Page Menu
Home
c4science
Search
Configure Global Search
Log In
Files
F91986184
cg_cmm_long.cpp
No One
Temporary
Actions
Download File
Edit File
Delete File
View Transforms
Subscribe
Mute Notifications
Award Token
Subscribers
None
File Metadata
Details
File Info
Storage
Attached
Created
Sat, Nov 16, 09:39
Size
6 KB
Mime Type
text/x-c++
Expires
Mon, Nov 18, 09:39 (1 d, 23 h)
Engine
blob
Format
Raw Data
Handle
22356664
Attached To
rLAMMPS lammps
cg_cmm_long.cpp
View Options
/* ----------------------------------------------------------------------
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
------------------------------------------------------------------------- */
#ifdef USE_OPENCL
#include "cg_cmm_long_ext_cl.h"
#else
#include "cg_cmm_long_ext_ptx.h"
#endif
#include "cg_cmm_long.h"
#include <cassert>
#define CMML_GPU_MemoryT CMML_GPU_Memory<numtyp, acctyp>
extern Device<PRECISION,ACC_PRECISION> device;
template <class numtyp, class acctyp>
CMML_GPU_MemoryT::CMML_GPU_Memory() : BaseCharge<numtyp,acctyp>(),
_allocated(false) {
}
template <class numtyp, class acctyp>
CMML_GPU_MemoryT::~CMML_GPU_Memory() {
clear();
}
template <class numtyp, class acctyp>
int CMML_GPU_MemoryT::bytes_per_atom(const int max_nbors) const {
return this->bytes_per_atom_atomic(max_nbors);
}
template <class numtyp, class acctyp>
int CMML_GPU_MemoryT::init(const int ntypes, double **host_cutsq,
int **host_cg_type, double **host_lj1,
double **host_lj2, double **host_lj3,
double **host_lj4, double **host_offset,
double *host_special_lj, const int nlocal,
const int nall, const int max_nbors,
const int maxspecial, const double cell_size,
const double gpu_split, FILE *_screen,
double **host_cut_ljsq,
const double host_cut_coulsq,
double *host_special_coul, const double qqrd2e,
const double g_ewald) {
int success;
success=this->init_atomic(nlocal,nall,max_nbors,maxspecial,cell_size,gpu_split,
_screen,cg_cmm_long);
if (success!=0)
return success;
// If atom type constants fit in shared memory use fast kernel
int lj_types=ntypes;
shared_types=false;
int max_shared_types=this->device->max_shared_types();
if (lj_types<=max_shared_types && this->_block_size>=max_shared_types) {
lj_types=max_shared_types;
shared_types=true;
}
_lj_types=lj_types;
// Allocate a host write buffer for data initialization
UCL_H_Vec<numtyp> host_write(lj_types*lj_types*32,*(this->ucl_device),
UCL_WRITE_OPTIMIZED);
for (int i=0; i<lj_types*lj_types; i++)
host_write[i]=0.0;
lj1.alloc(lj_types*lj_types,*(this->ucl_device),UCL_READ_ONLY);
this->atom->type_pack4(ntypes,lj_types,lj1,host_write,host_cutsq,
host_cut_ljsq,host_lj1,host_lj2);
lj3.alloc(lj_types*lj_types,*(this->ucl_device),UCL_READ_ONLY);
this->atom->type_pack4(ntypes,lj_types,lj3,host_write,host_cg_type,host_lj3,
host_lj4,host_offset);
sp_lj.alloc(8,*(this->ucl_device),UCL_READ_ONLY);
for (int i=0; i<4; i++) {
host_write[i]=host_special_lj[i];
host_write[i+4]=host_special_coul[i];
}
ucl_copy(sp_lj,host_write,8,false);
_cut_coulsq=host_cut_coulsq;
_qqrd2e=qqrd2e;
_g_ewald=g_ewald;
_allocated=true;
this->_max_bytes=lj1.row_bytes()+lj3.row_bytes()+sp_lj.row_bytes();
return 0;
}
template <class numtyp, class acctyp>
void CMML_GPU_MemoryT::clear() {
if (!_allocated)
return;
_allocated=false;
lj1.clear();
lj3.clear();
sp_lj.clear();
this->clear_atomic();
}
template <class numtyp, class acctyp>
double CMML_GPU_MemoryT::host_memory_usage() const {
return this->host_memory_usage_atomic()+sizeof(CMML_GPU_Memory<numtyp,acctyp>);
}
// ---------------------------------------------------------------------------
// Calculate energies, forces, and torques
// ---------------------------------------------------------------------------
template <class numtyp, class acctyp>
void CMML_GPU_MemoryT::loop(const bool _eflag, const bool _vflag) {
// Compute the block size and grid size to keep all cores busy
const int BX=this->block_size();
int eflag, vflag;
if (_eflag)
eflag=1;
else
eflag=0;
if (_vflag)
vflag=1;
else
vflag=0;
int GX=static_cast<int>(ceil(static_cast<double>(this->ans->inum())/
(BX/this->_threads_per_atom)));
int ainum=this->ans->inum();
int nbor_pitch=this->nbor->nbor_pitch();
this->time_pair.start();
if (shared_types) {
this->k_pair_fast.set_size(GX,BX);
this->k_pair_fast.run(&this->atom->dev_x.begin(), &lj1.begin(),
&lj3.begin(), &sp_lj.begin(),
&this->nbor->dev_nbor.begin(),
&this->_nbor_data->begin(),
&this->ans->dev_ans.begin(),
&this->ans->dev_engv.begin(), &eflag, &vflag,
&ainum, &nbor_pitch,
&this->atom->dev_q.begin(), &_cut_coulsq,
&_qqrd2e, &_g_ewald, &this->_threads_per_atom);
} else {
this->k_pair.set_size(GX,BX);
this->k_pair.run(&this->atom->dev_x.begin(), &lj1.begin(), &lj3.begin(),
&_lj_types, &sp_lj.begin(), &this->nbor->dev_nbor.begin(),
&this->_nbor_data->begin(), &this->ans->dev_ans.begin(),
&this->ans->dev_engv.begin(), &eflag, &vflag, &ainum,
&nbor_pitch, &this->atom->dev_q.begin(),
&_cut_coulsq, &_qqrd2e, &_g_ewald,
&this->_threads_per_atom);
}
this->time_pair.stop();
}
template class CMML_GPU_Memory<PRECISION,ACC_PRECISION>;
Event Timeline
Log In to Comment