Loading src/Benchmarks/SpMV/spmv.h +11 −11 Original line number Diff line number Diff line Loading @@ -202,17 +202,6 @@ benchmarkSpMV( Benchmark& benchmark, // Copy the values resultHostVector2 = hostVector2; // Setup cuSPARSE MetaData, since it has the same header as CSR, // and therefore will not get its own headers (rows, cols, speedup etc.) in log. // * Not setting this up causes (among other undiscovered errors) the speedup from CPU to GPU on the input format to be overwritten. benchmark.setMetadataColumns( Benchmark::MetadataColumns({ { "matrix name", convertToString( getMatrixFileName( inputFileName ) ) }, { "non-zeros", convertToString( hostMatrix.getNumberOfNonzeroMatrixElements() ) }, { "rows", convertToString( hostMatrix.getRows() ) }, { "columns", convertToString( hostMatrix.getColumns() ) }, { "matrix format", convertToString( "CSR-cuSPARSE" ) } } )); #ifdef HAVE_CUDA benchmark.time< Devices::Cuda >( reset, "GPU", spmvCuda ); Loading @@ -224,6 +213,17 @@ benchmarkSpMV( Benchmark& benchmark, resultDeviceVector2 = deviceVector2; // Setup cuSPARSE MetaData, since it has the same header as CSR, // and therefore will not get its own headers (rows, cols, speedup etc.) in log. // * Not setting this up causes (among other undiscovered errors) the speedup from CPU to GPU on the input format to be overwritten. benchmark.setMetadataColumns( Benchmark::MetadataColumns({ { "matrix name", convertToString( getMatrixFileName( inputFileName ) ) }, { "non-zeros", convertToString( hostMatrix.getNumberOfNonzeroMatrixElements() ) }, { "rows", convertToString( hostMatrix.getRows() ) }, { "columns", convertToString( hostMatrix.getColumns() ) }, { "matrix format", convertToString( "CSR-cuSPARSE" ) } } )); benchmark.time< Devices::Cuda >( reset, "GPU", spmvCusparse ); HostVector resultcuSPARSEDeviceVector2; Loading Loading
src/Benchmarks/SpMV/spmv.h +11 −11 Original line number Diff line number Diff line Loading @@ -202,17 +202,6 @@ benchmarkSpMV( Benchmark& benchmark, // Copy the values resultHostVector2 = hostVector2; // Setup cuSPARSE MetaData, since it has the same header as CSR, // and therefore will not get its own headers (rows, cols, speedup etc.) in log. // * Not setting this up causes (among other undiscovered errors) the speedup from CPU to GPU on the input format to be overwritten. benchmark.setMetadataColumns( Benchmark::MetadataColumns({ { "matrix name", convertToString( getMatrixFileName( inputFileName ) ) }, { "non-zeros", convertToString( hostMatrix.getNumberOfNonzeroMatrixElements() ) }, { "rows", convertToString( hostMatrix.getRows() ) }, { "columns", convertToString( hostMatrix.getColumns() ) }, { "matrix format", convertToString( "CSR-cuSPARSE" ) } } )); #ifdef HAVE_CUDA benchmark.time< Devices::Cuda >( reset, "GPU", spmvCuda ); Loading @@ -224,6 +213,17 @@ benchmarkSpMV( Benchmark& benchmark, resultDeviceVector2 = deviceVector2; // Setup cuSPARSE MetaData, since it has the same header as CSR, // and therefore will not get its own headers (rows, cols, speedup etc.) in log. // * Not setting this up causes (among other undiscovered errors) the speedup from CPU to GPU on the input format to be overwritten. benchmark.setMetadataColumns( Benchmark::MetadataColumns({ { "matrix name", convertToString( getMatrixFileName( inputFileName ) ) }, { "non-zeros", convertToString( hostMatrix.getNumberOfNonzeroMatrixElements() ) }, { "rows", convertToString( hostMatrix.getRows() ) }, { "columns", convertToString( hostMatrix.getColumns() ) }, { "matrix format", convertToString( "CSR-cuSPARSE" ) } } )); benchmark.time< Devices::Cuda >( reset, "GPU", spmvCusparse ); HostVector resultcuSPARSEDeviceVector2; Loading