performance.
//----------------------------------------------------------------------------
// Maximize shared memory and minimize L1 cache:
// rocmFuncSetCacheConfig(MyKernel, rocmFuncCachePreferShared );
// For 2.0 capability: 48 KB shared and 16 KB L1
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
/*
* Algorithmic constraints:
* (a) team.team_size() is a power of two
* (b) team.team_size() <= 512
* (c) team.vector_length() == blockDim.z == 1
*/
template< bool DoScan , class FunctorType , class ArgTag >
KOKKOS_INLINE_FUNCTION
void rocm_intra_block_reduce_scan( const FunctorType & functor ,
const typename FunctorValueTraits< FunctorType , ArgTag >::pointer_type base_data )
{
typedef FunctorValueTraits< FunctorType , ArgTag > ValueTraits ;
typedef FunctorValueJoin< FunctorType , ArgTag > ValueJoin ;
typedef typename ValueTraits::pointer_type pointer_type ;
const unsigned value_count = ValueTraits::value_count( functor );
const unsigned BlockSizeMask = team.team_size() - 1 ;
// Must have power of two thread count
if ( BlockSizeMask & team.team_size() ) { Kokkos::abort("ROCm::rocm_intra_block_scan requires power-of-two blockDim"); }
#define BLOCK_REDUCE_STEP( R , TD , S ) \
if ( ! ( R & ((1<<(S+1))-1) ) ) { ValueJoin::join( functor , TD , (TD - (value_count<<S)) ); }
#define BLOCK_SCAN_STEP( TD , N , S ) \
if ( N == (1<<S) ) { ValueJoin::join( functor , TD , (TD - (value_count<<S))); }
const unsigned rtid_intra = team.team_rank() ^ BlockSizeMask ;
const pointer_type tdata_intra = base_data + value_count * team.team_rank() ;
{ // Intra-workgroup reduction:
BLOCK_REDUCE_STEP(rtid_intra,tdata_intra,0)
BLOCK_REDUCE_STEP(rtid_intra,tdata_intra,1)
BLOCK_REDUCE_STEP(rtid_intra,tdata_intra,2)
BLOCK_REDUCE_STEP(rtid_intra,tdata_intra,3)
BLOCK_REDUCE_STEP(rtid_intra,tdata_intra,4)
}
team.team_barrier(); // Wait for all workgroups to reduce
{ // Inter-workgroup reduce-scan by a single workgroup to avoid extra synchronizations
const unsigned rtid_inter = ( team.team_rank() ^ BlockSizeMask ) << ROCmTraits::WarpIndexShift ;
if ( rtid_inter < team.team_size() ) {
const pointer_type tdata_inter = base_data + value_count * ( rtid_inter ^ BlockSizeMask );
if ( (1<<5) < BlockSizeMask ) { BLOCK_REDUCE_STEP(rtid_inter,tdata_inter,5) }
if ( (1<<6) < BlockSizeMask ) { __threadfence_block(); BLOCK_REDUCE_STEP(rtid_inter,tdata_inter,6) }
if ( (1<<7) < BlockSizeMask ) { __threadfence_block(); BLOCK_REDUCE_STEP(rtid_inter,tdata_inter,7) }
if ( (1<<8) < BlockSizeMask ) { __threadfence_block(); BLOCK_REDUCE_STEP(rtid_inter,tdata_inter,8) }
if ( DoScan ) {
int n = ( rtid_inter & 32 ) ? 32 : (
( rtid_inter & 64 ) ? 64 : (
( rtid_inter & 128 ) ? 128 : (
( rtid_inter & 256 ) ? 256 : 0 )));
if ( ! ( rtid_inter + n < team.team_size() ) ) n = 0 ;
__threadfence_block(); BLOCK_SCAN_STEP(tdata_inter,n,8)
__threadfence_block(); BLOCK_SCAN_STEP(tdata_inter,n,7)
__threadfence_block(); BLOCK_SCAN_STEP(tdata_inter,n,6)
__threadfence_block(); BLOCK_SCAN_STEP(tdata_inter,n,5)
}
}
}
team.team_barrier(); // Wait for inter-workgroup reduce-scan to complete
if ( DoScan ) {
int n = ( rtid_intra & 1 ) ? 1 : (
( rtid_intra & 2 ) ? 2 : (
( rtid_intra & 4 ) ? 4 : (
( rtid_intra & 8 ) ? 8 : (
( rtid_intra & 16 ) ? 16 : 0 ))));
if ( ! ( rtid_intra + n < team.team_size() ) ) n = 0 ;
#ifdef KOKKOS_IMPL_ROCM_CLANG_WORKAROUND
BLOCK_SCAN_STEP(tdata_intra,n,4) team.team_barrier();//__threadfence_block();
BLOCK_SCAN_STEP(tdata_intra,n,3) team.team_barrier();//__threadfence_block();
BLOCK_SCAN_STEP(tdata_intra,n,2) team.team_barrier();//__threadfence_block();
BLOCK_SCAN_STEP(tdata_intra,n,1) team.team_barrier();//__threadfence_block();
BLOCK_SCAN_STEP(tdata_intra,n,0) team.team_barrier();
#else
BLOCK_SCAN_STEP(tdata_intra,n,4) __threadfence_block();
BLOCK_SCAN_STEP(tdata_intra,n,3) __threadfence_block();
BLOCK_SCAN_STEP(tdata_intra,n,2) __threadfence_block();
BLOCK_SCAN_STEP(tdata_intra,n,1) __threadfence_block();
BLOCK_SCAN_STEP(tdata_intra,n,0) __threadfence_block();
#endif
}
#undef BLOCK_SCAN_STEP
#undef BLOCK_REDUCE_STEP
}
//----------------------------------------------------------------------------
/**\brief Input value-per-thread starting at 'shared_data'.
* Reduction value at last thread's location.
*
* If 'DoScan' then write blocks' scan values and block-groups' scan values.
*
* Global reduce result is in the last threads' 'shared_data' location.
*/
template< bool DoScan , class FunctorType , class ArgTag >
KOKKOS_INLINE_FUNCTION
bool rocm_single_inter_block_reduce_scan( const FunctorType & functor ,
const ROCm::size_type block_id ,
const ROCm::size_type block_count ,
ROCm::size_type * const shared_data ,
ROCm::size_type * const global_data ,
ROCm::size_type * const global_flags )
{
typedef ROCm::size_type size_type ;
typedef FunctorValueTraits< FunctorType , ArgTag > ValueTraits ;
typedef FunctorValueJoin< FunctorType , ArgTag > ValueJoin ;
typedef FunctorValueInit< FunctorType , ArgTag > ValueInit ;
typedef FunctorValueOps< FunctorType , ArgTag > ValueOps ;
typedef typename ValueTraits::pointer_type pointer_type ;
typedef typename ValueTraits::reference_type reference_type ;
typedef typename ValueTraits::value_type value_type ;
// '__ffs' = position of the least significant bit set to 1.
// 'team.team_size()' is guaranteed to be a power of two so this
// is the integral shift value that can replace an integral divide.
const unsigned BlockSizeShift = __ffs( team.team_size() ) - 1 ;
const unsigned BlockSizeMask = team.team_size() - 1 ;
// Must have power of two thread count
if ( BlockSizeMask & team.team_size() ) { Kokkos::abort("ROCm::rocm_single_inter_block_reduce_scan requires power-of-two blockDim"); }
const integral_nonzero_constant< size_type , ValueTraits::StaticValueSize / sizeof(size_type) >
word_count( ValueTraits::value_size( functor ) / sizeof(size_type) );
// Reduce the accumulation for the entire block.
rocm_intra_block_reduce_scan<false,FunctorType,ArgTag>( functor , pointer_type(shared_data) );
{
// Write accumulation total to global scratch space.
// Accumulation total is the last thread's data.
size_type * const shared = shared_data + word_count.value * BlockSizeMask ;
size_type * const global = global_data + word_count.value * block_id ;
#if (__ROCM_ARCH__ < 500)
for ( size_type i = team.team_rank() ; i < word_count.value ; i += team.team_size() ) { global[i] = shared[i] ; }
#else
for ( size_type i = 0 ; i < word_count.value ; i += 1 ) { global[i] = shared[i] ; }
#endif
}
// Contributing blocks note that their contribution has been completed via an atomic-increment flag
// If this block is not the last block to contribute to this group then the block is done.
team.team_barrier();
const bool is_last_block =
! team.team_reduce( team.team_rank() ? 0 : ( 1 + atomicInc( global_flags , block_count - 1 ) < block_count ) ,Impl::JoinAdd<ValueType>());
if ( is_last_block ) {
const size_type b = ( long(block_count) * long(team.team_rank()) ) >> BlockSizeShift ;
const size_type e = ( long(block_count) * long( team.team_rank() + 1 ) ) >> BlockSizeShift ;
{
void * const shared_ptr = shared_data + word_count.value * team.team_rank() ;
reference_type shared_value = ValueInit::init( functor , shared_ptr );
for ( size_type i = b ; i < e ; ++i ) {
ValueJoin::join( functor , shared_ptr , global_data + word_count.value * i );
}
}
rocm_intra_block_reduce_scan<DoScan,FunctorType,ArgTag>( functor , pointer_type(shared_data) );
if ( DoScan ) {
size_type * const shared_value = shared_data + word_count.value * ( team.team_rank() ? team.team_rank() - 1 : team.team_size() );
if ( ! team.team_rank() ) { ValueInit::init( functor , shared_value ); }
// Join previous inclusive scan value to each member
for ( size_type i = b ; i < e ; ++i ) {
size_type * const global_value = global_data + word_count.value * i ;
ValueJoin::join( functor , shared_value , global_value );
ValueOps ::copy( functor , global_value , shared_value );
}
}
}
return is_last_block ;
}
// Size in bytes required for inter block reduce or scan
template< bool DoScan , class FunctorType , class ArgTag >
inline
unsigned rocm_single_inter_block_reduce_scan_shmem( const FunctorType & functor , const unsigned BlockSize )
{
return ( BlockSize + 2 ) * Impl::FunctorValueTraits< FunctorType , ArgTag >::value_size( functor );
}
#endif
} // namespace Impl
} // namespace Kokkos
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
#endif /* #if defined( __ROCMCC__ ) */
#endif /* KOKKOS_ROCM_REDUCESCAN_HPP */

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@ -0,0 +1,157 @@
/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#include <ROCm/Kokkos_ROCm_Invoke.hpp>
#include <ROCm/Kokkos_ROCm_Join.hpp>
namespace Kokkos {
namespace Impl {
template< class Tag, class F, class TransformIndex>
void scan_enqueue(
const int len,
const F & f,
TransformIndex transform_index)
{
typedef Kokkos::Impl::FunctorValueTraits< F, Tag> ValueTraits;
typedef Kokkos::Impl::FunctorValueInit< F, Tag> ValueInit;
typedef Kokkos::Impl::FunctorValueJoin< F, Tag> ValueJoin;
typedef Kokkos::Impl::FunctorValueOps< F, Tag> ValueOps;
typedef typename ValueTraits::value_type value_type;
typedef typename ValueTraits::pointer_type pointer_type;
typedef typename ValueTraits::reference_type reference_type;
const auto td = get_tile_desc<value_type>(len);
std::vector<value_type> result_cpu(td.num_tiles);
hc::array<value_type> result(td.num_tiles);
hc::array<value_type> scratch(len);
tile_for<value_type>(td, [&,len,td](hc::tiled_index<1> t_idx, tile_buffer<value_type> buffer) [[hc]]
{
const auto local = t_idx.local[0];
const auto global = t_idx.global[0];
const auto tile = t_idx.tile[0];
// Join tile buffer elements
const auto join = [&](std::size_t i, std::size_t j)
{
buffer.action_at(i, j, [&](value_type& x, const value_type& y)
{
ValueJoin::join(f, &x, &y);
});
};
// Copy into tile
buffer.action_at(local, [&](value_type& state)
{
ValueInit::init(f, &state);
if (global < len) rocm_invoke<Tag>(f, transform_index(t_idx, td.tile_size, td.num_tiles), state, false);
});
t_idx.barrier.wait();
// Up sweep phase
for(std::size_t d=1;d<buffer.size();d*=2)
{
auto d2 = 2*d;
auto i = local*d2;
if(i<len)
{
auto j = i + d - 1;
auto k = i + d2 - 1;
// join(k, j); // no longer needed with ROCm 1.6
ValueJoin::join(f, &buffer[k], &buffer[j]);
}
}
t_idx.barrier.wait();
result[tile] = buffer[buffer.size()-1];
buffer[buffer.size()-1] = 0;
// Down sweep phase
for(std::size_t d=buffer.size()/2;d>0;d/=2)
{
auto d2 = 2*d;
auto i = local*d2;
if(i<len)
{
auto j = i + d - 1;
auto k = i + d2 - 1;
auto t = buffer[k];
// join(k, j); // no longer needed with ROCm 1.6
ValueJoin::join(f, &buffer[k], &buffer[j]);
buffer[j] = t;
}
t_idx.barrier.wait();
}
// Copy tiles into global memory
if (global < len) scratch[global] = buffer[local];
}).wait();
copy(result,result_cpu.data());
// The std::partial_sum was segfaulting, despite that this is cpu code.
// if(td.num_tiles>1)
// std::partial_sum(result_cpu.data(), result_cpu.data()+(td.num_tiles-1)*sizeof(value_type), result_cpu.data(), make_join_operator<ValueJoin>(f));
// use this implementation instead.
for(int i=1; i<td.num_tiles; i++)
ValueJoin::join(f, &result_cpu[i], &result_cpu[i-1]);
copy(result_cpu.data(),result);
hc::parallel_for_each(hc::extent<1>(len).tile(td.tile_size), [&,len,td](hc::tiled_index<1> t_idx) [[hc]]
{
// const auto local = t_idx.local[0];
const auto global = t_idx.global[0];
const auto tile = t_idx.tile[0];
if (global < len)
{
auto final_state = scratch[global];
// the join is locking up, at least with 1.6
if (tile != 0) final_state += result[tile-1];
// if (tile != 0) ValueJoin::join(f, &final_state, &result[tile-1]);
rocm_invoke<Tag>(f, transform_index(t_idx, td.tile_size, td.num_tiles), final_state, true);
}
}).wait();
}
} // namespace Impl
} // namespace Kokkos

View File

@ -0,0 +1,726 @@
/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#include <stdlib.h>
#include <iostream>
#include <sstream>
#include <stdexcept>
#include <algorithm>
#include <atomic>
#include <Kokkos_Macros.hpp>
/* only compile this file if ROCM is enabled for Kokkos */
#ifdef KOKKOS_ENABLE_ROCM
#include <Kokkos_Core.hpp>
#include <Kokkos_ROCm.hpp>
#include <Kokkos_ROCmSpace.hpp>
#include <impl/Kokkos_Error.hpp>
#if defined(KOKKOS_ENABLE_PROFILING)
#include <impl/Kokkos_Profiling_Interface.hpp>
#endif
/*--------------------------------------------------------------------------*/
/*--------------------------------------------------------------------------*/
#define ROCM_SAFE_CALL
namespace Kokkos {
namespace Impl {
using namespace hc;
DeepCopy<Kokkos::Experimental::ROCmSpace,Kokkos::Experimental::ROCmSpace,Kokkos::Experimental::ROCm>::DeepCopy( void * dst , const void * src , size_t n )
{
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
av.copy( src , dst , n);
}
DeepCopy<HostSpace,Kokkos::Experimental::ROCmSpace,Kokkos::Experimental::ROCm>::DeepCopy( void * dst , const void * src , size_t n )
{
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
av.copy( src , dst , n);
}
DeepCopy<Kokkos::Experimental::ROCmSpace,HostSpace,Kokkos::Experimental::ROCm>::DeepCopy( void * dst , const void * src , size_t n )
{
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
av.copy( src , dst , n);
}
DeepCopy<Kokkos::Experimental::ROCmSpace,Kokkos::Experimental::ROCmSpace,Kokkos::Experimental::ROCm>::DeepCopy( const Kokkos::Experimental::ROCm & instance , void * dst , const void * src , size_t n )
{
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
av.copy( src , dst , n);
}
DeepCopy<HostSpace,Kokkos::Experimental::ROCmSpace,Kokkos::Experimental::ROCm>::DeepCopy( const Kokkos::Experimental::ROCm & instance , void * dst , const void * src , size_t n )
{
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
av.copy( src , dst , n);
}
DeepCopy<Kokkos::Experimental::ROCmSpace,HostSpace,Kokkos::Experimental::ROCm>::DeepCopy( const Kokkos::Experimental::ROCm & instance , void * dst , const void * src , size_t n )
{
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
av.copy( src , dst , n);
}
DeepCopy<Kokkos::Experimental::ROCmHostPinnedSpace,Kokkos::Experimental::ROCmHostPinnedSpace,Kokkos::Experimental::ROCm>::DeepCopy( void * dst , const void * src , size_t n )
{
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
av.copy( src , dst , n);
}
DeepCopy<HostSpace,Kokkos::Experimental::ROCmHostPinnedSpace,Kokkos::Experimental::ROCm>::DeepCopy( void * dst , const void * src , size_t n )
{
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
av.copy( src , dst , n);
}
DeepCopy<Kokkos::Experimental::ROCmHostPinnedSpace,HostSpace,Kokkos::Experimental::ROCm>::DeepCopy( void * dst , const void * src , size_t n )
{
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
av.copy( src , dst , n);
}
DeepCopy<Kokkos::Experimental::ROCmHostPinnedSpace,Kokkos::Experimental::ROCmHostPinnedSpace,Kokkos::Experimental::ROCm>::DeepCopy( const Kokkos::Experimental::ROCm & instance , void * dst , const void * src , size_t n )
{
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
av.copy( src , dst , n);
}
DeepCopy<HostSpace,Kokkos::Experimental::ROCmHostPinnedSpace,Kokkos::Experimental::ROCm>::DeepCopy( const Kokkos::Experimental::ROCm & instance , void * dst , const void * src , size_t n )
{
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
av.copy( src , dst , n);
}
DeepCopy<Kokkos::Experimental::ROCmHostPinnedSpace,HostSpace,Kokkos::Experimental::ROCm>::DeepCopy( const Kokkos::Experimental::ROCm & instance , void * dst , const void * src , size_t n )
{
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
av.copy( src , dst , n);
}
hc::completion_future DeepCopyAsyncROCm( void * dst , const void * src , size_t n) {
hc::accelerator acc;
hc::accelerator_view av = acc.get_default_view();
return(av.copy_async( src , dst , n));
}
} // namespace Impl
} // namespace Kokkos
/*--------------------------------------------------------------------------*/
/*--------------------------------------------------------------------------*/
namespace Kokkos {
void Experimental::ROCmSpace::access_error()
{
const std::string msg("Kokkos::Experimental::ROCmSpace::access_error attempt to execute Experimental::ROCm function from non-ROCm space" );
Kokkos::Impl::throw_runtime_exception( msg );
}
void Experimental::ROCmSpace::access_error( const void * const )
{
const std::string msg("Kokkos::Experimental::ROCmSpace::access_error attempt to execute Experimental::ROCm function from non-ROCm space" );
Kokkos::Impl::throw_runtime_exception( msg );
}
} // namespace Kokkos
/*--------------------------------------------------------------------------*/
/*--------------------------------------------------------------------------*/
namespace Kokkos {
namespace Experimental {
ROCmSpace::ROCmSpace()
: m_device( ROCm().rocm_device() )
{
}
ROCmHostPinnedSpace::ROCmHostPinnedSpace()
{
}
void * ROCmSpace::allocate( const size_t arg_alloc_size ) const
{
void * ptr = Kokkos::Impl::rocm_device_allocate( arg_alloc_size );
return ptr ;
}
void * Experimental::ROCmHostPinnedSpace::allocate( const size_t arg_alloc_size ) const
{
void * ptr = Kokkos::Impl::rocm_hostpinned_allocate( arg_alloc_size );
return ptr ;
}
void ROCmSpace::deallocate( void * const arg_alloc_ptr , const size_t /* arg_alloc_size */ ) const
{
Kokkos::Impl::rocm_device_free(arg_alloc_ptr);
}
void Experimental::ROCmHostPinnedSpace::deallocate( void * const arg_alloc_ptr , const size_t /* arg_alloc_size */ ) const
{
Kokkos::Impl::rocm_device_free(arg_alloc_ptr);
}
} // namespace Experimental
} // namespace Kokkos
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Impl {
SharedAllocationRecord< void , void >
SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::s_root_record ;
SharedAllocationRecord< void , void >
SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::s_root_record ;
std::string
SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::get_label() const
{
SharedAllocationHeader header ;
Kokkos::Impl::DeepCopy< Kokkos::HostSpace , Kokkos::Experimental::ROCmSpace >( & header , RecordBase::head() , sizeof(SharedAllocationHeader) );
return std::string( header.m_label );
}
std::string
SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::get_label() const
{
return std::string( RecordBase::head()->m_label );
}
SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void > *
SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::
allocate( const Kokkos::Experimental::ROCmSpace & arg_space
, const std::string & arg_label
, const size_t arg_alloc_size
)
{
return new SharedAllocationRecord( arg_space , arg_label , arg_alloc_size );
}
SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void > *
SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::
allocate( const Kokkos::Experimental::ROCmHostPinnedSpace & arg_space
, const std::string & arg_label
, const size_t arg_alloc_size
)
{
return new SharedAllocationRecord( arg_space , arg_label , arg_alloc_size );
}
void
SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::
deallocate( SharedAllocationRecord< void , void > * arg_rec )
{
delete static_cast<SharedAllocationRecord*>(arg_rec);
}
void
SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::
deallocate( SharedAllocationRecord< void , void > * arg_rec )
{
delete static_cast<SharedAllocationRecord*>(arg_rec);
}
SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::
~SharedAllocationRecord()
{
#if defined(KOKKOS_ENABLE_PROFILING)
if(Kokkos::Profiling::profileLibraryLoaded()) {
SharedAllocationHeader header ;
Kokkos::Impl::DeepCopy<Kokkos::Experimental::ROCmSpace,HostSpace>( & header , RecordBase::m_alloc_ptr , sizeof(SharedAllocationHeader) );
Kokkos::Profiling::deallocateData(
Kokkos::Profiling::SpaceHandle(Kokkos::Experimental::ROCmSpace::name()),header.m_label,
data(),size());
}
#endif
m_space.deallocate( SharedAllocationRecord< void , void >::m_alloc_ptr
, SharedAllocationRecord< void , void >::m_alloc_size
);
}
SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::
~SharedAllocationRecord()
{
#if defined(KOKKOS_ENABLE_PROFILING)
if(Kokkos::Profiling::profileLibraryLoaded()) {
Kokkos::Profiling::deallocateData(
Kokkos::Profiling::SpaceHandle(Kokkos::Experimental::ROCmHostPinnedSpace::name()),RecordBase::m_alloc_ptr->m_label,
data(),size());
}
#endif
m_space.deallocate( SharedAllocationRecord< void , void >::m_alloc_ptr
, SharedAllocationRecord< void , void >::m_alloc_size
);
}
SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::
SharedAllocationRecord( const Kokkos::Experimental::ROCmSpace & arg_space
, const std::string & arg_label
, const size_t arg_alloc_size
, const SharedAllocationRecord< void , void >::function_type arg_dealloc
)
// Pass through allocated [ SharedAllocationHeader , user_memory ]
// Pass through deallocation function
: SharedAllocationRecord< void , void >
( & SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::s_root_record
, reinterpret_cast<SharedAllocationHeader*>( arg_space.allocate( sizeof(SharedAllocationHeader) + arg_alloc_size ) )
, sizeof(SharedAllocationHeader) + arg_alloc_size
, arg_dealloc
)
, m_space( arg_space )
{
#if defined(KOKKOS_ENABLE_PROFILING)
if(Kokkos::Profiling::profileLibraryLoaded()) {
Kokkos::Profiling::allocateData(Kokkos::Profiling::SpaceHandle(arg_space.name()),arg_label,data(),arg_alloc_size);
}
#endif
SharedAllocationHeader header ;
// Fill in the Header information
header.m_record = static_cast< SharedAllocationRecord< void , void > * >( this );
strncpy( header.m_label
, arg_label.c_str()
, SharedAllocationHeader::maximum_label_length
);
// Copy to device memory
Kokkos::Impl::DeepCopy<Kokkos::Experimental::ROCmSpace,HostSpace>( RecordBase::m_alloc_ptr , & header , sizeof(SharedAllocationHeader) );
}
SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::
SharedAllocationRecord( const Kokkos::Experimental::ROCmHostPinnedSpace & arg_space
, const std::string & arg_label
, const size_t arg_alloc_size
, const SharedAllocationRecord< void , void >::function_type arg_dealloc
)
// Pass through allocated [ SharedAllocationHeader , user_memory ]
// Pass through deallocation function
: SharedAllocationRecord< void , void >
( & SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::s_root_record
, reinterpret_cast<SharedAllocationHeader*>( arg_space.allocate( sizeof(SharedAllocationHeader) + arg_alloc_size ) )
, sizeof(SharedAllocationHeader) + arg_alloc_size
, arg_dealloc
)
, m_space( arg_space )
{
#if defined(KOKKOS_ENABLE_PROFILING)
if(Kokkos::Profiling::profileLibraryLoaded()) {
Kokkos::Profiling::allocateData(Kokkos::Profiling::SpaceHandle(arg_space.name()),arg_label,data(),arg_alloc_size);
}
#endif
// Fill in the Header information, directly accessible via host pinned memory
RecordBase::m_alloc_ptr->m_record = this ;
strncpy( RecordBase::m_alloc_ptr->m_label
, arg_label.c_str()
, SharedAllocationHeader::maximum_label_length
);
}
//----------------------------------------------------------------------------
void * SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::
allocate_tracked( const Kokkos::Experimental::ROCmSpace & arg_space
, const std::string & arg_alloc_label
, const size_t arg_alloc_size )
{
if ( ! arg_alloc_size ) return (void *) 0 ;
SharedAllocationRecord * const r =
allocate( arg_space , arg_alloc_label , arg_alloc_size );
RecordBase::increment( r );
return r->data();
}
void SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::
deallocate_tracked( void * const arg_alloc_ptr )
{
if ( arg_alloc_ptr != 0 ) {
SharedAllocationRecord * const r = get_record( arg_alloc_ptr );
RecordBase::decrement( r );
}
}
void * SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::
reallocate_tracked( void * const arg_alloc_ptr
, const size_t arg_alloc_size )
{
SharedAllocationRecord * const r_old = get_record( arg_alloc_ptr );
SharedAllocationRecord * const r_new = allocate( r_old->m_space , r_old->get_label() , arg_alloc_size );
Kokkos::Impl::DeepCopy<Kokkos::Experimental::ROCmSpace,Kokkos::Experimental::ROCmSpace>( r_new->data() , r_old->data()
, std::min( r_old->size() , r_new->size() ) );
RecordBase::increment( r_new );
RecordBase::decrement( r_old );
return r_new->data();
}
#if 0
void * SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::
allocate_tracked( const Kokkos::Experimental::ROCmHostPinnedSpace & arg_space
, const std::string & arg_alloc_label
, const size_t arg_alloc_size )
{
if ( ! arg_alloc_size ) return (void *) 0 ;
SharedAllocationRecord * const r =
allocate( arg_space , arg_alloc_label , arg_alloc_size );
RecordBase::increment( r );
return r->data();
}
void SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::
deallocate_tracked( void * const arg_alloc_ptr )
{
if ( arg_alloc_ptr != 0 ) {
SharedAllocationRecord * const r = get_record( arg_alloc_ptr );
RecordBase::decrement( r );
}
}
void * SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::
reallocate_tracked( void * const arg_alloc_ptr
, const size_t arg_alloc_size )
{
SharedAllocationRecord * const r_old = get_record( arg_alloc_ptr );
SharedAllocationRecord * const r_new = allocate( r_old->m_space , r_old->get_label() , arg_alloc_size );
Kokkos::Impl::DeepCopy<Experimental::ROCmHostPinnedSpace,Experimental::ROCmHostPinnedSpace>( r_new->data() , r_old->data()
, std::min( r_old->size() , r_new->size() ) );
RecordBase::increment( r_new );
RecordBase::decrement( r_old );
return r_new->data();
}
#endif
//----------------------------------------------------------------------------
SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void > *
SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::get_record( void * alloc_ptr )
{
using Header = SharedAllocationHeader ;
using RecordBase = SharedAllocationRecord< void , void > ;
using RecordROCm = SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void > ;
#if 0
// Copy the header from the allocation
Header head ;
Header const * const head_rocm = alloc_ptr ? Header::get_header( alloc_ptr ) : (Header*) 0 ;
if ( alloc_ptr ) {
Kokkos::Impl::DeepCopy<HostSpace,Experimental::ROCmSpace>( & head , head_rocm , sizeof(SharedAllocationHeader) );
}
RecordROCm * const record = alloc_ptr ? static_cast< RecordROCm * >( head.m_record ) : (RecordROCm *) 0 ;
if ( ! alloc_ptr || record->m_alloc_ptr != head_rocm ) {
Kokkos::Impl::throw_runtime_exception( std::string("Kokkos::Impl::SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::get_record ERROR" ) );
}
#else
// Iterate the list to search for the record among all allocations
// requires obtaining the root of the list and then locking the list.
RecordROCm * const record = static_cast< RecordROCm * >( RecordBase::find( & s_root_record , alloc_ptr ) );
if ( record == 0 ) {
Kokkos::Impl::throw_runtime_exception( std::string("Kokkos::Impl::SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::get_record ERROR" ) );
}
#endif
return record ;
}
#if 0
SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void > *
SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::get_record( void * alloc_ptr )
{
using Header = SharedAllocationHeader ;
using RecordROCm = SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void > ;
Header * const h = alloc_ptr ? reinterpret_cast< Header * >( alloc_ptr ) - 1 : (Header *) 0 ;
if ( ! alloc_ptr || h->m_record->m_alloc_ptr != h ) {
Kokkos::Impl::throw_runtime_exception( std::string("Kokkos::Impl::SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::get_record ERROR" ) );
}
return static_cast< RecordROCm * >( h->m_record );
}
#endif
// Iterate records to print orphaned memory ...
void
SharedAllocationRecord< Kokkos::Experimental::ROCmSpace , void >::
print_records( std::ostream & s , const Kokkos::Experimental::ROCmSpace & space , bool detail )
{
SharedAllocationRecord< void , void > * r = & s_root_record ;
char buffer[256] ;
SharedAllocationHeader head ;
if ( detail ) {
do {
if ( r->m_alloc_ptr ) {
Kokkos::Impl::DeepCopy<HostSpace,Kokkos::Experimental::ROCmSpace>( & head , r->m_alloc_ptr , sizeof(SharedAllocationHeader) );
}
else {
head.m_label[0] = 0 ;
}
//Formatting dependent on sizeof(uintptr_t)
const char * format_string;
if (sizeof(uintptr_t) == sizeof(unsigned long)) {
format_string = "ROCm addr( 0x%.12lx ) list( 0x%.12lx 0x%.12lx ) extent[ 0x%.12lx + %.8ld ] count(%d) dealloc(0x%.12lx) %s\n";
}
else if (sizeof(uintptr_t) == sizeof(unsigned long long)) {
format_string = "ROCm addr( 0x%.12llx ) list( 0x%.12llx 0x%.12llx ) extent[ 0x%.12llx + %.8ld ] count(%d) dealloc(0x%.12llx) %s\n";
}
snprintf( buffer , 256
, format_string
, reinterpret_cast<uintptr_t>( r )
, reinterpret_cast<uintptr_t>( r->m_prev )
, reinterpret_cast<uintptr_t>( r->m_next )
, reinterpret_cast<uintptr_t>( r->m_alloc_ptr )
, r->m_alloc_size
, r->m_count
, reinterpret_cast<uintptr_t>( r->m_dealloc )
, head.m_label
);
std::cout << buffer ;
r = r->m_next ;
} while ( r != & s_root_record );
}
else {
do {
if ( r->m_alloc_ptr ) {
Kokkos::Impl::DeepCopy<HostSpace,Kokkos::Experimental::ROCmSpace>( & head , r->m_alloc_ptr , sizeof(SharedAllocationHeader) );
//Formatting dependent on sizeof(uintptr_t)
const char * format_string;
if (sizeof(uintptr_t) == sizeof(unsigned long)) {
format_string = "ROCm [ 0x%.12lx + %ld ] %s\n";
}
else if (sizeof(uintptr_t) == sizeof(unsigned long long)) {
format_string = "ROCm [ 0x%.12llx + %ld ] %s\n";
}
snprintf( buffer , 256
, format_string
, reinterpret_cast< uintptr_t >( r->data() )
, r->size()
, head.m_label
);
}
else {
snprintf( buffer , 256 , "ROCm [ 0 + 0 ]\n" );
}
std::cout << buffer ;
r = r->m_next ;
} while ( r != & s_root_record );
}
}
#if 0
void
SharedAllocationRecord< Kokkos::Experimental::ROCmHostPinnedSpace , void >::
print_records( std::ostream & s , const Kokkos::Experimental::ROCmHostPinnedSpace & space , bool detail )
{
SharedAllocationRecord< void , void >::print_host_accessible_records( s , "ROCmHostPinned" , & s_root_record , detail );
}
#endif
} // namespace Impl
} // namespace Kokkos
/*--------------------------------------------------------------------------*/
/*--------------------------------------------------------------------------*/
namespace Kokkos {
namespace {
#if 0
KOKKOS_INLINE_FUNCTION void init_lock_array_kernel_atomic() {
unsigned i = tindex()*team_size() + lindex();
if(i<ROCM_SPACE_ATOMIC_MASK+1)
kokkos_impl_rocm_lock_arrays.atomic[i] = 0;
}
KOKKOS_INLINE_FUNCTION void init_lock_array_kernel_scratch_threadid(int N) {
unsigned i = tindex()*team_size() + lindex();
if(i<N) {
kokkos_impl_rocm_lock_arrays.scratch[i] = 0;
kokkos_impl_rocm_lock_arrays.threadid[i] = 0;
}
}
}
namespace Impl {
int* atomic_lock_array_rocm_space_ptr(bool deallocate) {
static int* ptr = NULL;
if(deallocate) {
rocmFree(ptr);
ptr = NULL;
}
if(ptr==NULL && !deallocate)
rocmMalloc(&ptr,sizeof(int)*(ROCM_SPACE_ATOMIC_MASK+1));
return ptr;
}
int* scratch_lock_array_rocm_space_ptr(bool deallocate) {
static int* ptr = NULL;
if(deallocate) {
rocmFree(ptr);
ptr = NULL;
}
if(ptr==NULL && !deallocate)
rocmMalloc(&ptr,sizeof(int)*(ROCm::concurrency()));
return ptr;
}
int* threadid_lock_array_rocm_space_ptr(bool deallocate) {
static int* ptr = NULL;
if(deallocate) {
rocmFree(ptr);
ptr = NULL;
}
if(ptr==NULL && !deallocate)
rocmMalloc(&ptr,sizeof(int)*(ROCm::concurrency()));
return ptr;
}
void init_lock_arrays_rocm_space() {
static int is_initialized = 0;
if(! is_initialized) {
Kokkos::Impl::ROCmLockArraysStruct locks;
locks.atomic = atomic_lock_array_rocm_space_ptr(false);
locks.scratch = scratch_lock_array_rocm_space_ptr(false);
locks.threadid = threadid_lock_array_rocm_space_ptr(false);
am_copyToSymbol( kokkos_impl_rocm_lock_arrays , & locks , sizeof(ROCmLockArraysStruct) );
init_lock_array_kernel_atomic<<<(ROCM_SPACE_ATOMIC_MASK+255)/256,256>>>();
init_lock_array_kernel_scratch_threadid<<<(Kokkos::Experimental::ROCm::concurrency()+255)/256,256>>>(Kokkos::Experimental::ROCm::concurrency());
}
}
#endif
void* rocm_resize_scratch_space(size_t bytes, bool force_shrink) {
static void* ptr = NULL;
static size_t current_size = 0;
if(current_size == 0) {
current_size = bytes;
ptr = Kokkos::kokkos_malloc<Kokkos::Experimental::ROCmSpace>("ROCmSpace::ScratchMemory",current_size);
}
if(bytes > current_size) {
current_size = bytes;
ptr = Kokkos::kokkos_realloc<Kokkos::Experimental::ROCmSpace>(ptr,current_size);
}
if((bytes < current_size) && (force_shrink)) {
current_size = bytes;
Kokkos::kokkos_free<Kokkos::Experimental::ROCmSpace>(ptr);
ptr = Kokkos::kokkos_malloc<Kokkos::Experimental::ROCmSpace>("ROCmSpace::ScratchMemory",current_size);
}
return ptr;
}
}
}
#endif // KOKKOS_ENABLE_ROCM

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/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#include <Kokkos_Core.hpp>
#if defined( KOKKOS_ENABLE_ROCM ) && defined( KOKKOS_ENABLE_TASKDAG )
#include <impl/Kokkos_TaskQueue_impl.hpp>
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Impl {
template class TaskQueue< Kokkos::Experimental::ROCm > ;
//----------------------------------------------------------------------------
KOKKOS_INLINE_FUNCTION
void TaskQueueSpecialization< Kokkos::Experimental::ROCm >::driver
( TaskQueueSpecialization< Kokkos::Experimental::ROCm >::queue_type * const queue,
hc::tiled_index<3> threadIdx )
{
using Member = TaskExec< Kokkos::Experimental::ROCm > ;
using Queue = TaskQueue< Kokkos::Experimental::ROCm > ;
using task_root_type = TaskBase< void , void , void > ;
task_root_type * const end = (task_root_type *) task_root_type::EndTag ;
Member single_exec( 1, threadIdx );
Member team_exec( threadIdx.tile_dim[0], threadIdx );
const int wavefront_lane = threadIdx.local[0] + threadIdx.local[1]* threadIdx.tile_dim[0] ;
union {
task_root_type * ptr ;
int raw[2] ;
} task ;
// Loop until all queues are empty and no tasks in flight
do {
// Each team lead attempts to acquire either a thread team task
// or collection of single thread tasks for the team.
if ( 0 == wavefront_lane ) {
task.ptr = 0 < *((volatile int *) & queue->m_ready_count) ? end : 0 ;
// Loop by priority and then type
for ( int i = 0 ; i < Queue::NumQueue && end == task.ptr ; ++i ) {
for ( int j = 0 ; j < 2 && end == task.ptr ; ++j ) {
task.ptr = Queue::pop_ready_task( & queue->m_ready[i][j] );
}
}
#if 0
printf("TaskQueue<ROCm>::driver(%d,%d) task(%lx)\n",threadIdx.z,blockIdx.x
, uintptr_t(task.ptr));
#endif
}
// shuffle broadcast
task.raw[0] = hc::__shfl( task.raw[0] , 0 );
task.raw[1] = hc::__shfl( task.raw[1] , 0 );
if ( 0 == task.ptr ) break ; // 0 == queue->m_ready_count
if ( end != task.ptr ) {
if ( task_root_type::TaskTeam == task.ptr->m_task_type ) {
// Thread Team Task
(*task.ptr->m_apply)( task.ptr , & team_exec );
}
else if ( 0 == threadIdx.local[1] ) {
// Single Thread Task
(*task.ptr->m_apply)( task.ptr , & single_exec );
}
if ( 0 == wavefront_lane ) {
queue->complete( task.ptr );
}
}
} while(1);
}
#if 0
namespace {
KOKKOS_INLINE_FUNCTION
void rocm_task_queue_execute( TaskQueue< Kokkos::Experimental::ROCm > * queue,
hc::tiled_index<3> threadIdx )
{ TaskQueueSpecialization< Kokkos::Experimental::ROCm >::driver( queue, threadIdx ); }
}
#endif
void TaskQueueSpecialization< Kokkos::Experimental::ROCm >::execute
( TaskQueue< Kokkos::Experimental::ROCm > * const queue )
{
const int workgroups_per_wavefront = 4 ;
const int wavefront_size = Kokkos::Impl::ROCmTraits::WavefrontSize ;
const int cu_count = Kokkos::Impl::rocm_internal_cu_count();
// const dim3 grid( Kokkos::Impl::rocm_internal_cu_count() , 1 , 1 );
// const dim3 block( 1 , Kokkos::Impl::ROCmTraits::WorkGroupSize , workgroups_per_wavefront );
// Query the stack size, in bytes:
// If not large enough then set the stack size, in bytes:
// adapted from the cuda code. TODO: Not at all sure that this is the proper
// to map the cuda grid/blocks/3D tiling to HCC
#if 0
hc::extent< 3 > flat_extent( cu_count,
wavefront_size, workgroups_per_wavefront );
hc::tiled_extent< 3 > team_extent = flat_extent.tile(1,
wavefront_size,workgroups_per_wavefront);
hc::parallel_for_each( team_extent , [&](hc::tiled_index<3> idx) [[hc]]
{
TaskQueueSpecialization< Kokkos::Experimental::ROCm >::driver( queue,idx );
}).wait();
#endif
}
}} /* namespace Kokkos::Impl */
//----------------------------------------------------------------------------
#endif /* #if defined( KOKKOS_ENABLE_ROCM ) && defined( KOKKOS_ENABLE_TASKDAG ) */

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/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#ifndef KOKKOS_IMPL_ROCM_TASK_HPP
#define KOKKOS_IMPL_ROCM_TASK_HPP
#if defined( KOKKOS_ENABLE_TASKDAG )
#include <ROCm/Kokkos_ROCm_Vectorization.hpp>
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Impl {
template< class > class TaskExec ;
template<>
class TaskQueueSpecialization< Kokkos::Experimental::ROCm >
{
public:
using execution_space = Kokkos::Experimental::ROCm ;
using queue_type = Kokkos::Impl::TaskQueue< execution_space > ;
using task_base_type = Kokkos::Impl::TaskBase< execution_space , void , void > ;
using member_type = TaskExec< execution_space > ;
// Must specify memory space
using memory_space = Kokkos::HostSpace ;
static
void iff_single_thread_recursive_execute( queue_type * const ) {}
KOKKOS_INLINE_FUNCTION
static void driver( queue_type * const, hc::tiled_index<3> );
// Must provide task queue execution function
static void execute( queue_type * const );
// Must provide mechanism to set function pointer in
// execution space from the host process.
template< typename FunctorType >
static
void proc_set_apply( typename TaskBase< Kokkos::Experimental::ROCm
, typename FunctorType::value_type
, FunctorType
>::function_type * ptr )
{
using TaskType = TaskBase< Kokkos::Experimental::ROCm
, typename FunctorType::value_type
, FunctorType
> ;
hc::extent< 1 > flat_extent( 1 );
hc::tiled_extent< 1 > team_extent = flat_extent.tile( 1);
hc::parallel_for_each( team_extent , [&](hc::tiled_index<1> idx) [[hc]]
{
*ptr = TaskType::apply ;
}).wait();
}
};
/*template<>
KOKKOS_FUNCTION
void TaskQueue<Kokkos::Experimental::ROCm>::decrement( typename TaskQueue<Kokkos::Experimental::ROCm>::task_root_type *
) {}
*/
extern template class TaskQueue< Kokkos::Experimental::ROCm > ;
//----------------------------------------------------------------------------
/**\brief Impl::TaskExec<ROCm> is the TaskScheduler<ROCm>::member_type
* passed to tasks running in a ROCm space.
*
* ROCm thread blocks for tasking are dimensioned:
* idx.tile_dim[0] == vector length
* idx.tile_dim[1] == team size
* idx.tile_dim[2] == number of teams
* where
* idx.tile_dim[0] * idx.tile_dim[1] == WavefrontSize
*
* Both single thread and thread team tasks are run by a full ROCm warp.
* A single thread task is called by warp lane #0 and the remaining
* lanes of the warp are idle.
*/
template<>
class TaskExec< Kokkos::Experimental::ROCm >
{
private:
TaskExec( TaskExec && ) = delete ;
TaskExec( TaskExec const & ) = delete ;
TaskExec & operator = ( TaskExec && ) = delete ;
TaskExec & operator = ( TaskExec const & ) = delete ;
friend class Kokkos::Impl::TaskQueue< Kokkos::Experimental::ROCm > ;
friend class Kokkos::Impl::TaskQueueSpecialization< Kokkos::Experimental::ROCm > ;
int m_team_size ;
hc::tiled_index<3> m_idx;
// KOKKOS_INLINE_FUNCTION TaskExec( int arg_team_size ) //TODO: tile_dim[0]
// : m_team_size( arg_team_size ) {}
KOKKOS_INLINE_FUNCTION TaskExec( int arg_team_size,
hc::tiled_index<3> tidx)
: m_team_size( arg_team_size),
m_idx( tidx ) {}
public:
// const auto local = t_idx.local[0];
// const auto global = t_idx.global[0];
// const auto tile = t_idx.tile[0];
hc::tiled_index<3> idx() const { return m_idx;}
#if defined( __HCC_ACCELERATOR__ )
KOKKOS_INLINE_FUNCTION void team_barrier() { /* __threadfence_block(); */ }
KOKKOS_INLINE_FUNCTION int team_rank() const { return m_idx.local[1] ; } // t_idx.tile[0];
KOKKOS_INLINE_FUNCTION int team_size() const { return m_team_size ; }
#else
KOKKOS_INLINE_FUNCTION void team_barrier() {}
KOKKOS_INLINE_FUNCTION int team_rank() const { return 0 ; }
KOKKOS_INLINE_FUNCTION int team_size() const { return 0 ; }
#endif
};
}} /* namespace Kokkos::Impl */
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
template<typename iType>
KOKKOS_INLINE_FUNCTION
Impl::TeamThreadRangeBoundariesStruct<iType,Impl::TaskExec< Kokkos::Experimental::ROCm > >
TeamThreadRange
( Impl::TaskExec< Kokkos::Experimental::ROCm > & thread, const iType & count )
{
return Impl::TeamThreadRangeBoundariesStruct<iType,Impl::TaskExec< Kokkos::Experimental::ROCm > >(thread,count);
}
template<typename iType1, typename iType2>
KOKKOS_INLINE_FUNCTION
Impl::TeamThreadRangeBoundariesStruct< typename std::common_type< iType1, iType2 >::type,
Impl::TaskExec< Kokkos::Experimental::ROCm > >
TeamThreadRange
( Impl:: TaskExec< Kokkos::Experimental::ROCm > & thread, const iType1 & begin, const iType2 & end )
{
typedef typename std::common_type<iType1, iType2>::type iType;
return Impl::TeamThreadRangeBoundariesStruct<iType, Impl::TaskExec< Kokkos::Experimental::ROCm > >(thread, begin, end);
}
template<typename iType>
KOKKOS_INLINE_FUNCTION
Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::TaskExec< Kokkos::Experimental::ROCm > >
ThreadVectorRange
( Impl::TaskExec< Kokkos::Experimental::ROCm > & thread
, const iType & count )
{
return Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::TaskExec< Kokkos::Experimental::ROCm > >(thread,count);
}
/** \brief Inter-thread parallel_for. Executes lambda(iType i) for each i=0..N-1.
*
* The range i=0..N-1 is mapped to all threads of the the calling thread team.
* This functionality requires C++11 support.
*/
template<typename iType, class Lambda>
KOKKOS_INLINE_FUNCTION
void parallel_for
( const Impl::TeamThreadRangeBoundariesStruct<iType,Impl:: TaskExec< Kokkos::Experimental::ROCm > >& loop_boundaries
, const Lambda& lambda
)
{
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment) {
lambda(i);
}
}
// reduce across corresponding lanes between team members within workgroup
// assume stride*team_size == workgroup_size
template< typename ValueType >
KOKKOS_INLINE_FUNCTION
void strided_shfl_workgroup_reduction
(const ValueType& f(),
ValueType& val,
int team_size,
int stride)
{
for (int lane_delta=(team_size*stride)>>1; lane_delta>=stride; lane_delta>>=1) {
f(val, Kokkos::shfl_down(val, lane_delta, team_size*stride));
}
}
template< typename ValueType, class JoinType >
KOKKOS_INLINE_FUNCTION
void strided_shfl_workgroup_reduction
(const JoinType& join,
ValueType& val,
int team_size,
int stride)
{
for (int lane_delta=(team_size*stride)>>1; lane_delta>=stride; lane_delta>>=1) {
join(val, shfl_down(val, lane_delta, team_size*stride));
}
}
// multiple within-workgroup non-strided reductions
template< typename ValueType, class JoinType >
KOKKOS_INLINE_FUNCTION
void multi_shfl_workgroup_reduction
(const JoinType& join,
ValueType& val,
int vec_length)
{
for (int lane_delta=vec_length>>1; lane_delta; lane_delta>>=1) {
join(val, shfl_down(val, lane_delta, vec_length));
}
}
// broadcast within workgroup
template< class ValueType >
KOKKOS_INLINE_FUNCTION
ValueType shfl_workgroup_broadcast
(ValueType& val,
int src_lane,
int width)
{
return shfl(val, src_lane, width);
}
// all-reduce across corresponding vector lanes between team members within workgroup
// assume vec_length*team_size == workgroup_size
// blockDim.x == vec_length == stride
// blockDim.y == team_size
// threadIdx.x == position in vec
// threadIdx.y == member number
template<typename iType, class Lambda, typename ValueType>
KOKKOS_INLINE_FUNCTION
void parallel_reduce
( const Impl::TeamThreadRangeBoundariesStruct<iType,Impl:: TaskExec< Kokkos::Experimental::ROCm > >& loop_boundaries
, const Lambda& lambda
, ValueType& initialized_result)
{
int team_rank = loop_boundaries.thread.team_rank(); // member num within the team
ValueType result = initialized_result;
hc::tiled_index<3> idx = loop_boundaries.thread.idx();
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment) {
lambda(i, result);
}
initialized_result = result;
strided_shfl_workgroup_reduction(
[&] (ValueType& val1, const ValueType& val2) { val1 += val2; },
initialized_result,
loop_boundaries.thread.team_size(),
idx.tile_dim[0]);
initialized_result = shfl_workgroup_broadcast<ValueType>( initialized_result, idx.local[0], Impl::ROCmTraits::WavefrontSize );
}
template< typename iType, class Lambda, typename ValueType, class JoinType >
KOKKOS_INLINE_FUNCTION
void parallel_reduce
(const Impl::TeamThreadRangeBoundariesStruct<iType,Impl::TaskExec< Kokkos::Experimental::ROCm > >& loop_boundaries,
const Lambda & lambda,
const JoinType & join,
ValueType& initialized_result)
{
hc::tiled_index<3> idx = loop_boundaries.thread.idx();
int team_rank = loop_boundaries.thread.team_rank(); // member num within the team
ValueType result = initialized_result;
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment) {
lambda(i, result);
}
strided_shfl_workgroup_reduction<ValueType, JoinType>(
join,
initialized_result,
loop_boundaries.thread.team_size(),
idx.tile_dim[0]);
initialized_result = shfl_workgroup_broadcast<ValueType>( initialized_result, idx.local[0], Impl::ROCmTraits::WavefrontSize );
}
// placeholder for future function
template< typename iType, class Lambda, typename ValueType >
KOKKOS_INLINE_FUNCTION
void parallel_reduce
(const Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::TaskExec< Kokkos::Experimental::ROCm > >& loop_boundaries,
const Lambda & lambda,
ValueType& initialized_result)
{
ValueType result = initialized_result;
hc::tiled_index<3> idx = loop_boundaries.thread.idx();
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment) {
lambda(i,result);
}
initialized_result = result;
//initialized_result = multi_shfl_workgroup_reduction(
multi_shfl_workgroup_reduction(
[&] (ValueType& val1, const ValueType& val2) { val1 += val2; },
initialized_result,
idx.tile_dim[0]);
initialized_result = shfl_workgroup_broadcast<ValueType>( initialized_result, 0, idx.tile_dim[0] );
}
// placeholder for future function
template< typename iType, class Lambda, typename ValueType, class JoinType >
KOKKOS_INLINE_FUNCTION
void parallel_reduce
(const Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::TaskExec< Kokkos::Experimental::ROCm > >& loop_boundaries,
const Lambda & lambda,
const JoinType & join,
ValueType& initialized_result)
{
hc::tiled_index<3> idx = loop_boundaries.thread.idx();
ValueType result = initialized_result;
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment) {
lambda(i,result);
}
initialized_result = result;
multi_shfl_workgroup_reduction<ValueType, JoinType>(join, initialized_result, idx.tile_dim[0]);
initialized_result = shfl_workgroup_broadcast<ValueType>( initialized_result, 0, idx.tile_dim[0] );
}
template< typename ValueType, typename iType, class Lambda >
KOKKOS_INLINE_FUNCTION
void parallel_scan
(const Impl::TeamThreadRangeBoundariesStruct<iType,Impl::TaskExec< Kokkos::Experimental::ROCm > >& loop_boundaries,
const Lambda & lambda)
{
hc::tiled_index<3> idx = loop_boundaries.thread.idx();
ValueType accum = 0 ;
ValueType val, y, local_total;
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment) {
val = 0;
lambda(i,val,false);
// intra-idx.tile_dim[0] exclusive scan on 'val'
// accum = accumulated, sum in total for this iteration
// INCLUSIVE scan
for( int offset = idx.tile_dim[0] ; offset < Impl::ROCmTraits::WavefrontSize ; offset <<= 1 ) {
y = shfl_up(val, offset, Impl::ROCmTraits::WavefrontSize);
if(idx.local[1]*idx.tile_dim[0] >= offset) { val += y; }
}
// pass accum to all threads
local_total = shfl_workgroup_broadcast<ValueType>(val,
idx.local[0]+Impl::ROCmTraits::WavefrontSize-idx.tile_dim[0],
Impl::ROCmTraits::WavefrontSize);
// make EXCLUSIVE scan by shifting values over one
val = shfl_up(val, idx.tile_dim[0], Impl::ROCmTraits::WavefrontSize);
if ( idx.local[1] == 0 ) { val = 0 ; }
val += accum;
lambda(i,val,true);
accum += local_total;
}
}
// placeholder for future function
template< typename iType, class Lambda, typename ValueType >
KOKKOS_INLINE_FUNCTION
void parallel_scan
(const Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::TaskExec< Kokkos::Experimental::ROCm > >& loop_boundaries,
const Lambda & lambda)
{
hc::tiled_index<3> idx = loop_boundaries.thread.idx();
ValueType accum = 0 ;
ValueType val, y, local_total;
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment) {
val = 0;
lambda(i,val,false);
// intra-idx.tile_dim[0] exclusive scan on 'val'
// accum = accumulated, sum in total for this iteration
// INCLUSIVE scan
for( int offset = 1 ; offset < idx.tile_dim[0] ; offset <<= 1 ) {
y = shfl_up(val, offset, idx.tile_dim[0]);
if(idx.local[0] >= offset) { val += y; }
}
// pass accum to all threads
local_total = shfl_workgroup_broadcast<ValueType>(val, idx.tile_dim[0]-1,
idx.tile_dim[0]);
// make EXCLUSIVE scan by shifting values over one
val = shfl_up(val, 1, idx.tile_dim[0]);
if ( idx.local[0] == 0 ) { val = 0 ; }
val += accum;
lambda(i,val,true);
accum += local_total;
}
}
} /* namespace Kokkos */
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
#endif /* #if defined( KOKKOS_ENABLE_TASKDAG ) */
#endif /* #ifndef KOKKOS_IMPL_ROCM_TASK_HPP */

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/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#include <hc.hpp>
#include <type_traits>
#include <vector>
#include <memory>
#include <ROCm/Kokkos_ROCm_Config.hpp>
#if !defined( KOKKOS_ROCM_TILE_H )
#define KOKKOS_ROCM_TILE_H
// Macro to abstract out the enable_if craziness
#define KOKKOS_ROCM_REQUIRES(...) \
bool KokkosROCmRequiresBool ## __LINE__ = true, typename std::enable_if<KokkosROCmRequiresBool ## __LINE__ && (__VA_ARGS__), int>::type = 0
// This number uniquely identifies the 1.5 release build.
#if __hcc_workweek__ > 17160
#define ROCM15 1
#endif
namespace Kokkos {
namespace Impl {
template<class T>
#if defined(ROCM15)
using lds_t = T;
#else
// prior to 1.5, needed to decorate LDS addresses
using lds_t = __attribute__((address_space(3))) T;
#endif
#define KOKKOS_ROCM_TILE_RESTRIC_CPU restrict(cpu, amp)
// a set of routines to the replace the std::routines
// that will operate on address space 3 types
#if defined(ROCM15)
// 1.5 can't use std::copy et al for LDS access, so we define our own
// set of routines
template<class I, class O>
void rcopy(I first, I last, O out) [[hc]]
{
while (first != last) *out++ = *first++;
}
template<class I,class F>
void rfor_each(I first, I last, F f) [[hc]]
{
for(;first!=last;++first) f(*first);
}
template<class I,class O,class F>
void rtransform(I first, I last, O out, F f) [[hc]]
{
while(first!=last) *out++ = f(*first++);
}
#endif
inline std::size_t get_max_tile_size() KOKKOS_ROCM_TILE_RESTRIC_CPU
{
return hc::accelerator().get_max_tile_static_size() - 1024;
}
inline std::size_t get_max_tile_thread() KOKKOS_ROCM_TILE_RESTRIC_CPU
{
return 64;
}
inline int next_pow_2(int x) restrict(cpu, amp)
{
--x;
x |= x >> 1;
x |= x >> 2;
x |= x >> 4;
x |= x >> 8;
x |= x >> 16;
return x+1;
}
template<class T>
inline std::size_t get_tile_size(std::size_t n = 1,
std::size_t team = 64,
std::size_t vector = 1)
KOKKOS_ROCM_TILE_RESTRIC_CPU
{
const auto size = sizeof(T) * n;
const auto group_size = get_max_tile_size();
if (size == 0 || size > group_size) return 0;
// Assume that thread size is a power of 2
auto thread_size = std::min(team*vector,4*get_max_tile_thread());
// ensure that we have enough tile static memory to keep
// threadsize * size elements for reductions
while(size > (group_size / thread_size) && thread_size > 2)
{ thread_size /= 2;
}
return thread_size;
}
template<class T>
struct array_view
{
T* x;
std::size_t n;
array_view(T* xp, std::size_t np) [[hc]] [[cpu]]
: x(xp), n(np)
{}
array_view(T* xp, T* yp) [[hc]] [[cpu]]
: x(xp), n(yp-xp)
{}
T& operator[](std::size_t i) const [[hc]] [[cpu]]
{
return x[i];
}
std::size_t size() const [[hc]] [[cpu]]
{
return this->n;
}
T* data() const [[hc]] [[cpu]]
{
return x;
}
T* begin() const [[hc]] [[cpu]]
{
return x;
}
T* end() const [[hc]] [[cpu]]
{
return x+this->size();
}
};
template<class T>
struct rocm_char
{ using type=char; };
template<class T>
struct rocm_char<const T>
: std::add_const<typename rocm_char<T>::type>
{};
#if !defined(ROCM15)
// earlier compilers required explicit address space decorations
template<class T>
struct rocm_char<__attribute__((address_space(3))) T>
{ using type = __attribute__((address_space(3))) typename rocm_char<T>::type; };
template<class T>
struct rocm_char<const __attribute__((address_space(3))) T>
{ using type = const __attribute__((address_space(3))) typename rocm_char<T>::type; };
#endif
template<class T, class Char=typename rocm_char<T>::type>
Char* rocm_byte_cast(T& x) restrict(cpu, amp)
{
return reinterpret_cast<Char*>(&x);
}
template<class T, class U>
void rocm_raw_assign(T& x, const U& y) restrict(cpu, amp)
{
auto * src = rocm_byte_cast(y);
auto * dest = rocm_byte_cast(x);
#if defined (ROCM15)
rcopy(src, src+sizeof(T), dest);
#else
std::copy(src, src+sizeof(T), dest);
#endif
}
template<class T, class U>
void rocm_assign_impl(T& x, const U& y, std::true_type) restrict(cpu, amp)
{
rocm_raw_assign(x, y);
}
template<class T, class U>
void rocm_assign_impl(T& x, const U& y, std::false_type) restrict(cpu, amp)
{
x = y;
}
// Workaround for assigning in and out of LDS memory
template<class T, class U>
void rocm_assign(T& x, const U& y) restrict(cpu, amp)
{
rocm_assign_impl(x, y, std::integral_constant<bool, (
sizeof(T) == sizeof(U)
)>());
}
// Compute the address space of tile
template<class T>
struct tile_type
{
#if defined (ROCM15)
typedef T type;
#else
typedef __attribute__((address_space(3))) T type;
#endif
};
#if !defined (ROCM15)
template<class T, class Body>
void lds_for(__attribute__((address_space(3))) T& value, Body b) [[hc]]
{
T state = value;
b(state);
value = state;
}
#endif
template<class T, class Body>
void lds_for(T& value, Body b) [[hc]]
{
b(value);
}
constexpr std::size_t get_max_tile_array_size()
{
return 24;
}
template<class Derived, class T>
struct single_action
{
template<class Action>
void action_at(std::size_t i, Action a) [[hc]]
{
auto& value = static_cast<Derived&>(*this)[i];
#if KOKKOS_ROCM_HAS_WORKAROUNDS
T state = value;
a(state);
value = state;
#else
a(value);
#endif
}
template<class Action>
void action_at(std::size_t i, std::size_t j, Action a) [[hc]]
{
static_cast<Derived&>(*this).action_at(i, [&](T& x)
{
static_cast<Derived&>(*this).action_at(j, [&](T& y)
{
a(x, y);
});
});
}
};
template<class T>
struct tile_buffer
: array_view<typename tile_type<T>::type>, single_action<tile_buffer<T>, T>
{
typedef typename tile_type<T>::type element_type;
typedef array_view<element_type> base;
using base::base;
tile_buffer(element_type* xp, std::size_t np, std::size_t) [[hc]] [[cpu]]
: base(xp, np)
{}
tile_buffer(T* xp, T* yp, std::size_t) [[hc]] [[cpu]]
: base(xp, yp)
{}
};
template<class T>
struct tile_buffer<T[]>
{
typedef typename tile_type<T>::type element_type;
typedef typename tile_type<char>::type tchar_type;
element_type* element_data;
std::size_t n, m;
tile_buffer(element_type* xp, std::size_t np, std::size_t mp) [[hc]] [[cpu]]
: element_data(xp), n(np), m(mp)
{}
tile_buffer(element_type* xp, element_type* yp, std::size_t mp) [[hc]] [[cpu]]
: element_data(xp), n(yp-xp), m(mp)
{}
element_type* operator[](std::size_t i) const [[hc]] [[cpu]]
{
return element_data+i*m;
}
template<class Action, class Q = T>
typename Impl::enable_if< (sizeof(Q) <= 8) , void >::type
action_at(std::size_t i, Action a) [[hc]]
{
element_type* value = (*this)[i];
#if defined (ROCM15)
a(value);
#else
#if KOKKOS_ROCM_HAS_WORKAROUNDS
if (m > get_max_tile_array_size()) return;
T state[get_max_tile_array_size()];
// std::copy(value, value+m, state);
// Workaround for assigning from LDS memory
std::transform(value, value+m, state, [](element_type& x)
{
T result;
rocm_assign(result, x);
return result;
});
a(state);
std::copy(state, state+m, value);
#endif
#endif
}
template<class Action, class Q = T>
typename Impl::enable_if< !(sizeof(Q) <= 8) , void >::type
action_at(std::size_t i, Action a) [[hc]]
{
element_type* value = (*this)[i];
#if defined (ROCM15)
a(value);
#else
//#if KOKKOS_ROCM_HAS_WORKAROUNDS
if (m > get_max_tile_array_size()) return;
T state[get_max_tile_array_size()];
// std::copy(value, value+m, state);
// Workaround for assigning from LDS memory
std::transform(value, value+m, state, [](element_type& x)
{
T result;
rocm_assign(result, x);
return result;
});
a(state);
// this workaround required when T is greater than 8 bytes
tile_static char tv[64*sizeof(T)];
size_t sT = sizeof(T);
for (int j = 0; j<sT; j++) tv[i*sT+j] = ((char *)state)[j];
for (int j = 0; j<sT; j++) ((tchar_type *)value)[j] = tv[i*sT+j];
#endif
}
template<class Action>
void action_at(std::size_t i, std::size_t j, Action a) [[hc]]
{
this->action_at(i, [&](T* x)
{
this->action_at(j, [&](T* y)
{
a(x, y);
});
});
}
std::size_t size() const [[hc]] [[cpu]]
{
return this->n;
}
element_type* data() const [[hc]] [[cpu]]
{
return element_data;
}
};
// Zero initialize LDS memory
struct zero_init_f
{
template<class T>
#if defined (ROCM15)
void operator()(T& x, std::size_t=1) const [[hc]]
{
auto * start = reinterpret_cast<char*>(&x);
for(int i=0; i<sizeof(T);i++) start[i] = 0;
rocm_raw_assign(x, T());
}
#else
void operator()(__attribute__((address_space(3))) T& x, std::size_t=1) const [[hc]]
{
auto * start = reinterpret_cast<__attribute__((address_space(3))) char*>(&x);
std::fill(start, start+sizeof(T), 0);
rocm_raw_assign(x, T());
}
#endif
template<class T>
#if defined (ROCM15)
void operator()(T* x, std::size_t size) const [[hc]]
{
rfor_each(x, x+size, *this);
}
#else
void operator()(__attribute__((address_space(3))) T* x, std::size_t size) const [[hc]]
{
std::for_each(x, x+size, *this);
}
#endif
};
static constexpr zero_init_f zero_init = {};
struct tile_desc
{
// Number of work items, or size of extent
std::size_t elements;
// number of threads in team
std::size_t team_size;
// vector length of team
std::size_t vector_length;
// Size of tile
std::size_t tile_size;
// Size of array
std::size_t array_size;
// Number of tiles
std::size_t num_tiles;
// Per team reserved LDS memory, used for reduction
std::size_t reduce_size;
// Per team shared memory in LDS, this in addition to reduce shared mem
std::size_t shared_size;
std::size_t size;
};
template<class T>
tile_desc get_tile_desc(std::size_t size,
std::size_t array_size=1,
std::size_t team_size=64,
std::size_t vector_size=1,
std::size_t shared_size=0)
{
tile_desc result;
result.elements = size;
result.array_size = array_size;
result.vector_length = vector_size;
result.team_size = team_size;
result.tile_size = get_tile_size<T>(array_size,team_size,vector_size);
result.num_tiles = std::ceil(1.0 * size / result.tile_size);
result.reduce_size = result.tile_size * sizeof(T) * array_size;
result.shared_size = shared_size;
result.size = result.tile_size * result.num_tiles;
return result;
}
template<class U, class F, class T=typename std::remove_extent<U>::type>
hc::completion_future tile_for(tile_desc td, F f)
{
assert(td.array_size <= get_max_tile_array_size() && "Exceed max array size");
assert(((td.size % td.tile_size) == 0) && "Tile size must be divisible by extent");
auto grid = hc::extent<1>(td.size).tile_with_dynamic(
td.tile_size, td.reduce_size + td.shared_size);
// grid.set_dynamic_group_segment_size(td.reduce_size + td.shared_size);
return parallel_for_each(grid, [=](hc::tiled_index<1> t_idx) [[hc]]
{
#if defined (ROCM15)
typedef T group_t;
#else
typedef __attribute__((address_space(3))) T group_t;
#endif
group_t * buffer = (group_t *)hc::get_dynamic_group_segment_base_pointer();
tile_buffer<U> tb(buffer, td.tile_size, td.array_size);
zero_init(tb[t_idx.local[0]], td.array_size);
f(t_idx, tb);
});
}
}}
#endif

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/*
//@HEADER
// ************************************************************************
//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/
#ifndef KOKKOS_ROCM_VECTORIZATION_HPP
#define KOKKOS_ROCM_VECTORIZATION_HPP
#include <Kokkos_Macros.hpp>
/* only compile this file if ROCM is enabled for Kokkos */
#ifdef KOKKOS_ENABLE_ROCM
#include <Kokkos_ROCm.hpp>
namespace Kokkos {
using namespace hc;
// Shuffle only makes sense on >= Fiji GPUs; it doesn't work on CPUs
// or other GPUs. We provide a generic definition (which is trivial
// and doesn't do what it claims to do) because we don't actually use
// this function unless we are on a suitable GPU, with a suitable
// Scalar type. (For example, in the mat-vec, the "ThreadsPerRow"
// internal parameter depends both on the ExecutionSpace and the Scalar type,
// and it controls whether shfl_down() gets called.)
namespace Impl {
template< typename Scalar >
struct shfl_union {
enum {n = sizeof(Scalar)/4};
float fval[n];
KOKKOS_INLINE_FUNCTION
Scalar value() {
return *(Scalar*) fval;
}
KOKKOS_INLINE_FUNCTION
void operator= (Scalar& value_) {
float* const val_ptr = (float*) &value_;
for(int i=0; i<n ; i++) {
fval[i] = val_ptr[i];
}
}
KOKKOS_INLINE_FUNCTION
void operator= (const Scalar& value_) {
float* const val_ptr = (float*) &value_;
for(int i=0; i<n ; i++) {
fval[i] = val_ptr[i];
}
}
};
}
#ifdef __HCC_ACCELERATOR__
KOKKOS_INLINE_FUNCTION
int __long2loint(const long val ) {
union {
long l;
int i[2];
} u;
u.l = val;
return u.i[0];
}
KOKKOS_INLINE_FUNCTION
int __long2hiint(const long val ) {
union {
long l;
int i[2];
} u;
u.l = val;
return u.i[1];
}
KOKKOS_INLINE_FUNCTION
int __double2loint(const double val ) {
union {
double d;
int i[2];
} u;
u.d = val;
return u.i[0];
}
KOKKOS_INLINE_FUNCTION
int __double2hiint(const double val ) {
union {
double d;
int i[2];
} u;
u.d = val;
return u.i[1];
}
KOKKOS_INLINE_FUNCTION
long __hiloint2long(const int hi, const int lo ) {
union {
long l;
int i[2];
} u;
u.i[0] = lo;
u.i[1] = hi;
return u.l;
}
KOKKOS_INLINE_FUNCTION
double __hiloint2double(const int hi, const int lo ) {
union {
double d;
int i[2];
} u;
u.i[0] = lo;
u.i[1] = hi;
return u.d;
}
KOKKOS_INLINE_FUNCTION
int shfl(const int &val, const int& srcLane, const int& width ) {
return __shfl(val,srcLane,width);
}
KOKKOS_INLINE_FUNCTION
float shfl(const float &val, const int& srcLane, const int& width ) {
return __shfl(val,srcLane,width);
}
template<typename Scalar>
KOKKOS_INLINE_FUNCTION
Scalar shfl(const Scalar &val, const int& srcLane, const typename Impl::enable_if< (sizeof(Scalar) == 4) , int >::type& width
) {
Scalar tmp1 = val;
float tmp = *reinterpret_cast<float*>(&tmp1);
tmp = __shfl(tmp,srcLane,width);
return *reinterpret_cast<Scalar*>(&tmp);
}
KOKKOS_INLINE_FUNCTION
double shfl(const double &val, const int& srcLane, const int& width) {
int lo = __double2loint(val);
int hi = __double2hiint(val);
lo = __shfl(lo,srcLane,width);
hi = __shfl(hi,srcLane,width);
return __hiloint2double(hi,lo);
}
template<typename Scalar>
KOKKOS_INLINE_FUNCTION
Scalar shfl(const Scalar &val, const int& srcLane, const typename Impl::enable_if< (sizeof(Scalar) == 8) ,int>::type& width) {
int lo = __double2loint(*reinterpret_cast<const double*>(&val));
int hi = __double2hiint(*reinterpret_cast<const double*>(&val));
lo = __shfl(lo,srcLane,width);
hi = __shfl(hi,srcLane,width);
const double tmp = __hiloint2double(hi,lo);
return *(reinterpret_cast<const Scalar*>(&tmp));
}
template<typename Scalar>
KOKKOS_INLINE_FUNCTION
Scalar shfl(const Scalar &val, const int& srcLane, const typename Impl::enable_if< (sizeof(Scalar) > 8) ,int>::type& width) {
Impl::shfl_union<Scalar> s_val;
Impl::shfl_union<Scalar> r_val;
s_val = val;
for(int i = 0; i<s_val.n; i++)
r_val.fval[i] = __shfl(s_val.fval[i],srcLane,width);
return r_val.value();
}
KOKKOS_INLINE_FUNCTION
int shfl_down(const int &val, const int& delta, const int& width) {
return __shfl_down(val,delta,width);
}
KOKKOS_INLINE_FUNCTION
float shfl_down(const float &val, const int& delta, const int& width) {
return __shfl_down(val,delta,width);
}
template<typename Scalar>
KOKKOS_INLINE_FUNCTION
Scalar shfl_down(const Scalar &val, const int& delta, const typename Impl::enable_if< (sizeof(Scalar) == 4) , int >::type & width) {
Scalar tmp1 = val;
float tmp = *reinterpret_cast<float*>(&tmp1);
tmp = __shfl_down(tmp,delta,width);
return *reinterpret_cast<Scalar*>(&tmp);
}
KOKKOS_INLINE_FUNCTION
long shfl_down(const long &val, const int& delta, const int& width) {
int lo = __long2loint(val);
int hi = __long2hiint(val);
lo = __shfl_down(lo,delta,width);
hi = __shfl_down(hi,delta,width);
return __hiloint2long(hi,lo);
}
KOKKOS_INLINE_FUNCTION
double shfl_down(const double &val, const int& delta, const int& width) {
int lo = __double2loint(val);
int hi = __double2hiint(val);
lo = __shfl_down(lo,delta,width);
hi = __shfl_down(hi,delta,width);
return __hiloint2double(hi,lo);
}
template<typename Scalar>
KOKKOS_INLINE_FUNCTION
Scalar shfl_down(const Scalar &val, const int& delta, const typename Impl::enable_if< (sizeof(Scalar) == 8) , int >::type & width) {
int lo = __double2loint(*reinterpret_cast<const double*>(&val));
int hi = __double2hiint(*reinterpret_cast<const double*>(&val));
lo = __shfl_down(lo,delta,width);
hi = __shfl_down(hi,delta,width);
const double tmp = __hiloint2double(hi,lo);
return *(reinterpret_cast<const Scalar*>(&tmp));
}
template<typename Scalar>
KOKKOS_INLINE_FUNCTION
Scalar shfl_down(const Scalar &val, const int& delta, const typename Impl::enable_if< (sizeof(Scalar) > 8) , int >::type & width) {
Impl::shfl_union<Scalar> s_val;
Impl::shfl_union<Scalar> r_val;
s_val = val;
for(int i = 0; i<s_val.n; i++)
r_val.fval[i] = __shfl_down(s_val.fval[i],delta,width);
return r_val.value();
}
KOKKOS_INLINE_FUNCTION
int shfl_up(const int &val, const int& delta, const int& width ) {
return __shfl_up(val,delta,width);
}
KOKKOS_INLINE_FUNCTION
float shfl_up(const float &val, const int& delta, const int& width ) {
return __shfl_up(val,delta,width);
}
template<typename Scalar>
KOKKOS_INLINE_FUNCTION
Scalar shfl_up(const Scalar &val, const int& delta, const typename Impl::enable_if< (sizeof(Scalar) == 4) , int >::type & width) {
Scalar tmp1 = val;
float tmp = *reinterpret_cast<float*>(&tmp1);
tmp = __shfl_up(tmp,delta,width);
return *reinterpret_cast<Scalar*>(&tmp);
}
KOKKOS_INLINE_FUNCTION
double shfl_up(const double &val, const int& delta, const int& width ) {
int lo = __double2loint(val);
int hi = __double2hiint(val);
lo = __shfl_up(lo,delta,width);
hi = __shfl_up(hi,delta,width);
return __hiloint2double(hi,lo);
}
template<typename Scalar>
KOKKOS_INLINE_FUNCTION
Scalar shfl_up(const Scalar &val, const int& delta, const typename Impl::enable_if< (sizeof(Scalar) == 8) , int >::type & width) {
int lo = __double2loint(*reinterpret_cast<const double*>(&val));
int hi = __double2hiint(*reinterpret_cast<const double*>(&val));
lo = __shfl_up(lo,delta,width);
hi = __shfl_up(hi,delta,width);
const double tmp = __hiloint2double(hi,lo);
return *(reinterpret_cast<const Scalar*>(&tmp));
}
template<typename Scalar>
KOKKOS_INLINE_FUNCTION
Scalar shfl_up(const Scalar &val, const int& delta, const typename Impl::enable_if< (sizeof(Scalar) > 8) , int >::type & width) {
Impl::shfl_union<Scalar> s_val;
Impl::shfl_union<Scalar> r_val;
s_val = val;
for(int i = 0; i<s_val.n; i++)
r_val.fval[i] = __shfl_up(s_val.fval[i],delta,width);
return r_val.value();
}
#else
template<typename Scalar>
inline
Scalar shfl(const Scalar &val, const int& srcLane, const int& width) {
if(width > 1) Kokkos::abort("Error: calling shfl from a device with CC<8.0.");
return val;
}
template<typename Scalar>
inline
Scalar shfl_down(const Scalar &val, const int& delta, const int& width) {
if(width > 1) Kokkos::abort("Error: calling shfl_down from a device with CC<8.0.");
return val;
}
template<typename Scalar>
inline
Scalar shfl_up(const Scalar &val, const int& delta, const int& width) {
if(width > 1) Kokkos::abort("Error: calling shfl_down from a device with CC<8.0.");
return val;
}
#endif
}
#endif // KOKKOS_ENABLE_ROCM
#endif

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#pragma once
#include "hc.hpp"
#include <cmath>
// Math functions with integer overloads will be converted to
// this floating point type.
#define HC_IMPLICIT_FLOAT_CONV double
#ifdef __KALMAR_ACCELERATOR__
#define HC_MATH_WRAPPER_1(function, arg1) \
template<typename T> \
inline T function(T arg1) __attribute__((hc,cpu)) { \
return hc::precise_math::function(arg1); \
}
#define KALMAR_MATH_WRAPPER_1(function, arg1) HC_MATH_WRAPPER_1(function, arg1)
#define HC_MATH_WRAPPER_FP_OVERLOAD_1(function, arg1) \
template<typename T> \
inline \
typename std::enable_if<std::is_integral<T>::value,HC_IMPLICIT_FLOAT_CONV>::type \
function(T arg1) __attribute__((hc,cpu)) { \
return hc::precise_math::function(static_cast<HC_IMPLICIT_FLOAT_CONV>(arg1)); \
} \
template<typename T> \
inline \
typename std::enable_if<std::is_floating_point <T>::value,T>::type \
function(T arg1) __attribute__((hc,cpu)) { \
return hc::precise_math::function(arg1); \
}
#define KALMAR_MATH_WRAPPER_FP_OVERLOAD_1(function, arg1) HC_MATH_WRAPPER_FP_OVERLOAD_1(function, arg1)
#define HC_MATH_WRAPPER_2(function, arg1, arg2) \
template<typename T> \
inline T function(T arg1, T arg2) __attribute__((hc,cpu)) { \
return hc::precise_math::function(arg1, arg2); \
}
#define HC_MATH_ALIAS_2(alias, function, arg1, arg2) \
template<typename T> \
inline T alias(T arg1, T arg2) __attribute__((hc,cpu)) { \
return hc::precise_math::function(arg1, arg2); \
}
#define HC_MATH_WRAPPER_3(function, arg1, arg2, arg3) \
template<typename T> \
inline T function(T arg1, T arg2, T arg3) __attribute__((hc,cpu)) { \
return hc::precise_math::function(arg1, arg2, arg3); \
}
#define HC_MATH_WRAPPER_TQ(function, arg1) \
template<typename T, typename Q> \
inline T function(Q arg1) __attribute__((hc,cpu)) { \
return hc::precise_math::function(arg1); \
}
#define HC_MATH_WRAPPER_FP_OVERLOAD_TQ(function, T, arg1) \
template<typename Q> \
inline \
typename std::enable_if<std::is_integral<Q>::value,T>::type \
function(Q arg1) __attribute__((hc,cpu)) { \
return hc::precise_math::function(static_cast<HC_IMPLICIT_FLOAT_CONV>(arg1)); \
}\
template<typename Q> \
inline \
typename std::enable_if<std::is_floating_point<Q>::value,T>::type \
function(Q arg1) __attribute__((hc,cpu)) { \
return hc::precise_math::function(arg1); \
}
#define HC_MATH_WRAPPER_TTQ(function, arg1, arg2) \
template<typename T, typename Q> \
inline T function(T arg1, Q arg2) __attribute__((hc,cpu)) { \
return hc::precise_math::function(arg1, arg2); \
}
#define HC_MATH_WRAPPER_FP_OVERLOAD_TTQ(function, arg1, arg2) \
template<typename T, typename Q> \
inline \
typename std::enable_if<std::is_integral<T>::value||std::is_integral<Q>::value,HC_IMPLICIT_FLOAT_CONV>::type \
function(T arg1, Q arg2) __attribute__((hc,cpu)) { \
return hc::precise_math::function(static_cast<HC_IMPLICIT_FLOAT_CONV>(arg1),static_cast<HC_IMPLICIT_FLOAT_CONV>(arg2)); \
}\
template<typename T, typename Q> \
inline \
typename std::enable_if<std::is_floating_point<T>::value&&std::is_floating_point<Q>::value,T>::type \
function(T arg1, Q arg2) __attribute__((hc,cpu)) { \
return hc::precise_math::function(arg1,arg2); \
}
#define HC_MATH_WRAPPER_TTTQ(function, arg1, arg2, arg3) \
template<typename T, typename Q> \
inline T function(T arg1, T arg2, Q arg3) __attribute__((hc,cpu)) { \
return hc::precise_math::function(arg1, arg2, arg3); \
}
#define HC_MATH_WRAPPER_VTQQ(function, arg1, arg2, arg3) \
template<typename T, typename Q> \
inline void function(T arg1, Q arg2, Q arg3) __attribute__((hc,cpu)) { \
hc::precise_math::function(arg1, arg2, arg3); \
}
#else
#define HC_MATH_WRAPPER_1(function, arg1) \
template<typename T> \
inline T function(T arg1) __attribute__((hc,cpu)) { \
return std::function(arg1); \
}
#define KALMAR_MATH_WRAPPER_1(function, arg1) \
template<typename T> \
inline T function(T arg1) __attribute__((hc,cpu)) { \
return hc::precise_math::function(arg1); \
}
#define HC_MATH_WRAPPER_FP_OVERLOAD_1(function, arg1) \
template<typename T> \
inline \
typename std::enable_if<std::is_integral<T>::value,HC_IMPLICIT_FLOAT_CONV>::type \
function(T arg1) __attribute__((hc,cpu)) { \
return ::function(static_cast<HC_IMPLICIT_FLOAT_CONV>(arg1)); \
} \
template<typename T> \
inline \
typename std::enable_if<std::is_floating_point <T>::value,T>::type \
function(T arg1) __attribute__((hc,cpu)) { \
return std::function(arg1); \
}
#define KALMAR_MATH_WRAPPER_FP_OVERLOAD_1(function, arg1) \
template<typename T> \
inline \
typename std::enable_if<std::is_integral<T>::value,HC_IMPLICIT_FLOAT_CONV>::type \
function(T arg1) __attribute__((hc,cpu)) { \
return hc::precise_math::function(static_cast<HC_IMPLICIT_FLOAT_CONV>(arg1)); \
} \
template<typename T> \
inline \
typename std::enable_if<std::is_floating_point <T>::value,T>::type \
function(T arg1) __attribute__((hc,cpu)) { \
return hc::precise_math::function(arg1); \
}
#define HC_MATH_WRAPPER_2(function, arg1, arg2) \
template<typename T> \
inline T function(T arg1, T arg2) __attribute__((hc,cpu)) { \
return std::function(arg1, arg2); \
}
#define HC_MATH_ALIAS_2(alias, function, arg1, arg2) \
template<typename T> \
inline T alias(T arg1, T arg2) __attribute__((hc,cpu)) { \
return std::function(arg1, arg2); \
}
#define HC_MATH_WRAPPER_3(function, arg1, arg2, arg3) \
template<typename T> \
inline T function(T arg1, T arg2, T arg3) __attribute__((hc,cpu)) { \
return std::function(arg1, arg2, arg3); \
}
#define HC_MATH_WRAPPER_TQ(function, arg1) \
template<typename T, typename Q> \
inline T function(Q arg1) __attribute__((hc,cpu)) { \
return std::function(arg1); \
}
#define HC_MATH_WRAPPER_FP_OVERLOAD_TQ(function, T, arg1) \
template<typename Q> \
inline \
typename std::enable_if<std::is_integral<Q>::value,T>::type \
function(Q arg1) __attribute__((hc)) { \
return std::function(static_cast<HC_IMPLICIT_FLOAT_CONV>(arg1)); \
}\
template<typename Q> \
inline \
typename std::enable_if<std::is_floating_point<Q>::value,T>::type \
function(Q arg1) __attribute__((hc)) { \
return std::function(arg1); \
}
#define HC_MATH_WRAPPER_TTQ(function, arg1, arg2) \
template<typename T, typename Q> \
inline T function(T arg1, Q arg2) __attribute__((hc,cpu)) { \
return std::function(arg1, arg2); \
}
#define HC_MATH_WRAPPER_FP_OVERLOAD_TTQ(function, arg1, arg2) \
template<typename T, typename Q> \
inline \
typename std::enable_if<std::is_integral<T>::value||std::is_integral<Q>::value,HC_IMPLICIT_FLOAT_CONV>::type \
function(T arg1, Q arg2) __attribute__((hc,cpu)) { \
return std::function(static_cast<HC_IMPLICIT_FLOAT_CONV>(arg1),static_cast<HC_IMPLICIT_FLOAT_CONV>(arg2)); \
}\
template<typename T, typename Q> \
inline \
typename std::enable_if<std::is_floating_point<T>::value&&std::is_floating_point<Q>::value,T>::type \
function(T arg1, Q arg2) __attribute__((hc,cpu)) { \
return std::function(arg1,arg2); \
}
#define HC_MATH_WRAPPER_TTTQ(function, arg1, arg2, arg3) \
template<typename T, typename Q> \
inline T function(T arg1, T arg2, Q arg3) __attribute__((hc,cpu)) { \
return std::function(arg1, arg2, arg3); \
}
#define HC_MATH_WRAPPER_VTQQ(function, arg1, arg2, arg3) \
template<typename T, typename Q> \
inline void function(T arg1, Q arg2, Q arg3) __attribute__((hc,cpu)) { \
std::function(arg1, arg2, arg3); \
}
#endif
// override global math functions
namespace std {
// following math functions are NOT available because they don't have a GPU implementation
//
// erfinv
// erfcinv
// fpclassify
//
// following math functions are NOT available because they don't have a CPU implementation
//
// cospif
// cospi
// rsqrtf
// rsqrt
// sinpif
// sinpi
// tanpi
//
HC_MATH_WRAPPER_TQ(ilogbf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_TQ(ilogb, int, x)
HC_MATH_WRAPPER_FP_OVERLOAD_TQ(isfinite, bool, x)
HC_MATH_WRAPPER_FP_OVERLOAD_TQ(isinf, bool, x)
HC_MATH_WRAPPER_FP_OVERLOAD_TQ(isnan, bool, x)
HC_MATH_WRAPPER_FP_OVERLOAD_TQ(isnormal, bool, x)
HC_MATH_WRAPPER_TQ(nanf, tagp)
HC_MATH_WRAPPER_TQ(nan, tagp)
//HC_MATH_WRAPPER_TQ(signbitf, x)
HC_MATH_WRAPPER_TQ(signbit, x)
HC_MATH_WRAPPER_TTQ(frexpf, x, exp)
HC_MATH_WRAPPER_TTQ(frexp, x, exp)
HC_MATH_WRAPPER_TTQ(ldexpf, x, exp)
HC_MATH_WRAPPER_TTQ(ldexp, x, exp)
HC_MATH_WRAPPER_TTQ(lgammaf, x, exp)
HC_MATH_WRAPPER_TTQ(lgamma, x, exp)
HC_MATH_WRAPPER_TTQ(modff, x, exp)
HC_MATH_WRAPPER_TTQ(modf, x, exp)
HC_MATH_WRAPPER_TTQ(scalbnf, x, exp)
HC_MATH_WRAPPER_TTQ(scalbn, x, exp)
HC_MATH_WRAPPER_TTTQ(remquof, x, y, quo)
HC_MATH_WRAPPER_TTTQ(remquo, x, y, quo)
HC_MATH_WRAPPER_VTQQ(sincosf, x, s, c)
HC_MATH_WRAPPER_VTQQ(sincos, x, s, c)
HC_MATH_WRAPPER_1(acosf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(acos, x)
HC_MATH_WRAPPER_1(acoshf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(acosh, x)
HC_MATH_WRAPPER_1(asinf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(asin, x)
HC_MATH_WRAPPER_1(asinhf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(asinh, x)
HC_MATH_WRAPPER_1(atanf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(atan, x)
HC_MATH_WRAPPER_1(atanhf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(atanh, x)
HC_MATH_WRAPPER_2(atan2f, x, y)
HC_MATH_WRAPPER_2(atan2, x, y)
HC_MATH_WRAPPER_1(cbrtf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(cbrt, x)
HC_MATH_WRAPPER_1(ceilf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(ceil, x)
HC_MATH_WRAPPER_2(copysignf, x, y)
HC_MATH_WRAPPER_2(copysign, x, y)
HC_MATH_WRAPPER_1(cosf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(cos, x)
HC_MATH_WRAPPER_1(coshf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(cosh, x)
KALMAR_MATH_WRAPPER_1(cospif, x)
KALMAR_MATH_WRAPPER_FP_OVERLOAD_1(cospi, x)
HC_MATH_WRAPPER_1(erff, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(erf, x)
HC_MATH_WRAPPER_1(erfcf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(erfc, x)
HC_MATH_WRAPPER_1(expf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(exp, x)
HC_MATH_WRAPPER_1(exp2f, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(exp2, x)
HC_MATH_WRAPPER_1(exp10f, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(exp10, x)
HC_MATH_WRAPPER_1(expm1f, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(expm1, x)
HC_MATH_WRAPPER_1(fabsf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(fabs, x)
HC_MATH_WRAPPER_2(fdimf, x, y)
HC_MATH_WRAPPER_2(fdim, x, y)
HC_MATH_WRAPPER_1(floorf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(floor, x)
HC_MATH_WRAPPER_3(fmaf, x, y, z)
HC_MATH_WRAPPER_3(fma, x, y, z)
HC_MATH_WRAPPER_2(fmaxf, x, y)
HC_MATH_WRAPPER_2(fmax, x, y)
HC_MATH_WRAPPER_2(fminf, x, y)
HC_MATH_WRAPPER_2(fmin, x, y)
HC_MATH_WRAPPER_2(fmodf, x, y)
HC_MATH_WRAPPER_2(fmod, x, y)
HC_MATH_WRAPPER_2(hypotf, x, y)
HC_MATH_WRAPPER_2(hypot, x, y)
HC_MATH_WRAPPER_1(logf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(log, x)
HC_MATH_WRAPPER_1(log10f, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(log10, x)
HC_MATH_WRAPPER_1(log2f, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(log2, x)
HC_MATH_WRAPPER_1(log1pf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(log1p, x)
HC_MATH_WRAPPER_1(logbf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(logb, x)
HC_MATH_WRAPPER_1(nearbyintf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(nearbyint, x)
HC_MATH_WRAPPER_2(nextafterf, x, y)
HC_MATH_WRAPPER_2(nextafter, x, y)
HC_MATH_WRAPPER_2(powf, x, y)
HC_MATH_WRAPPER_FP_OVERLOAD_TTQ(pow,x,y)
//HC_MATH_WRAPPER_1(rcbrtf, x)
//HC_MATH_WRAPPER_1(rcbrt, x)
HC_MATH_WRAPPER_2(remainderf, x, y)
HC_MATH_WRAPPER_2(remainder, x, y)
HC_MATH_WRAPPER_1(roundf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(round, x)
KALMAR_MATH_WRAPPER_1(rsqrtf, x)
KALMAR_MATH_WRAPPER_FP_OVERLOAD_1(rsqrt, x)
HC_MATH_WRAPPER_2(scalbf, x, exp)
HC_MATH_WRAPPER_2(scalb, x, exp)
HC_MATH_WRAPPER_1(sinf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(sin, x)
HC_MATH_WRAPPER_1(sinhf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(sinh, x)
KALMAR_MATH_WRAPPER_1(sinpif, x)
KALMAR_MATH_WRAPPER_FP_OVERLOAD_1(sinpi, x)
HC_MATH_WRAPPER_1(sqrtf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(sqrt, x)
HC_MATH_WRAPPER_1(tgammaf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(tgamma, x)
HC_MATH_WRAPPER_1(tanf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(tan, x)
HC_MATH_WRAPPER_1(tanhf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(tanh, x)
HC_MATH_WRAPPER_1(truncf, x)
HC_MATH_WRAPPER_FP_OVERLOAD_1(trunc, x)
//HC_MATH_ALIAS_2(min, fmin, x, y)
//HC_MATH_ALIAS_2(max, fmax, x, y)
} // namespace

View File

@ -125,6 +125,7 @@ T atomic_compare_exchange( volatile T * const dest , const T & compare ,
//----------------------------------------------------------------------------
// GCC native CAS supports int, long, unsigned int, unsigned long.
// Intel native CAS support int and long with the same interface as GCC.
#if !defined(KOKKOS_ENABLE_ROCM_ATOMICS)
#if !defined(__CUDA_ARCH__) || defined(KOKKOS_IMPL_CUDA_CLANG_WORKAROUND)
#if defined(KOKKOS_ENABLE_GNU_ATOMICS) || defined(KOKKOS_ENABLE_INTEL_ATOMICS)
@ -280,6 +281,7 @@ T atomic_compare_exchange( volatile T * const dest, const T compare, const T val
#endif
#endif
#endif // !defined ROCM_ATOMICS
template <typename T>
KOKKOS_INLINE_FUNCTION

View File

@ -158,6 +158,7 @@ T atomic_fetch_add( volatile T * const dest ,
#endif
#endif
//----------------------------------------------------------------------------
#if !defined(KOKKOS_ENABLE_ROCM_ATOMICS)
#if !defined(__CUDA_ARCH__) || defined(KOKKOS_IMPL_CUDA_CLANG_WORKAROUND)
#if defined(KOKKOS_ENABLE_GNU_ATOMICS) || defined(KOKKOS_ENABLE_INTEL_ATOMICS)
@ -355,6 +356,7 @@ T atomic_fetch_add( volatile T * const dest , const T val )
#endif
#endif
#endif // !defined ROCM_ATOMICS
//----------------------------------------------------------------------------
// Simpler version of atomic_fetch_add without the fetch

View File

@ -135,6 +135,7 @@ T atomic_fetch_sub( volatile T * const dest ,
#endif
#endif
//----------------------------------------------------------------------------
#if !defined(KOKKOS_ENABLE_ROCM_ATOMICS)
#if !defined(__CUDA_ARCH__) || defined(KOKKOS_IMPL_CUDA_CLANG_WORKAROUND)
#if defined(KOKKOS_ENABLE_GNU_ATOMICS) || defined(KOKKOS_ENABLE_INTEL_ATOMICS)
@ -263,6 +264,8 @@ T atomic_fetch_sub( volatile T * const dest , const T val )
#endif
#endif
#endif // !defined ROCM_ATOMICS
// Simpler version of atomic_fetch_sub without the fetch
template <typename T>
KOKKOS_INLINE_FUNCTION

View File

@ -238,7 +238,7 @@ T atomic_fetch_oper( const Oper& op, volatile T * const dest ,
*dest = Oper::apply(return_val, val);
Impl::unlock_address_host_space( (void*) dest );
return return_val;
#else
#elif defined(KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_CUDA)
// This is a way to (hopefully) avoid dead lock in a warp
T return_val;
int done = 0;
@ -277,7 +277,7 @@ T atomic_oper_fetch( const Oper& op, volatile T * const dest ,
*dest = return_val;
Impl::unlock_address_host_space( (void*) dest );
return return_val;
#else
#elif defined(KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_CUDA)
T return_val;
// This is a way to (hopefully) avoid dead lock in a warp
int done = 0;

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