lammps/lib/gpu/lal_dpd_ext.cpp

134 lines
5.1 KiB
C++

/***************************************************************************
dpd_ext.cpp
-------------------
Trung Dac Nguyen (ORNL)
Functions for LAMMPS access to dpd acceleration routines.
__________________________________________________________________________
This file is part of the LAMMPS Accelerator Library (LAMMPS_AL)
__________________________________________________________________________
begin : Jan 15, 2014
email : nguyentd@ornl.gov
***************************************************************************/
#include <iostream>
#include <cassert>
#include <math.h>
#include "lal_dpd.h"
using namespace std;
using namespace LAMMPS_AL;
static DPD<PRECISION,ACC_PRECISION> DPDMF;
// ---------------------------------------------------------------------------
// Allocate memory on host and device and copy constants to device
// ---------------------------------------------------------------------------
int dpd_gpu_init(const int ntypes, double **cutsq, double **host_a0,
double **host_gamma, double **host_sigma, double **host_cut,
double *special_lj, bool tstat_only, const int inum,
const int nall, const int max_nbors, const int maxspecial,
const double cell_size, int &gpu_mode, FILE *screen) {
DPDMF.clear();
gpu_mode=DPDMF.device->gpu_mode();
double gpu_split=DPDMF.device->particle_split();
int first_gpu=DPDMF.device->first_device();
int last_gpu=DPDMF.device->last_device();
int world_me=DPDMF.device->world_me();
int gpu_rank=DPDMF.device->gpu_rank();
int procs_per_gpu=DPDMF.device->procs_per_gpu();
DPDMF.device->init_message(screen,"dpd",first_gpu,last_gpu);
bool message=false;
if (DPDMF.device->replica_me()==0 && screen)
message=true;
if (message) {
fprintf(screen,"Initializing Device and compiling on process 0...");
fflush(screen);
}
int init_ok=0;
if (world_me==0)
init_ok=DPDMF.init(ntypes, cutsq, host_a0, host_gamma, host_sigma,
host_cut, special_lj, tstat_only, inum, nall, 300,
maxspecial, cell_size, gpu_split, screen);
DPDMF.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 Device %d on core %d...",first_gpu,i);
else
fprintf(screen,"Initializing Devices %d-%d on core %d...",first_gpu,
last_gpu,i);
fflush(screen);
}
if (gpu_rank==i && world_me!=0)
init_ok=DPDMF.init(ntypes, cutsq, host_a0, host_gamma, host_sigma,
host_cut, special_lj, tstat_only, inum, nall, 300,
maxspecial, cell_size, gpu_split, screen);
DPDMF.device->gpu_barrier();
if (message)
fprintf(screen,"Done.\n");
}
if (message)
fprintf(screen,"\n");
if (init_ok==0)
DPDMF.estimate_gpu_overhead();
return init_ok;
}
void dpd_gpu_clear() {
DPDMF.clear();
}
int ** dpd_gpu_compute_n(const int ago, const int inum_full, const int nall,
double **host_x, int *host_type, double *sublo,
double *subhi, tagint *tag, int **nspecial,
tagint **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,
double **host_v, const double dtinvsqrt,
const int seed, const int timestep,
double *boxlo, double *prd) {
return DPDMF.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,
host_v, dtinvsqrt, seed, timestep, boxlo, prd);
}
void dpd_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, tagint *tag,
double **host_v, const double dtinvsqrt,
const int seed, const int timestep,
const int nlocal, double *boxlo, double *prd) {
DPDMF.compute(ago, inum_full, nall, host_x, host_type, ilist, numj,
firstneigh, eflag, vflag, eatom, vatom, host_start, cpu_time, success,
tag, host_v, dtinvsqrt, seed, timestep, nlocal, boxlo, prd);
}
void dpd_gpu_update_coeff(int ntypes, double **host_a0, double **host_gamma,
double **host_sigma, double **host_cut)
{
DPDMF.update_coeff(ntypes,host_a0,host_gamma,host_sigma,host_cut);
}
double dpd_gpu_bytes() {
return DPDMF.host_memory_usage();
}