/*************************************************************************** spmv.h - description ------------------- begin : Dec 30, 2015 copyright : (C) 2015 by Tomas Oberhuber et al. email : tomas.oberhuber@fjfi.cvut.cz ***************************************************************************/ /* See Copyright Notice in tnl/Copyright */ // Implemented by: Jakub Klinkovsky #pragma once #include "../Benchmarks.h" #include <TNL/Pointers/DevicePointer.h> #include <TNL/Matrices/CSR.h> #include <TNL/Matrices/Ellpack.h> #include <TNL/Matrices/SlicedEllpack.h> #include <TNL/Matrices/ChunkedEllpack.h> #include <TNL/Matrices/MatrixReader.h> using namespace TNL::Matrices; namespace TNL { namespace Benchmarks { // silly alias to match the number of template parameters with other formats template< typename Real, typename Device, typename Index > using SlicedEllpack = Matrices::SlicedEllpack< Real, Device, Index >; // Get only the name of the format from getType(). template< typename Matrix > std::string getMatrixFormat( const Matrix& matrix ) { std::string mtrxFullType = matrix.getType(); std::string mtrxType = mtrxFullType.substr(0, mtrxFullType.find("<")); std::string format = mtrxType.substr(mtrxType.find(':') + 2); return format; } template< typename Matrix > void printMatrixInfo( const Matrix& matrix, std::ostream& str ) { str << "\n Format: " << getMatrixFormat( matrix ) << std::endl; str << " Rows: " << matrix.getRows() << std::endl; str << " Cols: " << matrix.getColumns() << std::endl; str << " Nonzero Elements: " << matrix.getNumberOfNonzeroMatrixElements() << std::endl; } template< typename Real, template< typename, typename, typename > class Matrix, template< typename, typename, typename > class Vector = Containers::Vector > bool benchmarkSpMV( Benchmark & benchmark, const String & inputFileName ) { typedef Matrix< Real, Devices::Host, int > HostMatrix; typedef Matrix< Real, Devices::Cuda, int > DeviceMatrix; typedef Containers::Vector< Real, Devices::Host, int > HostVector; typedef Containers::Vector< Real, Devices::Cuda, int > CudaVector; HostMatrix hostMatrix; DeviceMatrix deviceMatrix; HostVector hostVector, hostVector2; CudaVector deviceVector, deviceVector2; try { if( ! MatrixReader< HostMatrix >::readMtxFile( inputFileName, hostMatrix ) ) { std::cerr << "Failed to read the matrix file " << inputFileName << "." << std::endl; std::string matrixFormat = getMatrixFormat( hostMatrix ); std::string stringErrorMsg = "Failed to read the matrix file " + ( std::string )inputFileName + ".\n" + "matrix format: " + matrixFormat + "\nBenchmark failed: Unable to read the matrix."; char *errorMsg = &stringErrorMsg[0u]; benchmark.addErrorMessage( errorMsg, 3 ); return false; } } catch( std::bad_alloc ) { std::cerr << "Failed to allocate memory to read the matrix file " << inputFileName << "." << std::endl; std::string matrixFormat = getMatrixFormat( hostMatrix ); std::string stringErrorMsg = "Failed to allocate memory to read the matrix file " + ( std::string )inputFileName + ".\n" + "matrix format: " + matrixFormat + "\nBenchmark failed: Not enough memory."; char *errorMsg = &stringErrorMsg[0u]; benchmark.addErrorMessage( errorMsg, 3 ); return false; } // printMatrixInfo is redundant, because all the information is in the Benchmark's MetadataColumns. // printMatrixInfo( hostMatrix, std::cout ); #ifdef HAVE_CUDA // FIXME: This doesn't work for ChunkedEllpack, because // its cross-device assignment is not implemented yet. deviceMatrix = hostMatrix; #endif benchmark.setMetadataColumns( Benchmark::MetadataColumns({ { "matrix format", convertToString( getMatrixFormat( hostMatrix ) ) }, { "non-zeros", convertToString( hostMatrix.getNumberOfNonzeroMatrixElements() ) }, { "rows", convertToString( hostMatrix.getRows() ) }, { "columns", convertToString( hostMatrix.getColumns() ) } } )); hostVector.setSize( hostMatrix.getColumns() ); hostVector2.setSize( hostMatrix.getRows() ); #ifdef HAVE_CUDA deviceVector.setSize( hostMatrix.getColumns() ); deviceVector2.setSize( hostMatrix.getRows() ); #endif // reset function auto reset = [&]() { hostVector.setValue( 1.0 ); hostVector2.setValue( 0.0 ); #ifdef HAVE_CUDA deviceVector.setValue( 1.0 ); deviceVector2.setValue( 0.0 ); #endif }; const int elements = hostMatrix.getNumberOfNonzeroMatrixElements(); const double datasetSize = (double) elements * ( 2 * sizeof( Real ) + sizeof( int ) ) / oneGB; // compute functions auto spmvHost = [&]() { hostMatrix.vectorProduct( hostVector, hostVector2 ); }; auto spmvCuda = [&]() { deviceMatrix.vectorProduct( deviceVector, deviceVector2 ); }; benchmark.setOperation( datasetSize ); benchmark.time< Devices::Host >( reset, "CPU", spmvHost ); #ifdef HAVE_CUDA benchmark.time< Devices::Cuda >( reset, "GPU", spmvCuda ); #endif std::cout << std::endl; return true; } template< typename Real = double, typename Index = int > bool benchmarkSpmvSynthetic( Benchmark & benchmark, const String& inputFileName ) { bool result = true; // TODO: benchmark all formats from tnl-benchmark-spmv (different parameters of the base formats) result |= benchmarkSpMV< Real, Matrices::CSR >( benchmark, inputFileName ); result |= benchmarkSpMV< Real, Matrices::Ellpack >( benchmark, inputFileName ); result |= benchmarkSpMV< Real, SlicedEllpack >( benchmark, inputFileName ); // result |= benchmarkSpMV< Real, Matrices::ChunkedEllpack >( benchmark, inputFileName ); return result; } } // namespace Benchmarks } // namespace TNL