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lammps/lib/gpu/cmm_cut_gpu.cpp
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cmm_cut_gpu.cpp
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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 "cmm_cut_gpu_memory.h"
using namespace std;
static CMM_GPU_Memory<PRECISION,ACC_PRECISION> CMMMF;
// ---------------------------------------------------------------------------
// Allocate memory on host and device and copy constants to device
// ---------------------------------------------------------------------------
int cmm_gpu_init(const int ntypes, double **cutsq, int **cg_types,
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) {
CMMMF.clear();
gpu_mode=CMMMF.device->gpu_mode();
double gpu_split=CMMMF.device->particle_split();
int first_gpu=CMMMF.device->first_device();
int last_gpu=CMMMF.device->last_device();
int world_me=CMMMF.device->world_me();
int gpu_rank=CMMMF.device->gpu_rank();
int procs_per_gpu=CMMMF.device->procs_per_gpu();
CMMMF.device->init_message(screen,"cg/cmm",first_gpu,last_gpu);
bool message=false;
if (CMMMF.device->replica_me()==0 && screen)
message=true;
if (message) {
fprintf(screen,"Initializing GPU and compiling on process 0...");
fflush(screen);
}
int init_ok=0;
if (world_me==0)
init_ok=CMMMF.init(ntypes,cutsq,cg_types,host_lj1,host_lj2,host_lj3,
host_lj4, offset, special_lj, inum, nall, 300,
maxspecial, cell_size, gpu_split, screen);
CMMMF.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)
init_ok=CMMMF.init(ntypes,cutsq,cg_types,host_lj1,host_lj2,host_lj3,
host_lj4, offset, special_lj, inum, nall, 300,
maxspecial, cell_size, gpu_split, screen);
CMMMF.device->gpu_barrier();
if (message)
fprintf(screen,"Done.\n");
}
if (message)
fprintf(screen,"\n");
if (init_ok==0)
CMMMF.estimate_gpu_overhead();
return init_ok;
}
void cmm_gpu_clear() {
CMMMF.clear();
}
int** cmm_gpu_compute_n(const int ago, const int inum_full,
const int nall, double **host_x, int *host_type,
double *sublo, double *subhi, int *tag, int **nspecial,
int **special, const bool eflag, const bool vflag,
const bool eatom, const bool vatom, int &host_start,
int **ilist, int **jnum, const double cpu_time,
bool &success) {
return CMMMF.compute(ago, inum_full, nall, host_x, host_type, sublo,
subhi, tag, nspecial, special, eflag, vflag, eatom,
vatom, host_start, ilist, jnum, cpu_time, success);
}
void cmm_gpu_compute(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) {
CMMMF.compute(ago,inum_full,nall,host_x,host_type,ilist,numj,
firstneigh,eflag,vflag,eatom,vatom,host_start,cpu_time,success);
}
double cmm_gpu_bytes() {
return CMMMF.host_memory_usage();
}
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