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Faster RNG init
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paboyle
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2bf4688e83
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@ -33,6 +33,7 @@ Author: paboyle <paboyle@ph.ed.ac.uk>
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namespace Grid {
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//http://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-90Ar1.pdf ?
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//////////////////////////////////////////////////////////////
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// Allow the RNG state to be less dense than the fine grid
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@ -68,6 +69,7 @@ namespace Grid {
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}
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// Wrap seed_seq to give common interface with random_device
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// Should rather wrap random_device and have a generate
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class fixedSeed {
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public:
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@ -75,20 +77,31 @@ namespace Grid {
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std::seed_seq src;
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fixedSeed(const std::vector<int> &seeds) : src(seeds.begin(),seeds.end()) {};
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result_type operator () (void){
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std::vector<result_type> list(1);
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src.generate(list.begin(),list.end());
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return list[0];
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template<class int_type> fixedSeed(const std::vector<int_type> &seeds) : src(seeds.begin(),seeds.end()) {};
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template< class RandomIt > void generate( RandomIt begin, RandomIt end ) {
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src.generate(begin,end);
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}
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};
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class deviceSeed {
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public:
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std::random_device rd;
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typedef std::random_device::result_type result_type;
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deviceSeed(void) : rd(){};
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template< class RandomIt > void generate( RandomIt begin, RandomIt end ) {
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for(RandomIt it=begin; it!=end;it++){
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*it = rd();
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}
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}
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};
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// real scalars are one component
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template<class scalar,class distribution,class generator> void fillScalar(scalar &s,distribution &dist,generator & gen)
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{
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@ -122,7 +135,7 @@ namespace Grid {
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std::vector<RngEngine> _generators;
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std::vector<std::uniform_real_distribution<RealD>> _uniform;
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std::vector<std::normal_distribution<RealD>> _gaussian;
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std::vector<std::discrete_distribution<int32_t>> _bernoulli;
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std::vector<std::discrete_distribution<int32_t>> _bernoulli;
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void GetState(std::vector<RngStateType> & saved,int gen) {
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saved.resize(RngStateCount);
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@ -150,13 +163,6 @@ namespace Grid {
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// FIXME ... do we require lockstep draws of randoms
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// from all nodes keeping seeds consistent.
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// place a barrier/broadcast in the fill routine
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template<class source> void Seed(source &src)
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{
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typename source::result_type init = src();
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CartesianCommunicator::BroadcastWorld(0,(void *)&init,sizeof(init));
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_generators[0] = RngEngine(init);
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_seeded=1;
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}
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GridSerialRNG() : GridRNGbase() {
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_generators.resize(1);
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@ -239,12 +245,17 @@ namespace Grid {
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CartesianCommunicator::BroadcastWorld(0,(void *)&l,sizeof(l));
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}
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template<class source> void Seed(source &src)
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{
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_generators[0] = RngEngine(src);
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_seeded=1;
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}
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void SeedRandomDevice(void){
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std::random_device rd;
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Seed(rd);
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deviceSeed src;
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Seed(src);
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}
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void SeedFixedIntegers(const std::vector<int> &seeds){
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CartesianCommunicator::BroadcastWorld(0,(void *)&seeds[0],sizeof(int)*seeds.size());
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fixedSeed src(seeds);
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Seed(src);
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}
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@ -273,46 +284,6 @@ namespace Grid {
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}
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// This loop could be made faster to avoid the Ahmdahl by
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// i) seed generators on each timeslice, for x=y=z=0;
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// ii) seed generators on each z for x=y=0
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// iii)seed generators on each y,z for x=0
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// iv) seed generators on each y,z,x
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// made possible by physical indexing.
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template<class source> void Seed(source &src)
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{
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std::vector<int> gcoor;
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int gsites = _grid->_gsites;
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typename source::result_type init = src();
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RngEngine pseeder(init);
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std::uniform_int_distribution<uint64_t> ui;
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for(int gidx=0;gidx<gsites;gidx++){
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int rank,o_idx,i_idx;
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_grid->GlobalIndexToGlobalCoor(gidx,gcoor);
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_grid->GlobalCoorToRankIndex(rank,o_idx,i_idx,gcoor);
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int l_idx=generator_idx(o_idx,i_idx);
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const int num_rand_seed=16;
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std::vector<int> site_seeds(num_rand_seed);
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for(int i=0;i<site_seeds.size();i++){
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site_seeds[i]= ui(pseeder);
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}
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_grid->Broadcast(0,(void *)&site_seeds[0],sizeof(int)*site_seeds.size());
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if( rank == _grid->ThisRank() ){
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fixedSeed ssrc(site_seeds);
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typename source::result_type sinit = ssrc();
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_generators[l_idx] = RngEngine(sinit);
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}
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}
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_seeded=1;
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}
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//FIXME implement generic IO and create state save/restore
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//void SaveState(const std::string<char> &file);
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@ -354,11 +325,75 @@ PARALLEL_FOR_LOOP
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}
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};
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// This loop could be made faster to avoid the Ahmdahl by
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// i) seed generators on each timeslice, for x=y=z=0;
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// ii) seed generators on each z for x=y=0
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// iii)seed generators on each y,z for x=0
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// iv) seed generators on each y,z,x
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// made possible by physical indexing.
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template<class source> void Seed(source &src)
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{
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typedef typename source::result_type seed_t;
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std::uniform_int_distribution<seed_t> uid;
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int numseed=4;
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int gsites = _grid->_gsites;
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std::vector<seed_t> site_init(numseed);
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std::vector<int> gcoor;
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// Master RngEngine
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std::vector<seed_t> master_init(numseed); src.generate(master_init.begin(),master_init.end());
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_grid->Broadcast(0,(void *)&master_init[0],sizeof(seed_t)*numseed);
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fixedSeed master_seed(master_init);
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RngEngine master_engine(master_seed);
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// Per node RngEngine
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std::vector<seed_t> node_init(numseed);
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for(int r=0;r<_grid->ProcessorCount();r++) {
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std::vector<seed_t> rank_init(numseed);
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for(int i=0;i<numseed;i++) rank_init[i] = uid(master_engine);
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std::cout << GridLogMessage << "SeedSeq for rank "<<r;
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for(int i=0;i<numseed;i++) std::cout<<" "<<rank_init[i];
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std::cout <<std::endl;
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if ( r==_grid->ThisRank() ) {
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for(int i=0;i<numseed;i++) node_init[i] = rank_init[i];
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}
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}
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////////////////////////////////////////////////////
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// Set up a seed_seq wrapper with these 8 words
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// and draw for each site within node.
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////////////////////////////////////////////////////
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fixedSeed node_seed(node_init);
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RngEngine node_engine(node_seed);
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for(int gidx=0;gidx<gsites;gidx++){
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int rank,o_idx,i_idx;
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_grid->GlobalIndexToGlobalCoor(gidx,gcoor);
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_grid->GlobalCoorToRankIndex(rank,o_idx,i_idx,gcoor);
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if( rank == _grid->ThisRank() ){
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int l_idx=generator_idx(o_idx,i_idx);
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for(int i=0;i<numseed;i++) site_init[i] = uid(node_engine);
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fixedSeed site_seed(site_init);
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_generators[l_idx] = RngEngine(site_seed);
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}
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}
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_seeded=1;
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}
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void SeedRandomDevice(void){
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std::random_device rd;
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Seed(rd);
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deviceSeed src;
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Seed(src);
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}
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void SeedFixedIntegers(const std::vector<int> &seeds){
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CartesianCommunicator::BroadcastWorld(0,(void *)&seeds[0],sizeof(int)*seeds.size());
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fixedSeed src(seeds);
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Seed(src);
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}
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