/************************************************************************************* Grid physics library, www.github.com/paboyle/Grid Source file: Hadrons/Modules/MDistil/Distil.hpp Copyright (C) 2015-2019 Author: Felix Erben Author: Michael Marshall This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 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 */ #ifndef Hadrons_MDistil_Distil_hpp_ #define Hadrons_MDistil_Distil_hpp_ #include #include #include /****************************************************************************** Needed to make sure envCreate() (see Hadrons) works with specialisations with more than one parameter, eg obj I imagine this exists already? ******************************************************************************/ #ifndef COMMA #define COMMA , #endif /****************************************************************************** A consistent set of cross-platform methods for big endian <-> host byte ordering I imagine this exists already? ******************************************************************************/ #if defined(__linux__) # include #elif defined(__FreeBSD__) || defined(__NetBSD__) # include #elif defined(__OpenBSD__) # include # define be16toh(x) betoh16(x) # define be32toh(x) betoh32(x) # define be64toh(x) betoh64(x) #elif defined(__APPLE__) #include #define htobe16(x) OSSwapHostToBigInt16(x) #define htole16(x) OSSwapHostToLittleInt16(x) #define be16toh(x) OSSwapBigToHostInt16(x) #define le16toh(x) OSSwapLittleToHostInt16(x) #define htobe32(x) OSSwapHostToBigInt32(x) #define htole32(x) OSSwapHostToLittleInt32(x) #define be32toh(x) OSSwapBigToHostInt32(x) #define le32toh(x) OSSwapLittleToHostInt32(x) #define htobe64(x) OSSwapHostToBigInt64(x) #define htole64(x) OSSwapHostToLittleInt64(x) #define be64toh(x) OSSwapBigToHostInt64(x) #define le64toh(x) OSSwapLittleToHostInt64(x) #endif /****************************************************************************** This potentially belongs in CartesianCommunicator Turns out I don't actually need this when running inside hadrons ******************************************************************************/ BEGIN_MODULE_NAMESPACE(Grid) inline void SliceShare( GridBase * gridLowDim, GridBase * gridHighDim, void * Buffer, int BufferSize ) { // Work out which dimension is the spread-out dimension assert(gridLowDim); assert(gridHighDim); const int iNumDims{(const int)gridHighDim->_gdimensions.size()}; assert(iNumDims == gridLowDim->_gdimensions.size()); int dimSpreadOut = -1; std::vector coor(iNumDims); for( int i = 0 ; i < iNumDims ; i++ ) { coor[i] = gridHighDim->_processor_coor[i]; if( gridLowDim->_gdimensions[i] != gridHighDim->_gdimensions[i] ) { assert( dimSpreadOut == -1 ); assert( gridLowDim->_processors[i] == 1 ); // easiest assumption to make for now dimSpreadOut = i; } } if( dimSpreadOut != -1 && gridHighDim->_processors[dimSpreadOut] != gridLowDim->_processors[dimSpreadOut] ) { // Make sure the same number of data elements exist on each slice const int NumSlices{gridHighDim->_processors[dimSpreadOut] / gridLowDim->_processors[dimSpreadOut]}; assert(gridHighDim->_processors[dimSpreadOut] == gridLowDim->_processors[dimSpreadOut] * NumSlices); const int SliceSize{BufferSize/NumSlices}; //CCC_DEBUG_DUMP(Buffer, NumSlices, SliceSize); assert(BufferSize == SliceSize * NumSlices); //#ifndef USE_LOCAL_SLICES // assert(0); // Can't do this without MPI (should really test whether MPI is defined) //#else const auto MyRank{gridHighDim->ThisRank()}; std::vector reqs(0); int MySlice{coor[dimSpreadOut]}; char * const _buffer{(char *)Buffer}; char * const MyData{_buffer + MySlice * SliceSize}; for(int i = 1; i < NumSlices ; i++ ){ int SendSlice = ( MySlice + i ) % NumSlices; int RecvSlice = ( MySlice - i + NumSlices ) % NumSlices; char * const RecvData{_buffer + RecvSlice * SliceSize}; coor[dimSpreadOut] = SendSlice; const auto SendRank{gridHighDim->RankFromProcessorCoor(coor)}; coor[dimSpreadOut] = RecvSlice; const auto RecvRank{gridHighDim->RankFromProcessorCoor(coor)}; std::cout << GridLogMessage << "Send slice " << MySlice << " (" << MyRank << ") to " << SendSlice << " (" << SendRank << "), receive slice from " << RecvSlice << " (" << RecvRank << ")" << std::endl; gridHighDim->SendToRecvFromBegin(reqs,MyData,SendRank,RecvData,RecvRank,SliceSize); //memcpy(RecvData,MyData,SliceSize); // Debug } gridHighDim->SendToRecvFromComplete(reqs); std::cout << GridLogMessage << "Slice data shared." << std::endl; //CCC_DEBUG_DUMP(Buffer, NumSlices, SliceSize); //#endif } } /************************************************************************************* -Grad^2 (Peardon, 2009, pg 2, equation 3) Field Type of field the operator will be applied to GaugeField Gauge field the operator will smear using TODO CANDIDATE for integration into laplacian operator should just require adding number of dimensions to act on to constructor, where the default=all dimensions, but we could specify 3 spatial dimensions *************************************************************************************/ template class LinOpPeardonNabla : public LinearOperatorBase, public LinearFunction { typedef typename GaugeField::vector_type vCoeff_t; protected: // I don't really mind if _gf is messed with ... so make this public? //GaugeField & _gf; int nd; // number of spatial dimensions std::vector > > U; public: // Construct this operator given a gauge field and the number of dimensions it should act on LinOpPeardonNabla( GaugeField& gf, int dimSpatial = Grid::QCD::Tdir ) : /*_gf(gf),*/ nd{dimSpatial} { assert(dimSpatial>=1); for( int mu = 0 ; mu < nd ; mu++ ) U.push_back(PeekIndex(gf,mu)); } // Apply this operator to "in", return result in "out" void operator()(const Field& in, Field& out) { assert( nd <= in._grid->Nd() ); conformable( in, out ); out = ( ( Real ) ( 2 * nd ) ) * in; Field _tmp(in._grid); typedef typename GaugeField::vector_type vCoeff_t; //Lattice > U(in._grid); for( int mu = 0 ; mu < nd ; mu++ ) { //U = PeekIndex(_gf,mu); out -= U[mu] * Cshift( in, mu, 1); _tmp = adj( U[mu] ) * in; out -= Cshift(_tmp,mu,-1); } } void OpDiag (const Field &in, Field &out) { assert(0); }; void OpDir (const Field &in, Field &out,int dir,int disp) { assert(0); }; void Op (const Field &in, Field &out) { assert(0); }; void AdjOp (const Field &in, Field &out) { assert(0); }; void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2) { assert(0); }; void HermOp(const Field &in, Field &out) { operator()(in,out); }; }; template class LinOpPeardonNablaHerm : public LinearFunction { public: OperatorFunction & _poly; LinearOperatorBase &_Linop; LinOpPeardonNablaHerm(OperatorFunction & poly,LinearOperatorBase& linop) : _poly(poly), _Linop(linop) { } void operator()(const Field& in, Field& out) { _poly(_Linop,in,out); } }; END_MODULE_NAMESPACE // Grid /****************************************************************************** Common elements for distillation ******************************************************************************/ BEGIN_HADRONS_NAMESPACE BEGIN_MODULE_NAMESPACE(MDistil) typedef Grid::Hadrons::EigenPack DistilEP; typedef std::vector > > DistilNoises; /****************************************************************************** Make a lower dimensional grid ******************************************************************************/ inline GridCartesian * MakeLowerDimGrid( GridCartesian * gridHD ) { //LOG(Message) << "MakeLowerDimGrid() begin" << std::endl; int nd{static_cast(gridHD->_ndimension)}; std::vector latt_size = gridHD->_gdimensions; latt_size[nd-1] = 1; std::vector simd_layout = GridDefaultSimd(nd-1, vComplex::Nsimd()); simd_layout.push_back( 1 ); std::vector mpi_layout = gridHD->_processors; mpi_layout[nd-1] = 1; GridCartesian * gridLD = new GridCartesian(latt_size,simd_layout,mpi_layout,*gridHD); //LOG(Message) << "MakeLowerDimGrid() end" << std::endl; return gridLD; } /****************************************************************************** Perambulator object ******************************************************************************/ template class NamedTensor : public Eigen::Tensor { public: typedef Eigen::Tensor ET; std::array IndexNames; public: template EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE NamedTensor(std::array &IndexNames_, Eigen::Index firstDimension, IndexTypes... otherDimensions) : IndexNames{IndexNames_}, Eigen::Tensor(firstDimension, otherDimensions...) { // The number of dimensions used to construct a tensor must be equal to the rank of the tensor. EIGEN_STATIC_ASSERT(sizeof...(otherDimensions) + 1 == NumIndices_, YOU_MADE_A_PROGRAMMING_MISTAKE) } // Share data for timeslices we calculated with other nodes inline void SliceShare( GridCartesian * gridLowDim, GridCartesian * gridHighDim ) { Grid::SliceShare( gridLowDim, gridHighDim, this->data(), (int) (this->size() * sizeof(Scalar_))); } // load and save - not virtual - probably all changes inline void load(const std::string filename); inline void save(const std::string filename) const; inline void ReadBinary(const std::string filename); inline void WriteBinary(const std::string filename); }; /****************************************************************************** Save NamedTensor binary format (NB: On-disk format is Big Endian) ******************************************************************************/ template void NamedTensor::WriteBinary(const std::string filename) { LOG(Message) << "Writing NamedTensor to \"" << filename << "\"" << std::endl; std::ofstream w(filename, std::ios::binary); // Number of Scalar_Unit objects per Scalar_ constexpr unsigned int Scalar_Unit_Size{sizeof(Scalar_Unit)}; assert((Scalar_Unit_Size == 2 || Scalar_Unit_Size == 4 || Scalar_Unit_Size == 8 ) && "Scalar_Unit_Size should be 2, 4 or 8"); assert((sizeof(Scalar_) % Scalar_Unit_Size) == 0 && "Scalar_ is not composed of Scalar_Unit_Size" ); // Size of the data (in bytes) const auto NumElements{this->size()}; const std::streamsize TotalDataSize{static_cast(NumElements * sizeof(Scalar_))}; uint64_t u64 = htobe64(static_cast(TotalDataSize)); w.write(reinterpret_cast(&u64), sizeof(u64)); // number of dimensions which aren't 1 uint16_t u16 = static_cast(this->NumIndices); for( auto dim : this->dimensions() ) if( dim == 1 ) u16--; u16 = htobe16( u16 ); w.write(reinterpret_cast(&u16), sizeof(u16)); // dimensions together with names int d = 0; for( auto dim : this->dimensions() ) { if( dim != 1 ) { // size of this dimension u16 = htobe16( static_cast( dim ) ); w.write(reinterpret_cast(&u16), sizeof(u16)); // length of this dimension name u16 = htobe16( static_cast( IndexNames[d].size() ) ); w.write(reinterpret_cast(&u16), sizeof(u16)); // dimension name w.write(IndexNames[d].c_str(), IndexNames[d].size()); } d++; } // Actual data char * const pStart{reinterpret_cast(this->data())}; // Swap to network byte order in place (alternative is to copy memory - still slow) void * const pEnd{pStart + TotalDataSize}; if(Scalar_Unit_Size == 8) for(uint64_t * p = reinterpret_cast(pStart) ; p < pEnd ; p++ ) * p = htobe64( * p ); else if(Scalar_Unit_Size == 4) for(uint32_t * p = reinterpret_cast(pStart) ; p < pEnd ; p++ ) * p = htobe32( * p ); else if(Scalar_Unit_Size == 2) for(uint16_t * p = reinterpret_cast(pStart) ; p < pEnd ; p++ ) * p = htobe16( * p ); w.write(pStart, TotalDataSize); // Swap back from network byte order if(Scalar_Unit_Size == 8) for(uint64_t * p = reinterpret_cast(pStart) ; p < pEnd ; p++ ) * p = be64toh( * p ); else if(Scalar_Unit_Size == 4) for(uint32_t * p = reinterpret_cast(pStart) ; p < pEnd ; p++ ) * p = be32toh( * p ); else if(Scalar_Unit_Size == 2) for(uint16_t * p = reinterpret_cast(pStart) ; p < pEnd ; p++ ) * p = be16toh( * p ); // checksum #ifdef USE_IPP uint32_t u32 = htobe32(GridChecksum::crc32c(this->data(), TotalDataSize)); #else uint32_t u32 = htobe32(GridChecksum::crc32(this->data(), TotalDataSize)); #endif w.write(reinterpret_cast(&u32), sizeof(u32)); } /****************************************************************************** Load NamedTensor binary format (NB: On-disk format is Big Endian) ******************************************************************************/ template void NamedTensor::ReadBinary(const std::string filename) { LOG(Message) << "Reading NamedTensor from \"" << filename << "\"" << std::endl; std::ifstream r(filename, std::ios::binary); // Number of Scalar_Unit objects per Scalar_ constexpr unsigned int Scalar_Unit_Size{sizeof(Scalar_Unit)}; assert((Scalar_Unit_Size == 2 || Scalar_Unit_Size == 4 || Scalar_Unit_Size == 8 ) && "Scalar_Unit_Size should be 2, 4 or 8"); assert((sizeof(Scalar_) % Scalar_Unit_Size) == 0 && "Scalar_ is not composed of Scalar_Unit_Size" ); // Size of the data in bytes const auto NumElements{this->size()}; const std::streamsize TotalDataSize{static_cast(NumElements * sizeof(Scalar_))}; uint64_t u64; r.read(reinterpret_cast(&u64), sizeof(u64)); assert( TotalDataSize == be64toh( u64 ) && "Error: Size of the data in bytes" ); // number of dimensions which aren't 1 uint16_t u16; r.read(reinterpret_cast(&u16), sizeof(u16)); u16 = be16toh( u16 ); for( auto dim : this->dimensions() ) if( dim == 1 ) u16++; assert( this->NumIndices == u16 && "Error: number of dimensions which aren't 1" ); // dimensions together with names int d = 0; for( auto dim : this->dimensions() ) { if( dim != 1 ) { // size of dimension r.read(reinterpret_cast(&u16), sizeof(u16)); assert( dim == be16toh( u16 ) && "size of dimension" ); // length of dimension name r.read(reinterpret_cast(&u16), sizeof(u16)); size_t l = be16toh( u16 ); assert( l == IndexNames[d].size() && "length of dimension name" ); // dimension name std::string s( l, '?' ); r.read(&s[0], l); assert( s == IndexNames[d] && "dimension name" ); } d++; } // Actual data char * const pStart{reinterpret_cast(this->data())}; void * const pEnd{pStart + TotalDataSize}; r.read(pStart,TotalDataSize); // Swap back from network byte order if(Scalar_Unit_Size == 8) for(uint64_t * p = reinterpret_cast(pStart) ; p < pEnd ; p++ ) * p = be64toh( * p ); else if(Scalar_Unit_Size == 4) for(uint32_t * p = reinterpret_cast(pStart) ; p < pEnd ; p++ ) * p = be32toh( * p ); else if(Scalar_Unit_Size == 2) for(uint16_t * p = reinterpret_cast(pStart) ; p < pEnd ; p++ ) * p = be16toh( * p ); // checksum uint32_t u32; r.read(reinterpret_cast(&u32), sizeof(u32)); u32 = be32toh( u32 ); #ifdef USE_IPP u32 -= GridChecksum::crc32c(this->data(), TotalDataSize); #else u32 -= GridChecksum::crc32(this->data(), TotalDataSize); #endif assert( u32 == 0 && "Perambulator checksum invalid"); } /****************************************************************************** Save NamedTensor Hdf5 format ******************************************************************************/ template void NamedTensor::save(const std::string filename) const { LOG(Message) << "Writing NamedTensor to \"" << filename << "\"" << std::endl; #ifndef HAVE_HDF5 LOG(Message) << "Error: I/O for NamedTensor requires HDF5" << std::endl; #else Hdf5Writer w(filename); //w << this->NumIndices << this->dimensions() << this->IndexNames; #endif } /****************************************************************************** Load NamedTensor Hdf5 format ******************************************************************************/ template void NamedTensor::load(const std::string filename) { LOG(Message) << "Reading NamedTensor from \"" << filename << "\"" << std::endl; #ifndef HAVE_HDF5 LOG(Message) << "Error: I/O for NamedTensor requires HDF5" << std::endl; #else Hdf5Reader r(filename); typename ET::Dimensions d; std::array n; //r >> this->NumIndices >> d >> n; //this->IndexNames = n; #endif } /****************************************************************************** Perambulator object ******************************************************************************/ template using Perambulator = NamedTensor; /************************************************************************************* Rotate eigenvectors into our phase convention First component of first eigenvector is real and positive *************************************************************************************/ inline void RotateEigen(std::vector & evec) { ColourVector cv0; auto grid = evec[0]._grid; std::vector siteFirst(grid->Nd(),0); peekSite(cv0, evec[0], siteFirst); auto & cplx0 = cv0()()(0); if( std::imag(cplx0) == 0 ) std::cout << GridLogMessage << "RotateEigen() : Site 0 : " << cplx0 << " => already meets phase convention" << std::endl; else { const auto cplx0_mag{std::abs(cplx0)}; const auto phase{std::conj(cplx0 / cplx0_mag)}; std::cout << GridLogMessage << "RotateEigen() : Site 0 : |" << cplx0 << "|=" << cplx0_mag << " => phase=" << (std::arg(phase) / 3.14159265) << " pi" << std::endl; { // TODO: Only really needed on the master slice for( int k = 0 ; k < evec.size() ; k++ ) evec[k] *= phase; if(grid->IsBoss()){ for( int c = 0 ; c < Nc ; c++ ) cv0()()(c) *= phase; cplx0.imag(0); // This assumes phase convention is real, positive (so I get rid of rounding error) //pokeSite(cv0, evec[0], siteFirst); pokeLocalSite(cv0, evec[0], siteFirst); } } } } END_MODULE_NAMESPACE END_HADRONS_NAMESPACE #endif // Hadrons_MDistil_Distil_hpp_