Homec4science
Diffusion lammps (lammm-master-deprecated) Browse

lammps/lib/gpu/lal_table_ext.cpp
48fbb5605f1blammm-master-deprecated

Last Change
Raw File

lal_table_ext.cpp
View Options

/***************************************************************************
lal_table.cpp
-------------------
Trung Dac Nguyen (ORNL)
Functions for LAMMPS access to table acceleration routines.
__________________________________________________________________________
This file is part of the LAMMPS Accelerator Library (LAMMPS_AL)
__________________________________________________________________________
begin :
email : nguyentd@ornl.gov
***************************************************************************/
#include <iostream>
#include <cassert>
#include <math.h>
#include "lal_table.h"
using namespace std;
using namespace LAMMPS_AL;
static Table<PRECISION,ACC_PRECISION> TBMF;
// ---------------------------------------------------------------------------
// Allocate memory on host and device and copy constants to device
// ---------------------------------------------------------------------------
int table_gpu_init(const int ntypes, double **cutsq, double ***table_coeffs,
double **table_data, 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,
int tabstyle, int ntables, int tablength) {
TBMF.clear();
gpu_mode=TBMF.device->gpu_mode();
double gpu_split=TBMF.device->particle_split();
int first_gpu=TBMF.device->first_device();
int last_gpu=TBMF.device->last_device();
int world_me=TBMF.device->world_me();
int gpu_rank=TBMF.device->gpu_rank();
int procs_per_gpu=TBMF.device->procs_per_gpu();
TBMF.device->init_message(screen,"table",first_gpu,last_gpu);
bool message=false;
if (TBMF.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=TBMF.init(ntypes, cutsq, table_coeffs, table_data,
special_lj, inum, nall, 300, maxspecial, cell_size,
gpu_split, screen, tabstyle, ntables, tablength);
TBMF.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=TBMF.init(ntypes, cutsq, table_coeffs, table_data,
special_lj, inum, nall, 300, maxspecial, cell_size,
gpu_split, screen, tabstyle, ntables, tablength);
TBMF.device->gpu_barrier();
if (message)
fprintf(screen,"Done.\n");
}
if (message)
fprintf(screen,"\n");
if (init_ok==0)
TBMF.estimate_gpu_overhead();
return init_ok;
}
void table_gpu_clear() {
TBMF.clear();
}
int ** table_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 TBMF.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 table_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) {
TBMF.compute(ago,inum_full,nall,host_x,host_type,ilist,numj,
firstneigh,eflag,vflag,eatom,vatom,host_start,cpu_time,success);
}
double table_gpu_bytes() {
return TBMF.host_memory_usage();
}
c4science · Help