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Rework of RNG to use C++11 random. Should work correctly maintaining parallel RNG across
a machine. If a "fixedSeed" is used, randoms should be reproducible across different machine decomposition since the generators are physically indexed and assigned in lexico ordering.
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@ -6,22 +6,25 @@
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namespace Grid{
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class GridBase : public CartesianCommunicator {
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class GridRNG ; // Forward declaration;
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class GridBase : public CartesianCommunicator {
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public:
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// Give Lattice access
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template<class object> friend class Lattice;
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GridBase(std::vector<int> & processor_grid) : CartesianCommunicator(processor_grid) {};
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// Give Lattice access
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template<class object> friend class Lattice;
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//FIXME
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// protected:
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// Lattice wide random support. not yet fully implemented. Need seed strategy
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// and one generator per site.
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// std::default_random_engine generator;
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// static std::mt19937 generator( 9 );
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GridRNG *_rng;
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GridBase(std::vector<int> & processor_grid) : CartesianCommunicator(processor_grid) {};
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//FIXME
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// protected:
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// Lattice wide random support. not yet fully implemented. Need seed strategy
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// and one generator per site.
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// std::default_random_engine generator;
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// static std::mt19937 generator( 9 );
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//////////////////////////////////////////////////////////////////////
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// Commicator provides information on the processor grid
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//////////////////////////////////////////////////////////////////////
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@ -32,7 +35,7 @@ public:
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//////////////////////////////////////////////////////////////////////
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// Physics Grid information.
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std::vector<int> _simd_layout; // Which dimensions get relayed out over simd lanes.
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std::vector<int> _simd_layout;// Which dimensions get relayed out over simd lanes.
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std::vector<int> _fdimensions;// Global dimensions of array prior to cb removal
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std::vector<int> _gdimensions;// Global dimensions of array after cb removal
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std::vector<int> _ldimensions;// local dimensions of array with processor images removed
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@ -41,6 +44,8 @@ public:
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std::vector<int> _istride; // Inner stride i.e. within simd lane
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int _osites; // _isites*_osites = product(dimensions).
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int _isites;
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int _fsites; // _isites*_osites = product(dimensions).
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int _gsites;
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std::vector<int> _slice_block; // subslice information
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std::vector<int> _slice_stride;
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std::vector<int> _slice_nblock;
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@ -149,6 +154,21 @@ public:
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////////////////////////////////////////////////////////////////
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// Global addressing
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////////////////////////////////////////////////////////////////
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void GlobalIndexToGlobalCoor(int gidx,std::vector<int> &gcoor){
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gcoor.resize(_ndimension);
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for(int d=0;d<_ndimension;d++){
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gcoor[d] = gidx % _gdimensions[d];
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gidx = gidx / _gdimensions[d];
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}
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}
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void GlobalCoorToGlobalIndex(const std::vector<int> & gcoor,int & gidx){
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gidx=0;
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int mult=1;
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for(int mu=0;mu<_ndimension;mu++) {
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gidx+=mult*gcoor[mu];
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mult*=_gdimensions[mu];
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}
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}
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void RankIndexToGlobalCoor(int rank, int o_idx, int i_idx , std::vector<int> &gcoor)
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{
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gcoor.resize(_ndimension);
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@ -194,7 +214,8 @@ public:
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i_idx= iIndex(lcoor);
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o_idx= oIndex(lcoor);
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}
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};
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}
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#endif
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@ -43,12 +43,14 @@ public:
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_ostride.resize(_ndimension);
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_istride.resize(_ndimension);
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_osites = 1;
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_isites = 1;
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_fsites = _gsites = _osites = _isites = 1;
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for(int d=0;d<_ndimension;d++){
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_fdimensions[d] = dimensions[d]; // Global dimensions
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_gdimensions[d] = _fdimensions[d]; // Global dimensions
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_simd_layout[d] = simd_layout[d];
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_fsites = _fsites * _fdimensions[d];
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_gsites = _gsites * _gdimensions[d];
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//FIXME check for exact division
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@ -62,14 +62,17 @@ public:
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_ostride.resize(_ndimension);
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_istride.resize(_ndimension);
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_osites = 1;
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_isites = 1;
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_fsites = _gsites = _osites = _isites = 1;
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for(int d=0;d<_ndimension;d++){
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_fdimensions[d] = dimensions[d];
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_gdimensions[d] = _fdimensions[d];
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_fsites = _fsites * _fdimensions[d];
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_gsites = _gsites * _gdimensions[d];
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if (d==0) _gdimensions[0] = _gdimensions[0]/2; // Remove a checkerboard
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_ldimensions[d] = _gdimensions[d]/_processors[d];
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// Use a reduced simd grid
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_simd_layout[d] = simd_layout[d];
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_rdimensions[d]= _ldimensions[d]/_simd_layout[d];
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@ -9,6 +9,10 @@ namespace Grid {
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assert(lhs._grid == rhs._grid);
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assert(lhs.checkerboard == rhs.checkerboard);
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}
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void inline conformable(const GridBase *lhs,GridBase *rhs)
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{
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assert(lhs == rhs);
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}
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}
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#endif
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@ -1,32 +1,136 @@
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#ifndef GRID_LATTICE_RNG_H
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#define GRID_LATTICE_RNG_H
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#include <random>
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namespace Grid {
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// FIXME Randomise; deprecate this
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template <class vobj> inline void random(Lattice<vobj> &l){
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Real *v_ptr = (Real *)&l._odata[0];
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size_t v_len = l._grid->oSites()*sizeof(vobj);
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size_t d_len = v_len/sizeof(Real);
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for(int i=0;i<d_len;i++){
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// Wrap seed_seq to give common interface with random_device
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class fixedSeed {
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public:
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v_ptr[i]=drand48();
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}
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};
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typedef std::seed_seq::result_type result_type;
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std::seed_seq src;
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// FIXME Implement a consistent seed management strategy
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template <class vobj> inline void gaussian(Lattice<vobj> &l){
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// Zero mean, unit variance.
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std::normal_distribution<double> distribution(0.0,1.0);
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Real *v_ptr = (Real *)&l._odata[0];
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size_t v_len = l._grid->oSites()*sizeof(vobj);
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size_t d_len = v_len/sizeof(Real);
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fixedSeed(std::vector<int> &seeds) : src(seeds.begin(),seeds.end()) {};
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for(int i=0;i<d_len;i++){
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v_ptr[i]= drand48();
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}
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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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}
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};
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class GridRNG {
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public:
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// One generator per site.
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std::vector<std::ranlux48> _generators;
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// Uniform and Gaussian distributions from these generators.
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std::uniform_real_distribution<double> _uniform;
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std::normal_distribution<double> _gaussian;
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GridBase *_grid;
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int _vol;
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int generator_idx(int os,int is){
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return is*_grid->oSites()+os;
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}
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GridRNG(GridBase *grid) : _uniform{0,1}, _gaussian(0.0,1.0) {
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_grid=grid;
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_vol =_grid->iSites()*_grid->oSites();
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_generators.resize(_vol);
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// SeedFixedIntegers(seeds);
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// worst case we seed properly but non-deterministically
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SeedRandomDevice();
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}
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// FIXME: drive seeding from node zero and transmit to all
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// to get unique randoms on each node
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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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}
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void SeedFixedIntegers(std::vector<int> &seeds){
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fixedSeed src(seeds);
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Seed(src);
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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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for(int gidx=0;gidx<_grid->_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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typename source::result_type init = src();
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_grid->Broadcast(0,(void *)&init,sizeof(init));
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if( rank == _grid->ThisRank() ){
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_generators[l_idx] = std::ranlux48(init);
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}
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}
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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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//void LoadState(const std::string<char> &file);
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template <class vobj,class distribution> inline void fill(Lattice<vobj> &l,distribution &dist){
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typedef typename vobj::scalar_type scalar_type;
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typedef typename vobj::vector_type vector_type;
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conformable(_grid,l._grid);
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int Nsimd =_grid->Nsimd();
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int osites=_grid->oSites();
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int words = sizeof(vobj)/sizeof(vector_type);
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std::vector<std::vector<scalar_type> > buf(Nsimd,std::vector<scalar_type>(words));
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std::vector<scalar_type *> pointers(Nsimd);
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for(int ss=0;ss<osites;ss++){
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for(int si=0;si<Nsimd;si++){
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int gdx = generator_idx(ss,si); // index of generator state
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pointers[si] = (scalar_type *)&buf[si][0];
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for(int idx=0;idx<words;idx++){
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pointers[si][idx] = dist(_generators[gdx]);
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}
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}
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// merge into SIMD lanes
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merge(l._odata[ss],pointers);
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}
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};
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};
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// FIXME Implement a consistent seed management strategy
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template <class vobj> inline void random(GridRNG &rng,Lattice<vobj> &l){
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rng.fill(l,rng._uniform);
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}
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template <class vobj> inline void gaussian(GridRNG &rng,Lattice<vobj> &l){
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rng.fill(l,rng._gaussian);
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}
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}
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#endif
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@ -57,7 +57,8 @@ int main (int argc, char ** argv)
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GridCartesian Fine(latt_size,simd_layout,mpi_layout);
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GridRedBlackCartesian rbFine(latt_size,simd_layout,mpi_layout);
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GridRNG FineRNG(&Fine);
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LatticeColourMatrix Foo(&Fine);
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LatticeColourMatrix Bar(&Fine);
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@ -91,17 +92,17 @@ int main (int argc, char ** argv)
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iSpinMatrix<vComplex> iGammaFive;
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ColourMatrix cmat;
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random(Foo);
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gaussian(Bar);
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random(scFoo);
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random(scBar);
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random(FineRNG,Foo);
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gaussian(FineRNG,Bar);
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random(FineRNG,scFoo);
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random(FineRNG,scBar);
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random(cMat);
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random(sMat);
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random(scMat);
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random(cVec);
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random(sVec);
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random(scVec);
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random(FineRNG,cMat);
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random(FineRNG,sMat);
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random(FineRNG,scMat);
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random(FineRNG,cVec);
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random(FineRNG,sVec);
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random(FineRNG,scVec);
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fflush(stdout);
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cVec = cMat * cVec; // LatticeColourVector = LatticeColourMatrix * LatticeColourVector
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@ -277,7 +278,7 @@ int main (int argc, char ** argv)
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peekSite(bar,Bar,coor);
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for(int r=0;r<3;r++){
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for(int c=0;c<3;c++){
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cout<<"bar "<<coor[0]<<coor[1]<<coor[2]<<coor[3] <<" "<<bar()()(r,c)<<std::endl;
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// cout<<"bar "<<coor[0]<<coor[1]<<coor[2]<<coor[3] <<" "<<bar()()(r,c)<<std::endl;
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}}
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}}}}
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}
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GridCartesian Fine(latt_size,simd_layout,mpi_layout);
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GridRedBlackCartesian rbFine(latt_size,simd_layout,mpi_layout);
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GridRNG fRNG(&Fine);
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LatticeColourMatrix Foo(&Fine);
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LatticeColourMatrix Bar(&Fine);
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LatticeColourMatrix Check(&Fine);
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LatticeColourMatrix Diff(&Fine);
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random(Foo);
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gaussian(Bar);
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random(fRNG,Foo);
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gaussian(fRNG,Bar);
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for(int dir=0;dir<4;dir++){
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