git-svn-id: svn://svn.icms.temple.edu/lammps-ro/trunk@5545 f3b2605a-c512-4ea7-a41b-209d697bcdaa

This commit is contained in:
sjplimp 2011-01-12 21:41:35 +00:00
parent 9e1bc37b77
commit a499b28469
3 changed files with 383 additions and 0 deletions

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/* ----------------------------------------------------------------------
LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
http://lammps.sandia.gov, Sandia National Laboratories
Steve Plimpton, sjplimp@sandia.gov
Copyright (2003) Sandia Corporation. Under the terms of Contract
DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
certain rights in this software. This software is distributed under
the GNU General Public License.
See the README file in the top-level LAMMPS directory.
------------------------------------------------------------------------- */
/* ----------------------------------------------------------------------
Contributing authors: Mike Brown (ORNL), brownw@ornl.gov
------------------------------------------------------------------------- */
#include <iostream>
#include <cassert>
#include <math.h>
#include "crml_gpu_memory.h"
using namespace std;
static CRML_GPU_Memory<PRECISION,ACC_PRECISION> CRMLMF;
// ---------------------------------------------------------------------------
// Allocate memory on host and device and copy constants to device
// ---------------------------------------------------------------------------
bool crml_gpu_init(const int ntypes, double cut_bothsq, double **host_lj1,
double **host_lj2, double **host_lj3, double **host_lj4,
double **offset, double *special_lj, const int inum,
const int nall, const int max_nbors, const int maxspecial,
const double cell_size, int &gpu_mode, FILE *screen,
double host_cut_ljsq, double host_cut_coulsq,
double *host_special_coul, const double qqrd2e,
const double g_ewald, const double cut_lj_innersq,
const double denom_lj, double **epsilon,
double **sigma, const bool mix_arithmetic) {
CRMLMF.clear();
gpu_mode=CRMLMF.device->gpu_mode();
double gpu_split=CRMLMF.device->particle_split();
int first_gpu=CRMLMF.device->first_device();
int last_gpu=CRMLMF.device->last_device();
int world_me=CRMLMF.device->world_me();
int gpu_rank=CRMLMF.device->gpu_rank();
int procs_per_gpu=CRMLMF.device->procs_per_gpu();
CRMLMF.device->init_message(screen,"lj/charmm/coul/long",first_gpu,last_gpu);
bool message=false;
if (CRMLMF.device->replica_me()==0 && screen)
message=true;
if (message) {
fprintf(screen,"Initializing GPU and compiling on process 0...");
fflush(screen);
}
if (world_me==0) {
bool init_ok=CRMLMF.init(ntypes, cut_bothsq, host_lj1, host_lj2, host_lj3,
host_lj4, offset, special_lj, inum, nall, 300,
maxspecial, cell_size, gpu_split, screen,
host_cut_ljsq, host_cut_coulsq, host_special_coul,
qqrd2e, g_ewald, cut_lj_innersq, denom_lj,
epsilon,sigma,mix_arithmetic);
if (!init_ok)
return false;
}
CRMLMF.device->world_barrier();
if (message)
fprintf(screen,"Done.\n");
for (int i=0; i<procs_per_gpu; i++) {
if (message) {
if (last_gpu-first_gpu==0)
fprintf(screen,"Initializing GPU %d on core %d...",first_gpu,i);
else
fprintf(screen,"Initializing GPUs %d-%d on core %d...",first_gpu,
last_gpu,i);
fflush(screen);
}
if (gpu_rank==i && world_me!=0) {
bool init_ok=CRMLMF.init(ntypes, cut_bothsq, host_lj1, host_lj2, host_lj3,
host_lj4, offset, special_lj, inum, nall, 300,
maxspecial, cell_size, gpu_split,
screen, host_cut_ljsq, host_cut_coulsq,
host_special_coul, qqrd2e, g_ewald,
cut_lj_innersq, denom_lj, epsilon, sigma,
mix_arithmetic);
if (!init_ok)
return false;
}
CRMLMF.device->gpu_barrier();
if (message)
fprintf(screen,"Done.\n");
}
if (message)
fprintf(screen,"\n");
return true;
}
void crml_gpu_clear() {
CRMLMF.clear();
}
int * crml_gpu_compute_n(const int timestep, const int ago, const int inum_full,
const int nall, double **host_x, int *host_type,
double *boxlo, double *boxhi, int *tag, int **nspecial,
int **special, const bool eflag, const bool vflag,
const bool eatom, const bool vatom, int &host_start,
const double cpu_time, bool &success, double *host_q) {
return CRMLMF.compute(timestep, ago, inum_full, nall, host_x, host_type, boxlo,
boxhi, tag, nspecial, special, eflag, vflag, eatom,
vatom, host_start, cpu_time, success, host_q);
}
void crml_gpu_compute(const int timestep, const int ago, const int inum_full,
const int nall, double **host_x, int *host_type,
int *ilist, int *numj, int **firstneigh,
const bool eflag, const bool vflag, const bool eatom,
const bool vatom, int &host_start, const double cpu_time,
bool &success, double *host_q) {
CRMLMF.compute(timestep,ago,inum_full,nall,host_x,host_type,ilist,numj,
firstneigh,eflag,vflag,eatom,vatom,host_start,cpu_time,success,
host_q);
}
double crml_gpu_bytes() {
return CRMLMF.host_memory_usage();
}

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/* ----------------------------------------------------------------------
LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
http://lammps.sandia.gov, Sandia National Laboratories
Steve Plimpton, sjplimp@sandia.gov
Copyright (2003) Sandia Corporation. Under the terms of Contract
DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
certain rights in this software. This software is distributed under
the GNU General Public License.
See the README file in the top-level LAMMPS directory.
------------------------------------------------------------------------- */
/* ----------------------------------------------------------------------
Contributing authors: Mike Brown (ORNL), brownw@ornl.gov
------------------------------------------------------------------------- */
#ifdef USE_OPENCL
#include "crml_gpu_cl.h"
#else
#include "crml_gpu_ptx.h"
#endif
#include "crml_gpu_memory.h"
#include <cassert>
#define CRML_GPU_MemoryT CRML_GPU_Memory<numtyp, acctyp>
extern PairGPUDevice<PRECISION,ACC_PRECISION> pair_gpu_device;
template <class numtyp, class acctyp>
CRML_GPU_MemoryT::CRML_GPU_Memory() : ChargeGPUMemory<numtyp,acctyp>(),
_allocated(false) {
}
template <class numtyp, class acctyp>
CRML_GPU_MemoryT::~CRML_GPU_Memory() {
clear();
}
template <class numtyp, class acctyp>
int CRML_GPU_MemoryT::bytes_per_atom(const int max_nbors) const {
return this->bytes_per_atom_atomic(max_nbors);
}
template <class numtyp, class acctyp>
bool CRML_GPU_MemoryT::init(const int ntypes,
double host_cut_bothsq, double **host_lj1,
double **host_lj2, double **host_lj3,
double **host_lj4, double **host_offset,
double *host_special_lj, const int nlocal,
const int nall, const int max_nbors,
const int maxspecial, const double cell_size,
const double gpu_split, FILE *_screen,
double host_cut_ljsq, const double host_cut_coulsq,
double *host_special_coul, const double qqrd2e,
const double g_ewald, const double cut_lj_innersq,
const double denom_lj, double **epsilon,
double **sigma, const bool mix_arithmetic) {
this->init_atomic(nlocal,nall,max_nbors,maxspecial,cell_size,gpu_split,
_screen,crml_gpu_kernel);
// If atom type constants fit in shared memory use fast kernel
int lj_types=ntypes;
shared_types=false;
if (this->_block_size>=64 && mix_arithmetic)
shared_types=true;
_lj_types=lj_types;
// Allocate a host write buffer for data initialization
int h_size=lj_types*lj_types;
if (h_size<MAX_BIO_SHARED_TYPES)
h_size=MAX_BIO_SHARED_TYPES;
UCL_H_Vec<numtyp> host_write(h_size*32,*(this->ucl_device),
UCL_WRITE_OPTIMIZED);
for (int i=0; i<h_size*32; i++)
host_write[i]=0.0;
lj1.alloc(lj_types*lj_types,*(this->ucl_device),UCL_READ_ONLY);
this->atom->type_pack4(ntypes,lj_types,lj1,host_write,host_lj1,host_lj2,
host_lj3,host_lj4);
ljd.alloc(MAX_BIO_SHARED_TYPES,*(this->ucl_device),UCL_READ_ONLY);
this->atom->self_pack2(ntypes,ljd,host_write,epsilon,sigma);
sp_lj.alloc(8,*(this->ucl_device),UCL_READ_ONLY);
for (int i=0; i<4; i++) {
host_write[i]=host_special_lj[i];
host_write[i+4]=host_special_coul[i];
}
ucl_copy(sp_lj,host_write,8,false);
_cut_bothsq = host_cut_bothsq;
_cut_coulsq = host_cut_coulsq;
_cut_ljsq = host_cut_ljsq;
_cut_lj_innersq = cut_lj_innersq;
_qqrd2e=qqrd2e;
_g_ewald=g_ewald;
_denom_lj=denom_lj;
_allocated=true;
this->_max_bytes=lj1.row_bytes()+ljd.row_bytes()+sp_lj.row_bytes();
return true;
}
template <class numtyp, class acctyp>
void CRML_GPU_MemoryT::clear() {
if (!_allocated)
return;
_allocated=false;
lj1.clear();
ljd.clear();
sp_lj.clear();
this->clear_atomic();
}
template <class numtyp, class acctyp>
double CRML_GPU_MemoryT::host_memory_usage() const {
return this->host_memory_usage_atomic()+sizeof(CRML_GPU_Memory<numtyp,acctyp>);
}
// ---------------------------------------------------------------------------
// Calculate energies, forces, and torques
// ---------------------------------------------------------------------------
template <class numtyp, class acctyp>
void CRML_GPU_MemoryT::loop(const bool _eflag, const bool _vflag) {
// Compute the block size and grid size to keep all cores busy
const int BX=this->block_size();
int eflag, vflag;
if (_eflag)
eflag=1;
else
eflag=0;
if (_vflag)
vflag=1;
else
vflag=0;
int GX=static_cast<int>(ceil(static_cast<double>(this->atom->inum())/BX));
int ainum=this->atom->inum();
int anall=this->atom->nall();
int nbor_pitch=this->nbor->nbor_pitch();
this->time_pair.start();
if (shared_types) {
this->k_pair_fast.set_size(GX,BX);
this->k_pair_fast.run(&this->atom->dev_x.begin(), &ljd.begin(),
&sp_lj.begin(), &this->nbor->dev_nbor.begin(),
&this->atom->dev_ans.begin(),
&this->atom->dev_engv.begin(), &eflag, &vflag,
&ainum, &anall, &nbor_pitch,
&this->atom->dev_q.begin(), &_cut_coulsq,
&_qqrd2e, &_g_ewald, &_denom_lj, &_cut_bothsq,
&_cut_ljsq, &_cut_lj_innersq);
} else {
this->k_pair.set_size(GX,BX);
this->k_pair.run(&this->atom->dev_x.begin(), &lj1.begin(),
&_lj_types, &sp_lj.begin(), &this->nbor->dev_nbor.begin(),
&this->atom->dev_ans.begin(),
&this->atom->dev_engv.begin(), &eflag, &vflag, &ainum,
&anall, &nbor_pitch, &this->atom->dev_q.begin(),
&_cut_coulsq, &_qqrd2e, &_g_ewald, &_denom_lj,
&_cut_bothsq, &_cut_ljsq, &_cut_lj_innersq);
}
this->time_pair.stop();
}
template class CRML_GPU_Memory<PRECISION,ACC_PRECISION>;

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/* ----------------------------------------------------------------------
LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
http://lammps.sandia.gov, Sandia National Laboratories
Steve Plimpton, sjplimp@sandia.gov
Copyright (2003) Sandia Corporation. Under the terms of Contract
DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
certain rights in this software. This software is distributed under
the GNU General Public License.
See the README file in the top-level LAMMPS directory.
------------------------------------------------------------------------- */
/* ----------------------------------------------------------------------
Contributing authors: Mike Brown (ORNL), brownw@ornl.gov
------------------------------------------------------------------------- */
#ifndef CRML_GPU_MEMORY_H
#define CRML_GPU_MEMORY_H
#include "charge_gpu_memory.h"
template <class numtyp, class acctyp>
class CRML_GPU_Memory : public ChargeGPUMemory<numtyp, acctyp> {
public:
CRML_GPU_Memory();
~CRML_GPU_Memory();
/// Clear any previous data and set up for a new LAMMPS run
/** \param max_nbors initial number of rows in the neighbor matrix
* \param cell_size cutoff + skin
* \param gpu_split fraction of particles handled by device **/
bool init(const int ntypes, double host_cut_bothsq,
double **host_lj1, double **host_lj2, double **host_lj3,
double **host_lj4, double **host_offset, double *host_special_lj,
const int nlocal, const int nall, const int max_nbors,
const int maxspecial, const double cell_size,
const double gpu_split, FILE *screen, double host_cut_ljsq,
const double host_cut_coulsq, double *host_special_coul,
const double qqrd2e, const double g_ewald,
const double cut_lj_innersq, const double denom_lj,
double **epsilon, double **sigma, const bool mix_arithmetic);
/// Clear all host and device data
/** \note This is called at the beginning of the init() routine **/
void clear();
/// Returns memory usage on device per atom
int bytes_per_atom(const int max_nbors) const;
/// Total host memory used by library for pair style
double host_memory_usage() const;
// --------------------------- TYPE DATA --------------------------
/// x = lj1, y = lj2, z = lj3, w = lj4
UCL_D_Vec<numtyp4> lj1;
/// x = epsilon, y = sigma
UCL_D_Vec<numtyp2> ljd;
/// Special LJ values [0-3] and Special Coul values [4-7]
UCL_D_Vec<numtyp> sp_lj;
/// If atom type constants fit in shared memory, use fast kernels
bool shared_types;
/// Number of atom types
int _lj_types;
numtyp _qqrd2e, _g_ewald, _denom_lj;
numtyp _cut_coulsq, _cut_bothsq, _cut_ljsq, _cut_lj_innersq;
private:
bool _allocated;
void loop(const bool _eflag, const bool _vflag);
};
#endif