forked from lijiext/lammps
git-svn-id: svn://svn.icms.temple.edu/lammps-ro/trunk@5545 f3b2605a-c512-4ea7-a41b-209d697bcdaa
This commit is contained in:
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9e1bc37b77
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/* ----------------------------------------------------------------------
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LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
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http://lammps.sandia.gov, Sandia National Laboratories
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Steve Plimpton, sjplimp@sandia.gov
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Copyright (2003) Sandia Corporation. Under the terms of Contract
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DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
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certain rights in this software. This software is distributed under
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the GNU General Public License.
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See the README file in the top-level LAMMPS directory.
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------------------------------------------------------------------------- */
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/* ----------------------------------------------------------------------
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Contributing authors: Mike Brown (ORNL), brownw@ornl.gov
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------------------------------------------------------------------------- */
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#include <iostream>
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#include <cassert>
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#include <math.h>
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#include "crml_gpu_memory.h"
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using namespace std;
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static CRML_GPU_Memory<PRECISION,ACC_PRECISION> CRMLMF;
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// ---------------------------------------------------------------------------
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// Allocate memory on host and device and copy constants to device
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// ---------------------------------------------------------------------------
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bool crml_gpu_init(const int ntypes, double cut_bothsq, double **host_lj1,
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double **host_lj2, double **host_lj3, double **host_lj4,
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double **offset, double *special_lj, const int inum,
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const int nall, const int max_nbors, const int maxspecial,
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const double cell_size, int &gpu_mode, FILE *screen,
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double host_cut_ljsq, double host_cut_coulsq,
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double *host_special_coul, const double qqrd2e,
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const double g_ewald, const double cut_lj_innersq,
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const double denom_lj, double **epsilon,
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double **sigma, const bool mix_arithmetic) {
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CRMLMF.clear();
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gpu_mode=CRMLMF.device->gpu_mode();
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double gpu_split=CRMLMF.device->particle_split();
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int first_gpu=CRMLMF.device->first_device();
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int last_gpu=CRMLMF.device->last_device();
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int world_me=CRMLMF.device->world_me();
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int gpu_rank=CRMLMF.device->gpu_rank();
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int procs_per_gpu=CRMLMF.device->procs_per_gpu();
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CRMLMF.device->init_message(screen,"lj/charmm/coul/long",first_gpu,last_gpu);
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bool message=false;
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if (CRMLMF.device->replica_me()==0 && screen)
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message=true;
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if (message) {
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fprintf(screen,"Initializing GPU and compiling on process 0...");
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fflush(screen);
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}
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if (world_me==0) {
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bool init_ok=CRMLMF.init(ntypes, cut_bothsq, host_lj1, host_lj2, host_lj3,
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host_lj4, offset, special_lj, inum, nall, 300,
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maxspecial, cell_size, gpu_split, screen,
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host_cut_ljsq, host_cut_coulsq, host_special_coul,
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qqrd2e, g_ewald, cut_lj_innersq, denom_lj,
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epsilon,sigma,mix_arithmetic);
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if (!init_ok)
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return false;
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}
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CRMLMF.device->world_barrier();
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if (message)
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fprintf(screen,"Done.\n");
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for (int i=0; i<procs_per_gpu; i++) {
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if (message) {
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if (last_gpu-first_gpu==0)
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fprintf(screen,"Initializing GPU %d on core %d...",first_gpu,i);
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else
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fprintf(screen,"Initializing GPUs %d-%d on core %d...",first_gpu,
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last_gpu,i);
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fflush(screen);
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}
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if (gpu_rank==i && world_me!=0) {
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bool init_ok=CRMLMF.init(ntypes, cut_bothsq, host_lj1, host_lj2, host_lj3,
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host_lj4, offset, special_lj, inum, nall, 300,
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maxspecial, cell_size, gpu_split,
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screen, host_cut_ljsq, host_cut_coulsq,
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host_special_coul, qqrd2e, g_ewald,
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cut_lj_innersq, denom_lj, epsilon, sigma,
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mix_arithmetic);
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if (!init_ok)
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return false;
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}
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CRMLMF.device->gpu_barrier();
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if (message)
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fprintf(screen,"Done.\n");
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}
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if (message)
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fprintf(screen,"\n");
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return true;
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}
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void crml_gpu_clear() {
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CRMLMF.clear();
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}
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int * crml_gpu_compute_n(const int timestep, const int ago, const int inum_full,
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const int nall, double **host_x, int *host_type,
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double *boxlo, double *boxhi, int *tag, int **nspecial,
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int **special, const bool eflag, const bool vflag,
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const bool eatom, const bool vatom, int &host_start,
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const double cpu_time, bool &success, double *host_q) {
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return CRMLMF.compute(timestep, ago, inum_full, nall, host_x, host_type, boxlo,
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boxhi, tag, nspecial, special, eflag, vflag, eatom,
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vatom, host_start, cpu_time, success, host_q);
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}
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void crml_gpu_compute(const int timestep, const int ago, const int inum_full,
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const int nall, double **host_x, int *host_type,
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int *ilist, int *numj, int **firstneigh,
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const bool eflag, const bool vflag, const bool eatom,
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const bool vatom, int &host_start, const double cpu_time,
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bool &success, double *host_q) {
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CRMLMF.compute(timestep,ago,inum_full,nall,host_x,host_type,ilist,numj,
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firstneigh,eflag,vflag,eatom,vatom,host_start,cpu_time,success,
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host_q);
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}
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double crml_gpu_bytes() {
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return CRMLMF.host_memory_usage();
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}
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@ -0,0 +1,169 @@
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/* ----------------------------------------------------------------------
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LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
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http://lammps.sandia.gov, Sandia National Laboratories
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Steve Plimpton, sjplimp@sandia.gov
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Copyright (2003) Sandia Corporation. Under the terms of Contract
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DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
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certain rights in this software. This software is distributed under
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the GNU General Public License.
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See the README file in the top-level LAMMPS directory.
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------------------------------------------------------------------------- */
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/* ----------------------------------------------------------------------
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Contributing authors: Mike Brown (ORNL), brownw@ornl.gov
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------------------------------------------------------------------------- */
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#ifdef USE_OPENCL
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#include "crml_gpu_cl.h"
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#else
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#include "crml_gpu_ptx.h"
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#endif
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#include "crml_gpu_memory.h"
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#include <cassert>
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#define CRML_GPU_MemoryT CRML_GPU_Memory<numtyp, acctyp>
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extern PairGPUDevice<PRECISION,ACC_PRECISION> pair_gpu_device;
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template <class numtyp, class acctyp>
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CRML_GPU_MemoryT::CRML_GPU_Memory() : ChargeGPUMemory<numtyp,acctyp>(),
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_allocated(false) {
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}
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template <class numtyp, class acctyp>
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CRML_GPU_MemoryT::~CRML_GPU_Memory() {
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clear();
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}
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template <class numtyp, class acctyp>
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int CRML_GPU_MemoryT::bytes_per_atom(const int max_nbors) const {
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return this->bytes_per_atom_atomic(max_nbors);
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}
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template <class numtyp, class acctyp>
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bool CRML_GPU_MemoryT::init(const int ntypes,
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double host_cut_bothsq, double **host_lj1,
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double **host_lj2, double **host_lj3,
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double **host_lj4, double **host_offset,
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double *host_special_lj, const int nlocal,
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const int nall, const int max_nbors,
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const int maxspecial, const double cell_size,
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const double gpu_split, FILE *_screen,
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double host_cut_ljsq, const double host_cut_coulsq,
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double *host_special_coul, const double qqrd2e,
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const double g_ewald, const double cut_lj_innersq,
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const double denom_lj, double **epsilon,
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double **sigma, const bool mix_arithmetic) {
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this->init_atomic(nlocal,nall,max_nbors,maxspecial,cell_size,gpu_split,
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_screen,crml_gpu_kernel);
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// If atom type constants fit in shared memory use fast kernel
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int lj_types=ntypes;
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shared_types=false;
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if (this->_block_size>=64 && mix_arithmetic)
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shared_types=true;
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_lj_types=lj_types;
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// Allocate a host write buffer for data initialization
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int h_size=lj_types*lj_types;
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if (h_size<MAX_BIO_SHARED_TYPES)
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h_size=MAX_BIO_SHARED_TYPES;
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UCL_H_Vec<numtyp> host_write(h_size*32,*(this->ucl_device),
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UCL_WRITE_OPTIMIZED);
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for (int i=0; i<h_size*32; i++)
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host_write[i]=0.0;
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lj1.alloc(lj_types*lj_types,*(this->ucl_device),UCL_READ_ONLY);
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this->atom->type_pack4(ntypes,lj_types,lj1,host_write,host_lj1,host_lj2,
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host_lj3,host_lj4);
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ljd.alloc(MAX_BIO_SHARED_TYPES,*(this->ucl_device),UCL_READ_ONLY);
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this->atom->self_pack2(ntypes,ljd,host_write,epsilon,sigma);
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sp_lj.alloc(8,*(this->ucl_device),UCL_READ_ONLY);
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for (int i=0; i<4; i++) {
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host_write[i]=host_special_lj[i];
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host_write[i+4]=host_special_coul[i];
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}
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ucl_copy(sp_lj,host_write,8,false);
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_cut_bothsq = host_cut_bothsq;
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_cut_coulsq = host_cut_coulsq;
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_cut_ljsq = host_cut_ljsq;
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_cut_lj_innersq = cut_lj_innersq;
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_qqrd2e=qqrd2e;
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_g_ewald=g_ewald;
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_denom_lj=denom_lj;
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_allocated=true;
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this->_max_bytes=lj1.row_bytes()+ljd.row_bytes()+sp_lj.row_bytes();
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return true;
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}
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template <class numtyp, class acctyp>
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void CRML_GPU_MemoryT::clear() {
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if (!_allocated)
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return;
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_allocated=false;
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lj1.clear();
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ljd.clear();
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sp_lj.clear();
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this->clear_atomic();
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}
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template <class numtyp, class acctyp>
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double CRML_GPU_MemoryT::host_memory_usage() const {
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return this->host_memory_usage_atomic()+sizeof(CRML_GPU_Memory<numtyp,acctyp>);
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}
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// ---------------------------------------------------------------------------
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// Calculate energies, forces, and torques
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// ---------------------------------------------------------------------------
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template <class numtyp, class acctyp>
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void CRML_GPU_MemoryT::loop(const bool _eflag, const bool _vflag) {
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// Compute the block size and grid size to keep all cores busy
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const int BX=this->block_size();
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int eflag, vflag;
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if (_eflag)
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eflag=1;
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else
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eflag=0;
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if (_vflag)
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vflag=1;
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else
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vflag=0;
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int GX=static_cast<int>(ceil(static_cast<double>(this->atom->inum())/BX));
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int ainum=this->atom->inum();
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int anall=this->atom->nall();
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int nbor_pitch=this->nbor->nbor_pitch();
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this->time_pair.start();
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if (shared_types) {
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this->k_pair_fast.set_size(GX,BX);
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this->k_pair_fast.run(&this->atom->dev_x.begin(), &ljd.begin(),
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&sp_lj.begin(), &this->nbor->dev_nbor.begin(),
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&this->atom->dev_ans.begin(),
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&this->atom->dev_engv.begin(), &eflag, &vflag,
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&ainum, &anall, &nbor_pitch,
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&this->atom->dev_q.begin(), &_cut_coulsq,
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&_qqrd2e, &_g_ewald, &_denom_lj, &_cut_bothsq,
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&_cut_ljsq, &_cut_lj_innersq);
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} else {
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this->k_pair.set_size(GX,BX);
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this->k_pair.run(&this->atom->dev_x.begin(), &lj1.begin(),
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&_lj_types, &sp_lj.begin(), &this->nbor->dev_nbor.begin(),
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&this->atom->dev_ans.begin(),
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&this->atom->dev_engv.begin(), &eflag, &vflag, &ainum,
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&anall, &nbor_pitch, &this->atom->dev_q.begin(),
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&_cut_coulsq, &_qqrd2e, &_g_ewald, &_denom_lj,
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&_cut_bothsq, &_cut_ljsq, &_cut_lj_innersq);
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}
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this->time_pair.stop();
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}
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template class CRML_GPU_Memory<PRECISION,ACC_PRECISION>;
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@ -0,0 +1,79 @@
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/* ----------------------------------------------------------------------
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LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
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http://lammps.sandia.gov, Sandia National Laboratories
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Steve Plimpton, sjplimp@sandia.gov
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Copyright (2003) Sandia Corporation. Under the terms of Contract
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DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
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certain rights in this software. This software is distributed under
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the GNU General Public License.
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See the README file in the top-level LAMMPS directory.
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------------------------------------------------------------------------- */
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/* ----------------------------------------------------------------------
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Contributing authors: Mike Brown (ORNL), brownw@ornl.gov
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------------------------------------------------------------------------- */
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#ifndef CRML_GPU_MEMORY_H
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#define CRML_GPU_MEMORY_H
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#include "charge_gpu_memory.h"
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template <class numtyp, class acctyp>
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class CRML_GPU_Memory : public ChargeGPUMemory<numtyp, acctyp> {
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public:
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CRML_GPU_Memory();
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~CRML_GPU_Memory();
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/// Clear any previous data and set up for a new LAMMPS run
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/** \param max_nbors initial number of rows in the neighbor matrix
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* \param cell_size cutoff + skin
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* \param gpu_split fraction of particles handled by device **/
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bool init(const int ntypes, double host_cut_bothsq,
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double **host_lj1, double **host_lj2, double **host_lj3,
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double **host_lj4, double **host_offset, double *host_special_lj,
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const int nlocal, const int nall, const int max_nbors,
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const int maxspecial, const double cell_size,
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const double gpu_split, FILE *screen, double host_cut_ljsq,
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const double host_cut_coulsq, double *host_special_coul,
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const double qqrd2e, const double g_ewald,
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const double cut_lj_innersq, const double denom_lj,
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double **epsilon, double **sigma, const bool mix_arithmetic);
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/// Clear all host and device data
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/** \note This is called at the beginning of the init() routine **/
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void clear();
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/// Returns memory usage on device per atom
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int bytes_per_atom(const int max_nbors) const;
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/// Total host memory used by library for pair style
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double host_memory_usage() const;
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// --------------------------- TYPE DATA --------------------------
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/// x = lj1, y = lj2, z = lj3, w = lj4
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UCL_D_Vec<numtyp4> lj1;
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/// x = epsilon, y = sigma
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UCL_D_Vec<numtyp2> ljd;
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/// Special LJ values [0-3] and Special Coul values [4-7]
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UCL_D_Vec<numtyp> sp_lj;
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/// If atom type constants fit in shared memory, use fast kernels
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bool shared_types;
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/// Number of atom types
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int _lj_types;
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numtyp _qqrd2e, _g_ewald, _denom_lj;
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numtyp _cut_coulsq, _cut_bothsq, _cut_ljsq, _cut_lj_innersq;
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private:
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bool _allocated;
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void loop(const bool _eflag, const bool _vflag);
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};
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#endif
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