mirror of https://github.com/lammps/lammps.git
165 lines
6.4 KiB
C++
165 lines
6.4 KiB
C++
/* ----------------------------------------------------------------------
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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 "pppm_gpu_memory.h"
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using namespace std;
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static PPPMGPUMemory<PRECISION,ACC_PRECISION,float,_lgpu_float4> PPPMF;
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static PPPMGPUMemory<PRECISION,ACC_PRECISION,double,_lgpu_double4> PPPMD;
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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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template <class grdtyp, class memtyp>
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grdtyp * pppm_gpu_init(memtyp &pppm, const int nlocal, const int nall,
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FILE *screen, const int order, const int nxlo_out,
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const int nylo_out, const int nzlo_out,
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const int nxhi_out, const int nyhi_out,
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const int nzhi_out, double **rho_coeff,
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grdtyp **vd_brick, const double slab_volfactor,
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const int nx_pppm, const int ny_pppm, const int nz_pppm,
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int &success) {
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pppm.clear(0.0);
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int first_gpu=pppm.device->first_device();
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int last_gpu=pppm.device->last_device();
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int world_me=pppm.device->world_me();
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int gpu_rank=pppm.device->gpu_rank();
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int procs_per_gpu=pppm.device->procs_per_gpu();
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pppm.device->init_message(screen,"pppm",first_gpu,last_gpu);
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bool message=false;
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if (pppm.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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success=0;
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grdtyp * host_brick=NULL;
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if (world_me==0)
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host_brick=pppm.init(nlocal,nall,screen,order,nxlo_out,nylo_out,nzlo_out,
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nxhi_out,nyhi_out,nzhi_out,rho_coeff,vd_brick,
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slab_volfactor,nx_pppm,ny_pppm,nz_pppm,success);
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pppm.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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host_brick=pppm.init(nlocal,nall,screen,order,nxlo_out,nylo_out,
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nzlo_out,nxhi_out,nyhi_out,nzhi_out,rho_coeff,
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vd_brick,slab_volfactor,nx_pppm,ny_pppm,nz_pppm,
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success);
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pppm.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 host_brick;
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}
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float * pppm_gpu_init_f(const int nlocal, const int nall, FILE *screen,
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const int order, const int nxlo_out,
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const int nylo_out, const int nzlo_out,
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const int nxhi_out, const int nyhi_out,
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const int nzhi_out, double **rho_coeff,
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float **vd_brick, const double slab_volfactor,
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const int nx_pppm, const int ny_pppm, const int nz_pppm,
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int &success) {
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float *b=pppm_gpu_init(PPPMF,nlocal,nall,screen,order,nxlo_out,nylo_out,
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nzlo_out,nxhi_out,nyhi_out,nzhi_out,rho_coeff,vd_brick,
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slab_volfactor,nx_pppm,ny_pppm,nz_pppm,success);
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PPPMF.device->set_single_precompute(&PPPMF);
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return b;
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}
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void pppm_gpu_clear_f(const double cpu_time) {
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PPPMF.clear(cpu_time);
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}
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int pppm_gpu_spread_f(const int ago, const int nlocal, const int nall,
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double **host_x, int *host_type, bool &success,
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double *host_q, double *boxlo, const double delxinv,
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const double delyinv, const double delzinv) {
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return PPPMF.spread(ago,nlocal,nall,host_x,host_type,success,host_q,boxlo,
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delxinv,delyinv,delzinv);
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}
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void pppm_gpu_interp_f(const float qqrd2e_scale) {
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return PPPMF.interp(qqrd2e_scale);
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}
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double pppm_gpu_bytes_f() {
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return PPPMF.host_memory_usage();
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}
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double * pppm_gpu_init_d(const int nlocal, const int nall, FILE *screen,
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const int order, const int nxlo_out,
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const int nylo_out, const int nzlo_out,
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const int nxhi_out, const int nyhi_out,
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const int nzhi_out, double **rho_coeff,
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double **vd_brick, const double slab_volfactor,
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const int nx_pppm, const int ny_pppm,
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const int nz_pppm, int &success) {
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double *b=pppm_gpu_init(PPPMD,nlocal,nall,screen,order,nxlo_out,nylo_out,
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nzlo_out,nxhi_out,nyhi_out,nzhi_out,rho_coeff,
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vd_brick,slab_volfactor,nx_pppm,ny_pppm,nz_pppm,
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success);
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PPPMF.device->set_double_precompute(&PPPMD);
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return b;
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}
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void pppm_gpu_clear_d(const double cpu_time) {
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PPPMD.clear(cpu_time);
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}
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int pppm_gpu_spread_d(const int ago, const int nlocal, const int nall,
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double **host_x, int *host_type, bool &success,
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double *host_q, double *boxlo, const double delxinv,
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const double delyinv, const double delzinv) {
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return PPPMD.spread(ago,nlocal,nall,host_x,host_type,success,host_q,boxlo,
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delxinv,delyinv,delzinv);
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}
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void pppm_gpu_interp_d(const double qqrd2e_scale) {
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return PPPMD.interp(qqrd2e_scale);
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}
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double pppm_gpu_bytes_d() {
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return PPPMD.host_memory_usage();
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}
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