forked from lijiext/lammps
124 lines
4.1 KiB
C++
124 lines
4.1 KiB
C++
/***************************************************************************
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coul_long_ext.cpp
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-------------------
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Axel Kohlmeyer (Temple)
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Functions for LAMMPS access to coul/long acceleration routines.
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__________________________________________________________________________
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This file is part of the LAMMPS Accelerator Library (LAMMPS_AL)
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__________________________________________________________________________
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begin : July 2011
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email : a.kohlmeyer@temple.edu
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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 "lal_coul_long.h"
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using namespace std;
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using namespace LAMMPS_AL;
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static CoulLong<PRECISION,ACC_PRECISION> CLMF;
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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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int cl_gpu_init(const int inum, const int nall, const int max_nbors,
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const int maxspecial, const double cell_size, int &gpu_mode,
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FILE *screen, double host_cut_coulsq, double *host_special_coul,
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const double qqrd2e, const double g_ewald) {
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CLMF.clear();
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gpu_mode=CLMF.device->gpu_mode();
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double gpu_split=CLMF.device->particle_split();
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int first_gpu=CLMF.device->first_device();
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int last_gpu=CLMF.device->last_device();
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int world_me=CLMF.device->world_me();
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int gpu_rank=CLMF.device->gpu_rank();
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int procs_per_gpu=CLMF.device->procs_per_gpu();
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CLMF.device->init_message(screen,"coul/long",first_gpu,last_gpu);
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bool message=false;
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if (CLMF.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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int init_ok=0;
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if (world_me==0)
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init_ok=CLMF.init(inum, nall, 300, maxspecial, cell_size, gpu_split,
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screen, host_cut_coulsq, host_special_coul, qqrd2e,
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g_ewald);
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CLMF.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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init_ok=CLMF.init(inum, nall, 300, maxspecial, cell_size, gpu_split,
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screen, host_cut_coulsq, host_special_coul,
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qqrd2e, g_ewald);
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CLMF.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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if (init_ok==0)
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CLMF.estimate_gpu_overhead();
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return init_ok;
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}
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void cl_gpu_clear() {
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CLMF.clear();
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}
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int** cl_gpu_compute_n(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 *sublo, double *subhi, 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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int **ilist, int **jnum, const double cpu_time,
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bool &success, double *host_q, double *boxlo,
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double *prd) {
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return CLMF.compute(ago, inum_full, nall, host_x, host_type, sublo,
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subhi, tag, nspecial, special, eflag, vflag, eatom,
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vatom, host_start, ilist, jnum, cpu_time, success,
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host_q, boxlo, prd);
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}
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void cl_gpu_compute(const int ago, const int inum_full, const int nall,
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double **host_x, int *host_type, int *ilist, int *numj,
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int **firstneigh, 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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const int nlocal, double *boxlo, double *prd) {
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CLMF.compute(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,nlocal,boxlo,prd);
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}
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double cl_gpu_bytes() {
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return CLMF.host_memory_usage();
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}
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