mirror of
https://github.com/paboyle/Grid.git
synced 2025-04-05 03:35:55 +01:00
Namespace indent
This commit is contained in:
paboyle
parent
c19ccdad7c
commit
7e00f643f8
@ -1,4 +1,4 @@
|
||||
/*************************************************************************************
|
||||
/*************************************************************************************
|
||||
|
||||
Grid physics library, www.github.com/paboyle/Grid
|
||||
|
||||
@ -24,8 +24,8 @@
|
||||
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
|
||||
|
||||
See the full license in the file "LICENSE" in the top level distribution directory
|
||||
*************************************************************************************/
|
||||
/* END LEGAL */
|
||||
*************************************************************************************/
|
||||
/* END LEGAL */
|
||||
#ifndef GRID_LATTICE_RNG_H
|
||||
#define GRID_LATTICE_RNG_H
|
||||
|
||||
@ -41,446 +41,446 @@
|
||||
#undef RNG_FAST_DISCARD
|
||||
#endif
|
||||
|
||||
namespace Grid {
|
||||
NAMESPACE_BEGIN(Grid);
|
||||
|
||||
//////////////////////////////////////////////////////////////
|
||||
// Allow the RNG state to be less dense than the fine grid
|
||||
//////////////////////////////////////////////////////////////
|
||||
inline int RNGfillable(GridBase *coarse,GridBase *fine)
|
||||
{
|
||||
//////////////////////////////////////////////////////////////
|
||||
// Allow the RNG state to be less dense than the fine grid
|
||||
//////////////////////////////////////////////////////////////
|
||||
inline int RNGfillable(GridBase *coarse,GridBase *fine)
|
||||
{
|
||||
|
||||
int rngdims = coarse->_ndimension;
|
||||
int rngdims = coarse->_ndimension;
|
||||
|
||||
// trivially extended in higher dims, with locality guaranteeing RNG state is local to node
|
||||
int lowerdims = fine->_ndimension - coarse->_ndimension;
|
||||
assert(lowerdims >= 0);
|
||||
for(int d=0;d<lowerdims;d++){
|
||||
assert(fine->_simd_layout[d]==1);
|
||||
assert(fine->_processors[d]==1);
|
||||
}
|
||||
|
||||
int multiplicity=1;
|
||||
for(int d=0;d<lowerdims;d++){
|
||||
multiplicity=multiplicity*fine->_rdimensions[d];
|
||||
}
|
||||
// local and global volumes subdivide cleanly after SIMDization
|
||||
for(int d=0;d<rngdims;d++){
|
||||
int fd= d+lowerdims;
|
||||
assert(coarse->_processors[d] == fine->_processors[fd]);
|
||||
assert(coarse->_simd_layout[d] == fine->_simd_layout[fd]);
|
||||
assert(((fine->_rdimensions[fd] / coarse->_rdimensions[d])* coarse->_rdimensions[d])==fine->_rdimensions[fd]);
|
||||
|
||||
multiplicity = multiplicity *fine->_rdimensions[fd] / coarse->_rdimensions[d];
|
||||
}
|
||||
return multiplicity;
|
||||
// trivially extended in higher dims, with locality guaranteeing RNG state is local to node
|
||||
int lowerdims = fine->_ndimension - coarse->_ndimension;
|
||||
assert(lowerdims >= 0);
|
||||
for(int d=0;d<lowerdims;d++){
|
||||
assert(fine->_simd_layout[d]==1);
|
||||
assert(fine->_processors[d]==1);
|
||||
}
|
||||
|
||||
int multiplicity=1;
|
||||
for(int d=0;d<lowerdims;d++){
|
||||
multiplicity=multiplicity*fine->_rdimensions[d];
|
||||
}
|
||||
// local and global volumes subdivide cleanly after SIMDization
|
||||
for(int d=0;d<rngdims;d++){
|
||||
int fd= d+lowerdims;
|
||||
assert(coarse->_processors[d] == fine->_processors[fd]);
|
||||
assert(coarse->_simd_layout[d] == fine->_simd_layout[fd]);
|
||||
assert(((fine->_rdimensions[fd] / coarse->_rdimensions[d])* coarse->_rdimensions[d])==fine->_rdimensions[fd]);
|
||||
|
||||
multiplicity = multiplicity *fine->_rdimensions[fd] / coarse->_rdimensions[d];
|
||||
}
|
||||
return multiplicity;
|
||||
}
|
||||
|
||||
|
||||
// merge of April 11 2017
|
||||
// this function is necessary for the LS vectorised field
|
||||
inline int RNGfillable_general(GridBase *coarse,GridBase *fine)
|
||||
{
|
||||
int rngdims = coarse->_ndimension;
|
||||
// this function is necessary for the LS vectorised field
|
||||
inline int RNGfillable_general(GridBase *coarse,GridBase *fine)
|
||||
{
|
||||
int rngdims = coarse->_ndimension;
|
||||
|
||||
// trivially extended in higher dims, with locality guaranteeing RNG state is local to node
|
||||
int lowerdims = fine->_ndimension - coarse->_ndimension; assert(lowerdims >= 0);
|
||||
// assumes that the higher dimensions are not using more processors
|
||||
// all further divisions are local
|
||||
for(int d=0;d<lowerdims;d++) assert(fine->_processors[d]==1);
|
||||
for(int d=0;d<rngdims;d++) assert(coarse->_processors[d] == fine->_processors[d+lowerdims]);
|
||||
// trivially extended in higher dims, with locality guaranteeing RNG state is local to node
|
||||
int lowerdims = fine->_ndimension - coarse->_ndimension; assert(lowerdims >= 0);
|
||||
// assumes that the higher dimensions are not using more processors
|
||||
// all further divisions are local
|
||||
for(int d=0;d<lowerdims;d++) assert(fine->_processors[d]==1);
|
||||
for(int d=0;d<rngdims;d++) assert(coarse->_processors[d] == fine->_processors[d+lowerdims]);
|
||||
|
||||
// then divide the number of local sites
|
||||
// check that the total number of sims agree, meanse the iSites are the same
|
||||
assert(fine->Nsimd() == coarse->Nsimd());
|
||||
// then divide the number of local sites
|
||||
// check that the total number of sims agree, meanse the iSites are the same
|
||||
assert(fine->Nsimd() == coarse->Nsimd());
|
||||
|
||||
// check that the two grids divide cleanly
|
||||
assert( (fine->lSites() / coarse->lSites() ) * coarse->lSites() == fine->lSites() );
|
||||
// check that the two grids divide cleanly
|
||||
assert( (fine->lSites() / coarse->lSites() ) * coarse->lSites() == fine->lSites() );
|
||||
|
||||
return fine->lSites() / coarse->lSites();
|
||||
}
|
||||
return fine->lSites() / coarse->lSites();
|
||||
}
|
||||
|
||||
// real scalars are one component
|
||||
template<class scalar,class distribution,class generator>
|
||||
void fillScalar(scalar &s,distribution &dist,generator & gen)
|
||||
{
|
||||
s=dist(gen);
|
||||
}
|
||||
template<class distribution,class generator>
|
||||
void fillScalar(ComplexF &s,distribution &dist, generator &gen)
|
||||
{
|
||||
s=ComplexF(dist(gen),dist(gen));
|
||||
}
|
||||
template<class distribution,class generator>
|
||||
void fillScalar(ComplexD &s,distribution &dist,generator &gen)
|
||||
{
|
||||
s=ComplexD(dist(gen),dist(gen));
|
||||
}
|
||||
// real scalars are one component
|
||||
template<class scalar,class distribution,class generator>
|
||||
void fillScalar(scalar &s,distribution &dist,generator & gen)
|
||||
{
|
||||
s=dist(gen);
|
||||
}
|
||||
template<class distribution,class generator>
|
||||
void fillScalar(ComplexF &s,distribution &dist, generator &gen)
|
||||
{
|
||||
s=ComplexF(dist(gen),dist(gen));
|
||||
}
|
||||
template<class distribution,class generator>
|
||||
void fillScalar(ComplexD &s,distribution &dist,generator &gen)
|
||||
{
|
||||
s=ComplexD(dist(gen),dist(gen));
|
||||
}
|
||||
|
||||
class GridRNGbase {
|
||||
public:
|
||||
// One generator per site.
|
||||
// Uniform and Gaussian distributions from these generators.
|
||||
class GridRNGbase {
|
||||
public:
|
||||
// One generator per site.
|
||||
// Uniform and Gaussian distributions from these generators.
|
||||
#ifdef RNG_RANLUX
|
||||
typedef std::ranlux48 RngEngine;
|
||||
typedef uint64_t RngStateType;
|
||||
static const int RngStateCount = 15;
|
||||
typedef std::ranlux48 RngEngine;
|
||||
typedef uint64_t RngStateType;
|
||||
static const int RngStateCount = 15;
|
||||
#endif
|
||||
#ifdef RNG_MT19937
|
||||
typedef std::mt19937 RngEngine;
|
||||
typedef uint32_t RngStateType;
|
||||
static const int RngStateCount = std::mt19937::state_size;
|
||||
typedef std::mt19937 RngEngine;
|
||||
typedef uint32_t RngStateType;
|
||||
static const int RngStateCount = std::mt19937::state_size;
|
||||
#endif
|
||||
#ifdef RNG_SITMO
|
||||
typedef sitmo::prng_engine RngEngine;
|
||||
typedef uint64_t RngStateType;
|
||||
static const int RngStateCount = 13;
|
||||
typedef sitmo::prng_engine RngEngine;
|
||||
typedef uint64_t RngStateType;
|
||||
static const int RngStateCount = 13;
|
||||
#endif
|
||||
|
||||
std::vector<RngEngine> _generators;
|
||||
std::vector<std::uniform_real_distribution<RealD> > _uniform;
|
||||
std::vector<std::normal_distribution<RealD> > _gaussian;
|
||||
std::vector<std::discrete_distribution<int32_t> > _bernoulli;
|
||||
std::vector<std::uniform_int_distribution<uint32_t> > _uid;
|
||||
std::vector<RngEngine> _generators;
|
||||
std::vector<std::uniform_real_distribution<RealD> > _uniform;
|
||||
std::vector<std::normal_distribution<RealD> > _gaussian;
|
||||
std::vector<std::discrete_distribution<int32_t> > _bernoulli;
|
||||
std::vector<std::uniform_int_distribution<uint32_t> > _uid;
|
||||
|
||||
///////////////////////
|
||||
// support for parallel init
|
||||
///////////////////////
|
||||
///////////////////////
|
||||
// support for parallel init
|
||||
///////////////////////
|
||||
#ifdef RNG_FAST_DISCARD
|
||||
static void Skip(RngEngine &eng,uint64_t site)
|
||||
{
|
||||
/////////////////////////////////////////////////////////////////////////////////////
|
||||
// Skip by 2^40 elements between successive lattice sites
|
||||
// This goes by 10^12.
|
||||
// Consider quenched updating; likely never exceeding rate of 1000 sweeps
|
||||
// per second on any machine. This gives us of order 10^9 seconds, or 100 years
|
||||
// skip ahead.
|
||||
// For HMC unlikely to go at faster than a solve per second, and
|
||||
// tens of seconds per trajectory so this is clean in all reasonable cases,
|
||||
// and margin of safety is orders of magnitude.
|
||||
// We could hack Sitmo to skip in the higher order words of state if necessary
|
||||
/////////////////////////////////////////////////////////////////////////////////////
|
||||
// uint64_t skip = site+1; // Old init Skipped then drew. Checked compat with faster init
|
||||
uint64_t skip = site;
|
||||
skip = skip<<40;
|
||||
eng.discard(skip);
|
||||
// std::cout << " Engine " <<site << " state " <<eng<<std::endl;
|
||||
}
|
||||
static void Skip(RngEngine &eng,uint64_t site)
|
||||
{
|
||||
/////////////////////////////////////////////////////////////////////////////////////
|
||||
// Skip by 2^40 elements between successive lattice sites
|
||||
// This goes by 10^12.
|
||||
// Consider quenched updating; likely never exceeding rate of 1000 sweeps
|
||||
// per second on any machine. This gives us of order 10^9 seconds, or 100 years
|
||||
// skip ahead.
|
||||
// For HMC unlikely to go at faster than a solve per second, and
|
||||
// tens of seconds per trajectory so this is clean in all reasonable cases,
|
||||
// and margin of safety is orders of magnitude.
|
||||
// We could hack Sitmo to skip in the higher order words of state if necessary
|
||||
/////////////////////////////////////////////////////////////////////////////////////
|
||||
// uint64_t skip = site+1; // Old init Skipped then drew. Checked compat with faster init
|
||||
uint64_t skip = site;
|
||||
skip = skip<<40;
|
||||
eng.discard(skip);
|
||||
// std::cout << " Engine " <<site << " state " <<eng<<std::endl;
|
||||
}
|
||||
#endif
|
||||
static RngEngine Reseed(RngEngine &eng)
|
||||
{
|
||||
std::vector<uint32_t> newseed;
|
||||
std::uniform_int_distribution<uint32_t> uid;
|
||||
return Reseed(eng,newseed,uid);
|
||||
}
|
||||
static RngEngine Reseed(RngEngine &eng,std::vector<uint32_t> & newseed,
|
||||
std::uniform_int_distribution<uint32_t> &uid)
|
||||
{
|
||||
const int reseeds=4;
|
||||
static RngEngine Reseed(RngEngine &eng)
|
||||
{
|
||||
std::vector<uint32_t> newseed;
|
||||
std::uniform_int_distribution<uint32_t> uid;
|
||||
return Reseed(eng,newseed,uid);
|
||||
}
|
||||
static RngEngine Reseed(RngEngine &eng,std::vector<uint32_t> & newseed,
|
||||
std::uniform_int_distribution<uint32_t> &uid)
|
||||
{
|
||||
const int reseeds=4;
|
||||
|
||||
newseed.resize(reseeds);
|
||||
for(int i=0;i<reseeds;i++){
|
||||
newseed[i] = uid(eng);
|
||||
}
|
||||
std::seed_seq sseq(newseed.begin(),newseed.end());
|
||||
return RngEngine(sseq);
|
||||
}
|
||||
newseed.resize(reseeds);
|
||||
for(int i=0;i<reseeds;i++){
|
||||
newseed[i] = uid(eng);
|
||||
}
|
||||
std::seed_seq sseq(newseed.begin(),newseed.end());
|
||||
return RngEngine(sseq);
|
||||
}
|
||||
|
||||
void GetState(std::vector<RngStateType> & saved,RngEngine &eng) {
|
||||
saved.resize(RngStateCount);
|
||||
std::stringstream ss;
|
||||
ss<<eng;
|
||||
ss.seekg(0,ss.beg);
|
||||
for(int i=0;i<RngStateCount;i++){
|
||||
ss>>saved[i];
|
||||
}
|
||||
void GetState(std::vector<RngStateType> & saved,RngEngine &eng) {
|
||||
saved.resize(RngStateCount);
|
||||
std::stringstream ss;
|
||||
ss<<eng;
|
||||
ss.seekg(0,ss.beg);
|
||||
for(int i=0;i<RngStateCount;i++){
|
||||
ss>>saved[i];
|
||||
}
|
||||
void GetState(std::vector<RngStateType> & saved,int gen) {
|
||||
GetState(saved,_generators[gen]);
|
||||
}
|
||||
void GetState(std::vector<RngStateType> & saved,int gen) {
|
||||
GetState(saved,_generators[gen]);
|
||||
}
|
||||
void SetState(std::vector<RngStateType> & saved,RngEngine &eng){
|
||||
assert(saved.size()==RngStateCount);
|
||||
std::stringstream ss;
|
||||
for(int i=0;i<RngStateCount;i++){
|
||||
ss<< saved[i]<<" ";
|
||||
}
|
||||
void SetState(std::vector<RngStateType> & saved,RngEngine &eng){
|
||||
assert(saved.size()==RngStateCount);
|
||||
std::stringstream ss;
|
||||
for(int i=0;i<RngStateCount;i++){
|
||||
ss<< saved[i]<<" ";
|
||||
}
|
||||
ss.seekg(0,ss.beg);
|
||||
ss>>eng;
|
||||
}
|
||||
void SetState(std::vector<RngStateType> & saved,int gen){
|
||||
SetState(saved,_generators[gen]);
|
||||
}
|
||||
void SetEngine(RngEngine &Eng, int gen){
|
||||
_generators[gen]=Eng;
|
||||
}
|
||||
void GetEngine(RngEngine &Eng, int gen){
|
||||
Eng=_generators[gen];
|
||||
}
|
||||
template<class source> void Seed(source &src, int gen)
|
||||
{
|
||||
_generators[gen] = RngEngine(src);
|
||||
}
|
||||
};
|
||||
ss.seekg(0,ss.beg);
|
||||
ss>>eng;
|
||||
}
|
||||
void SetState(std::vector<RngStateType> & saved,int gen){
|
||||
SetState(saved,_generators[gen]);
|
||||
}
|
||||
void SetEngine(RngEngine &Eng, int gen){
|
||||
_generators[gen]=Eng;
|
||||
}
|
||||
void GetEngine(RngEngine &Eng, int gen){
|
||||
Eng=_generators[gen];
|
||||
}
|
||||
template<class source> void Seed(source &src, int gen)
|
||||
{
|
||||
_generators[gen] = RngEngine(src);
|
||||
}
|
||||
};
|
||||
|
||||
class GridSerialRNG : public GridRNGbase {
|
||||
public:
|
||||
class GridSerialRNG : public GridRNGbase {
|
||||
public:
|
||||
|
||||
GridSerialRNG() : GridRNGbase() {
|
||||
_generators.resize(1);
|
||||
_uniform.resize(1,std::uniform_real_distribution<RealD>{0,1});
|
||||
_gaussian.resize(1,std::normal_distribution<RealD>(0.0,1.0) );
|
||||
_bernoulli.resize(1,std::discrete_distribution<int32_t>{1,1});
|
||||
_uid.resize(1,std::uniform_int_distribution<uint32_t>() );
|
||||
}
|
||||
GridSerialRNG() : GridRNGbase() {
|
||||
_generators.resize(1);
|
||||
_uniform.resize(1,std::uniform_real_distribution<RealD>{0,1});
|
||||
_gaussian.resize(1,std::normal_distribution<RealD>(0.0,1.0) );
|
||||
_bernoulli.resize(1,std::discrete_distribution<int32_t>{1,1});
|
||||
_uid.resize(1,std::uniform_int_distribution<uint32_t>() );
|
||||
}
|
||||
|
||||
template <class sobj,class distribution> inline void fill(sobj &l,std::vector<distribution> &dist){
|
||||
template <class sobj,class distribution> inline void fill(sobj &l,std::vector<distribution> &dist){
|
||||
|
||||
typedef typename sobj::scalar_type scalar_type;
|
||||
typedef typename sobj::scalar_type scalar_type;
|
||||
|
||||
int words = sizeof(sobj)/sizeof(scalar_type);
|
||||
int words = sizeof(sobj)/sizeof(scalar_type);
|
||||
|
||||
scalar_type *buf = (scalar_type *) & l;
|
||||
scalar_type *buf = (scalar_type *) & l;
|
||||
|
||||
dist[0].reset();
|
||||
for(int idx=0;idx<words;idx++){
|
||||
fillScalar(buf[idx],dist[0],_generators[0]);
|
||||
}
|
||||
dist[0].reset();
|
||||
for(int idx=0;idx<words;idx++){
|
||||
fillScalar(buf[idx],dist[0],_generators[0]);
|
||||
}
|
||||
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
|
||||
};
|
||||
|
||||
template <class distribution> inline void fill(ComplexF &l,std::vector<distribution> &dist){
|
||||
dist[0].reset();
|
||||
fillScalar(l,dist[0],_generators[0]);
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
template <class distribution> inline void fill(ComplexD &l,std::vector<distribution> &dist){
|
||||
dist[0].reset();
|
||||
fillScalar(l,dist[0],_generators[0]);
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
template <class distribution> inline void fill(RealF &l,std::vector<distribution> &dist){
|
||||
dist[0].reset();
|
||||
fillScalar(l,dist[0],_generators[0]);
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
template <class distribution> inline void fill(RealD &l,std::vector<distribution> &dist){
|
||||
dist[0].reset();
|
||||
fillScalar(l,dist[0],_generators[0]);
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
// vector fill
|
||||
template <class distribution> inline void fill(vComplexF &l,std::vector<distribution> &dist){
|
||||
RealF *pointer=(RealF *)&l;
|
||||
dist[0].reset();
|
||||
for(int i=0;i<2*vComplexF::Nsimd();i++){
|
||||
fillScalar(pointer[i],dist[0],_generators[0]);
|
||||
}
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
template <class distribution> inline void fill(vComplexD &l,std::vector<distribution> &dist){
|
||||
RealD *pointer=(RealD *)&l;
|
||||
dist[0].reset();
|
||||
for(int i=0;i<2*vComplexD::Nsimd();i++){
|
||||
fillScalar(pointer[i],dist[0],_generators[0]);
|
||||
}
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
template <class distribution> inline void fill(vRealF &l,std::vector<distribution> &dist){
|
||||
RealF *pointer=(RealF *)&l;
|
||||
dist[0].reset();
|
||||
for(int i=0;i<vRealF::Nsimd();i++){
|
||||
fillScalar(pointer[i],dist[0],_generators[0]);
|
||||
}
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
template <class distribution> inline void fill(vRealD &l,std::vector<distribution> &dist){
|
||||
RealD *pointer=(RealD *)&l;
|
||||
dist[0].reset();
|
||||
for(int i=0;i<vRealD::Nsimd();i++){
|
||||
fillScalar(pointer[i],dist[0],_generators[0]);
|
||||
}
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
|
||||
void SeedFixedIntegers(const std::vector<int> &seeds){
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&seeds[0],sizeof(int)*seeds.size());
|
||||
std::seed_seq src(seeds.begin(),seeds.end());
|
||||
Seed(src,0);
|
||||
}
|
||||
};
|
||||
|
||||
class GridParallelRNG : public GridRNGbase {
|
||||
|
||||
double _time_counter;
|
||||
|
||||
public:
|
||||
GridBase *_grid;
|
||||
unsigned int _vol;
|
||||
|
||||
int generator_idx(int os,int is) {
|
||||
return is*_grid->oSites()+os;
|
||||
template <class distribution> inline void fill(ComplexF &l,std::vector<distribution> &dist){
|
||||
dist[0].reset();
|
||||
fillScalar(l,dist[0],_generators[0]);
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
template <class distribution> inline void fill(ComplexD &l,std::vector<distribution> &dist){
|
||||
dist[0].reset();
|
||||
fillScalar(l,dist[0],_generators[0]);
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
template <class distribution> inline void fill(RealF &l,std::vector<distribution> &dist){
|
||||
dist[0].reset();
|
||||
fillScalar(l,dist[0],_generators[0]);
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
template <class distribution> inline void fill(RealD &l,std::vector<distribution> &dist){
|
||||
dist[0].reset();
|
||||
fillScalar(l,dist[0],_generators[0]);
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
// vector fill
|
||||
template <class distribution> inline void fill(vComplexF &l,std::vector<distribution> &dist){
|
||||
RealF *pointer=(RealF *)&l;
|
||||
dist[0].reset();
|
||||
for(int i=0;i<2*vComplexF::Nsimd();i++){
|
||||
fillScalar(pointer[i],dist[0],_generators[0]);
|
||||
}
|
||||
|
||||
GridParallelRNG(GridBase *grid) : GridRNGbase() {
|
||||
_grid = grid;
|
||||
_vol =_grid->iSites()*_grid->oSites();
|
||||
|
||||
_generators.resize(_vol);
|
||||
_uniform.resize(_vol,std::uniform_real_distribution<RealD>{0,1});
|
||||
_gaussian.resize(_vol,std::normal_distribution<RealD>(0.0,1.0) );
|
||||
_bernoulli.resize(_vol,std::discrete_distribution<int32_t>{1,1});
|
||||
_uid.resize(_vol,std::uniform_int_distribution<uint32_t>() );
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
template <class distribution> inline void fill(vComplexD &l,std::vector<distribution> &dist){
|
||||
RealD *pointer=(RealD *)&l;
|
||||
dist[0].reset();
|
||||
for(int i=0;i<2*vComplexD::Nsimd();i++){
|
||||
fillScalar(pointer[i],dist[0],_generators[0]);
|
||||
}
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
template <class distribution> inline void fill(vRealF &l,std::vector<distribution> &dist){
|
||||
RealF *pointer=(RealF *)&l;
|
||||
dist[0].reset();
|
||||
for(int i=0;i<vRealF::Nsimd();i++){
|
||||
fillScalar(pointer[i],dist[0],_generators[0]);
|
||||
}
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
template <class distribution> inline void fill(vRealD &l,std::vector<distribution> &dist){
|
||||
RealD *pointer=(RealD *)&l;
|
||||
dist[0].reset();
|
||||
for(int i=0;i<vRealD::Nsimd();i++){
|
||||
fillScalar(pointer[i],dist[0],_generators[0]);
|
||||
}
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
|
||||
}
|
||||
|
||||
void SeedFixedIntegers(const std::vector<int> &seeds){
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&seeds[0],sizeof(int)*seeds.size());
|
||||
std::seed_seq src(seeds.begin(),seeds.end());
|
||||
Seed(src,0);
|
||||
}
|
||||
};
|
||||
|
||||
template <class vobj,class distribution> inline void fill(Lattice<vobj> &l,std::vector<distribution> &dist){
|
||||
class GridParallelRNG : public GridRNGbase {
|
||||
|
||||
typedef typename vobj::scalar_object scalar_object;
|
||||
typedef typename vobj::scalar_type scalar_type;
|
||||
typedef typename vobj::vector_type vector_type;
|
||||
double _time_counter;
|
||||
|
||||
double inner_time_counter = usecond();
|
||||
public:
|
||||
GridBase *_grid;
|
||||
unsigned int _vol;
|
||||
|
||||
int multiplicity = RNGfillable_general(_grid, l._grid); // l has finer or same grid
|
||||
int Nsimd = _grid->Nsimd(); // guaranteed to be the same for l._grid too
|
||||
int osites = _grid->oSites(); // guaranteed to be <= l._grid->oSites() by a factor multiplicity
|
||||
int words = sizeof(scalar_object) / sizeof(scalar_type);
|
||||
int generator_idx(int os,int is) {
|
||||
return is*_grid->oSites()+os;
|
||||
}
|
||||
|
||||
parallel_for(int ss=0;ss<osites;ss++){
|
||||
std::vector<scalar_object> buf(Nsimd);
|
||||
for (int m = 0; m < multiplicity; m++) { // Draw from same generator multiplicity times
|
||||
GridParallelRNG(GridBase *grid) : GridRNGbase() {
|
||||
_grid = grid;
|
||||
_vol =_grid->iSites()*_grid->oSites();
|
||||
|
||||
int sm = multiplicity * ss + m; // Maps the generator site to the fine site
|
||||
_generators.resize(_vol);
|
||||
_uniform.resize(_vol,std::uniform_real_distribution<RealD>{0,1});
|
||||
_gaussian.resize(_vol,std::normal_distribution<RealD>(0.0,1.0) );
|
||||
_bernoulli.resize(_vol,std::discrete_distribution<int32_t>{1,1});
|
||||
_uid.resize(_vol,std::uniform_int_distribution<uint32_t>() );
|
||||
}
|
||||
|
||||
for (int si = 0; si < Nsimd; si++) {
|
||||
template <class vobj,class distribution> inline void fill(Lattice<vobj> &l,std::vector<distribution> &dist){
|
||||
|
||||
typedef typename vobj::scalar_object scalar_object;
|
||||
typedef typename vobj::scalar_type scalar_type;
|
||||
typedef typename vobj::vector_type vector_type;
|
||||
|
||||
double inner_time_counter = usecond();
|
||||
|
||||
int multiplicity = RNGfillable_general(_grid, l._grid); // l has finer or same grid
|
||||
int Nsimd = _grid->Nsimd(); // guaranteed to be the same for l._grid too
|
||||
int osites = _grid->oSites(); // guaranteed to be <= l._grid->oSites() by a factor multiplicity
|
||||
int words = sizeof(scalar_object) / sizeof(scalar_type);
|
||||
|
||||
parallel_for(int ss=0;ss<osites;ss++){
|
||||
std::vector<scalar_object> buf(Nsimd);
|
||||
for (int m = 0; m < multiplicity; m++) { // Draw from same generator multiplicity times
|
||||
|
||||
int sm = multiplicity * ss + m; // Maps the generator site to the fine site
|
||||
|
||||
for (int si = 0; si < Nsimd; si++) {
|
||||
|
||||
int gdx = generator_idx(ss, si); // index of generator state
|
||||
scalar_type *pointer = (scalar_type *)&buf[si];
|
||||
dist[gdx].reset();
|
||||
for (int idx = 0; idx < words; idx++)
|
||||
fillScalar(pointer[idx], dist[gdx], _generators[gdx]);
|
||||
}
|
||||
// merge into SIMD lanes, FIXME suboptimal implementation
|
||||
merge(l._odata[sm], buf);
|
||||
}
|
||||
int gdx = generator_idx(ss, si); // index of generator state
|
||||
scalar_type *pointer = (scalar_type *)&buf[si];
|
||||
dist[gdx].reset();
|
||||
for (int idx = 0; idx < words; idx++)
|
||||
fillScalar(pointer[idx], dist[gdx], _generators[gdx]);
|
||||
}
|
||||
// merge into SIMD lanes, FIXME suboptimal implementation
|
||||
merge(l._odata[sm], buf);
|
||||
}
|
||||
}
|
||||
|
||||
_time_counter += usecond()- inner_time_counter;
|
||||
};
|
||||
_time_counter += usecond()- inner_time_counter;
|
||||
};
|
||||
|
||||
void SeedFixedIntegers(const std::vector<int> &seeds){
|
||||
void SeedFixedIntegers(const std::vector<int> &seeds){
|
||||
|
||||
// Everyone generates the same seed_seq based on input seeds
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&seeds[0],sizeof(int)*seeds.size());
|
||||
// Everyone generates the same seed_seq based on input seeds
|
||||
CartesianCommunicator::BroadcastWorld(0,(void *)&seeds[0],sizeof(int)*seeds.size());
|
||||
|
||||
std::seed_seq source(seeds.begin(),seeds.end());
|
||||
std::seed_seq source(seeds.begin(),seeds.end());
|
||||
|
||||
RngEngine master_engine(source);
|
||||
RngEngine master_engine(source);
|
||||
|
||||
#ifdef RNG_FAST_DISCARD
|
||||
////////////////////////////////////////////////
|
||||
// Skip ahead through a single stream.
|
||||
// Applicable to SITMO and other has based/crypto RNGs
|
||||
// Should be applicable to Mersenne Twister, but the C++11
|
||||
// MT implementation does not implement fast discard even though
|
||||
// in principle this is possible
|
||||
////////////////////////////////////////////////
|
||||
////////////////////////////////////////////////
|
||||
// Skip ahead through a single stream.
|
||||
// Applicable to SITMO and other has based/crypto RNGs
|
||||
// Should be applicable to Mersenne Twister, but the C++11
|
||||
// MT implementation does not implement fast discard even though
|
||||
// in principle this is possible
|
||||
////////////////////////////////////////////////
|
||||
|
||||
// Everybody loops over global volume.
|
||||
parallel_for(int gidx=0;gidx<_grid->_gsites;gidx++){
|
||||
// Everybody loops over global volume.
|
||||
parallel_for(int gidx=0;gidx<_grid->_gsites;gidx++){
|
||||
|
||||
// Where is it?
|
||||
int rank,o_idx,i_idx;
|
||||
std::vector<int> gcoor;
|
||||
// Where is it?
|
||||
int rank,o_idx,i_idx;
|
||||
std::vector<int> gcoor;
|
||||
|
||||
_grid->GlobalIndexToGlobalCoor(gidx,gcoor);
|
||||
_grid->GlobalCoorToRankIndex(rank,o_idx,i_idx,gcoor);
|
||||
|
||||
// If this is one of mine we take it
|
||||
if( rank == _grid->ThisRank() ){
|
||||
int l_idx=generator_idx(o_idx,i_idx);
|
||||
_generators[l_idx] = master_engine;
|
||||
Skip(_generators[l_idx],gidx); // Skip to next RNG sequence
|
||||
}
|
||||
_grid->GlobalIndexToGlobalCoor(gidx,gcoor);
|
||||
_grid->GlobalCoorToRankIndex(rank,o_idx,i_idx,gcoor);
|
||||
|
||||
// If this is one of mine we take it
|
||||
if( rank == _grid->ThisRank() ){
|
||||
int l_idx=generator_idx(o_idx,i_idx);
|
||||
_generators[l_idx] = master_engine;
|
||||
Skip(_generators[l_idx],gidx); // Skip to next RNG sequence
|
||||
}
|
||||
|
||||
}
|
||||
#else
|
||||
////////////////////////////////////////////////////////////////
|
||||
// Machine and thread decomposition dependent seeding is efficient
|
||||
// and maximally parallel; but NOT reproducible from machine to machine.
|
||||
// Not ideal, but fastest way to reseed all nodes.
|
||||
////////////////////////////////////////////////////////////////
|
||||
{
|
||||
// Obtain one Reseed per processor
|
||||
int Nproc = _grid->ProcessorCount();
|
||||
std::vector<RngEngine> seeders(Nproc);
|
||||
int me= _grid->ThisRank();
|
||||
for(int p=0;p<Nproc;p++){
|
||||
seeders[p] = Reseed(master_engine);
|
||||
}
|
||||
master_engine = seeders[me];
|
||||
////////////////////////////////////////////////////////////////
|
||||
// Machine and thread decomposition dependent seeding is efficient
|
||||
// and maximally parallel; but NOT reproducible from machine to machine.
|
||||
// Not ideal, but fastest way to reseed all nodes.
|
||||
////////////////////////////////////////////////////////////////
|
||||
{
|
||||
// Obtain one Reseed per processor
|
||||
int Nproc = _grid->ProcessorCount();
|
||||
std::vector<RngEngine> seeders(Nproc);
|
||||
int me= _grid->ThisRank();
|
||||
for(int p=0;p<Nproc;p++){
|
||||
seeders[p] = Reseed(master_engine);
|
||||
}
|
||||
master_engine = seeders[me];
|
||||
}
|
||||
|
||||
{
|
||||
// Obtain one reseeded generator per thread
|
||||
int Nthread = GridThread::GetThreads();
|
||||
std::vector<RngEngine> seeders(Nthread);
|
||||
for(int t=0;t<Nthread;t++){
|
||||
seeders[t] = Reseed(master_engine);
|
||||
}
|
||||
|
||||
{
|
||||
// Obtain one reseeded generator per thread
|
||||
int Nthread = GridThread::GetThreads();
|
||||
std::vector<RngEngine> seeders(Nthread);
|
||||
for(int t=0;t<Nthread;t++){
|
||||
seeders[t] = Reseed(master_engine);
|
||||
}
|
||||
|
||||
parallel_for(int t=0;t<Nthread;t++) {
|
||||
// set up one per local site in threaded fashion
|
||||
std::vector<uint32_t> newseeds;
|
||||
std::uniform_int_distribution<uint32_t> uid;
|
||||
for(int l=0;l<_grid->lSites();l++) {
|
||||
if ( (l%Nthread)==t ) {
|
||||
_generators[l] = Reseed(seeders[t],newseeds,uid);
|
||||
}
|
||||
parallel_for(int t=0;t<Nthread;t++) {
|
||||
// set up one per local site in threaded fashion
|
||||
std::vector<uint32_t> newseeds;
|
||||
std::uniform_int_distribution<uint32_t> uid;
|
||||
for(int l=0;l<_grid->lSites();l++) {
|
||||
if ( (l%Nthread)==t ) {
|
||||
_generators[l] = Reseed(seeders[t],newseeds,uid);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
#endif
|
||||
}
|
||||
|
||||
void Report(){
|
||||
std::cout << GridLogMessage << "Time spent in the fill() routine by GridParallelRNG: "<< _time_counter/1e3 << " ms" << std::endl;
|
||||
}
|
||||
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// Support for rigorous test of RNG's
|
||||
// Return uniform random uint32_t from requested site generator
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
uint32_t GlobalU01(int gsite){
|
||||
|
||||
uint32_t the_number;
|
||||
// who
|
||||
std::vector<int> gcoor;
|
||||
int rank,o_idx,i_idx;
|
||||
_grid->GlobalIndexToGlobalCoor(gsite,gcoor);
|
||||
_grid->GlobalCoorToRankIndex(rank,o_idx,i_idx,gcoor);
|
||||
|
||||
// draw
|
||||
int l_idx=generator_idx(o_idx,i_idx);
|
||||
if( rank == _grid->ThisRank() ){
|
||||
the_number = _uid[l_idx](_generators[l_idx]);
|
||||
}
|
||||
|
||||
void Report(){
|
||||
std::cout << GridLogMessage << "Time spent in the fill() routine by GridParallelRNG: "<< _time_counter/1e3 << " ms" << std::endl;
|
||||
}
|
||||
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// Support for rigorous test of RNG's
|
||||
// Return uniform random uint32_t from requested site generator
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
uint32_t GlobalU01(int gsite){
|
||||
|
||||
uint32_t the_number;
|
||||
// who
|
||||
std::vector<int> gcoor;
|
||||
int rank,o_idx,i_idx;
|
||||
_grid->GlobalIndexToGlobalCoor(gsite,gcoor);
|
||||
_grid->GlobalCoorToRankIndex(rank,o_idx,i_idx,gcoor);
|
||||
|
||||
// draw
|
||||
int l_idx=generator_idx(o_idx,i_idx);
|
||||
if( rank == _grid->ThisRank() ){
|
||||
the_number = _uid[l_idx](_generators[l_idx]);
|
||||
}
|
||||
|
||||
// share & return
|
||||
_grid->Broadcast(rank,(void *)&the_number,sizeof(the_number));
|
||||
return the_number;
|
||||
}
|
||||
// share & return
|
||||
_grid->Broadcast(rank,(void *)&the_number,sizeof(the_number));
|
||||
return the_number;
|
||||
}
|
||||
|
||||
};
|
||||
};
|
||||
|
||||
template <class vobj> inline void random(GridParallelRNG &rng,Lattice<vobj> &l) { rng.fill(l,rng._uniform); }
|
||||
template <class vobj> inline void gaussian(GridParallelRNG &rng,Lattice<vobj> &l) { rng.fill(l,rng._gaussian); }
|
||||
template <class vobj> inline void bernoulli(GridParallelRNG &rng,Lattice<vobj> &l){ rng.fill(l,rng._bernoulli);}
|
||||
template <class vobj> inline void random(GridParallelRNG &rng,Lattice<vobj> &l) { rng.fill(l,rng._uniform); }
|
||||
template <class vobj> inline void gaussian(GridParallelRNG &rng,Lattice<vobj> &l) { rng.fill(l,rng._gaussian); }
|
||||
template <class vobj> inline void bernoulli(GridParallelRNG &rng,Lattice<vobj> &l){ rng.fill(l,rng._bernoulli);}
|
||||
|
||||
template <class sobj> inline void random(GridSerialRNG &rng,sobj &l) { rng.fill(l,rng._uniform ); }
|
||||
template <class sobj> inline void gaussian(GridSerialRNG &rng,sobj &l) { rng.fill(l,rng._gaussian ); }
|
||||
template <class sobj> inline void bernoulli(GridSerialRNG &rng,sobj &l){ rng.fill(l,rng._bernoulli); }
|
||||
template <class sobj> inline void random(GridSerialRNG &rng,sobj &l) { rng.fill(l,rng._uniform ); }
|
||||
template <class sobj> inline void gaussian(GridSerialRNG &rng,sobj &l) { rng.fill(l,rng._gaussian ); }
|
||||
template <class sobj> inline void bernoulli(GridSerialRNG &rng,sobj &l){ rng.fill(l,rng._bernoulli); }
|
||||
|
||||
}
|
||||
NAMESPACE_END(Grid);
|
||||
#endif
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user