diff --git a/src/Benchmarks/SpMV/ReferenceFormats/cusparseCSRMatrixLegacy.h b/src/Benchmarks/SpMV/ReferenceFormats/cusparseCSRMatrixLegacy.h
new file mode 100644
index 0000000000000000000000000000000000000000..133723e988b5cb21177ea440c397d182a654ef05
--- /dev/null
+++ b/src/Benchmarks/SpMV/ReferenceFormats/cusparseCSRMatrixLegacy.h
@@ -0,0 +1,171 @@
+/***************************************************************************
+ tnlCusparseCSRLegacy.h - description
+ -------------------
+ begin : Feb 1, 2021
+ copyright : (C) 2021 by Tomas Oberhuber
+ email : tomas.oberhuber@fjfi.cvut.cz
+ ***************************************************************************/
+
+/* See Copyright Notice in tnl/Copyright */
+
+#include <TNL/Assert.h>
+#include <TNL/Devices/Cuda.h>
+#include <Benchmarks/SpMV/ReferenceFormats/Legacy/CSR.h>
+#ifdef HAVE_CUDA
+#include <cusparse.h>
+#endif
+
+namespace TNL {
+
+template< typename Real >
+class CusparseCSRBaseLegacy
+{
+ public:
+ using RealType = Real;
+ using DeviceType = TNL::Devices::Cuda;
+ using MatrixType = Benchmarks::SpMV::ReferenceFormats::Legacy::CSR< Real, Devices::Cuda, int >;
+
+ CusparseCSRBaseLegacy()
+ : matrix( 0 )
+ {
+ };
+
+#ifdef HAVE_CUDA
+ void init( const MatrixType& matrix,
+ cusparseHandle_t* cusparseHandle )
+ {
+ this->matrix = &matrix;
+ this->cusparseHandle = cusparseHandle;
+ cusparseCreateMatDescr( & this->matrixDescriptor );
+ };
+#endif
+
+ int getRows() const
+ {
+ return matrix->getRows();
+ }
+
+ int getColumns() const
+ {
+ return matrix->getColumns();
+ }
+
+ int getNumberOfMatrixElements() const
+ {
+ return matrix->getAllocatedElementsCount();
+ }
+
+
+ template< typename InVector,
+ typename OutVector >
+ void vectorProduct( const InVector& inVector,
+ OutVector& outVector ) const
+ {
+ TNL_ASSERT_TRUE( matrix, "matrix was not initialized" );
+#ifdef HAVE_CUDA
+#if CUDART_VERSION >= 11000
+ throw std::runtime_error("cusparseDcsrmv was removed in CUDA 11.");
+#else
+ cusparseDcsrmv( *( this->cusparseHandle ),
+ CUSPARSE_OPERATION_NON_TRANSPOSE,
+ this->matrix->getRows(),
+ this->matrix->getColumns(),
+ this->matrix->values.getSize(),
+ 1.0,
+ this->matrixDescriptor,
+ this->matrix->values.getData(),
+ this->matrix->getRowPointers().getData(),
+ this->matrix->columnIndexes.getData(),
+ inVector.getData(),
+ 1.0,
+ outVector.getData() );
+#endif
+#endif
+ }
+
+ protected:
+
+ const MatrixType* matrix;
+#ifdef HAVE_CUDA
+ cusparseHandle_t* cusparseHandle;
+
+ cusparseMatDescr_t matrixDescriptor;
+#endif
+};
+
+
+template< typename Real >
+class CusparseCSRLegacy
+{};
+
+template<>
+class CusparseCSRLegacy< double > : public CusparseCSRBaseLegacy< double >
+{
+ public:
+
+ template< typename InVector,
+ typename OutVector >
+ void vectorProduct( const InVector& inVector,
+ OutVector& outVector ) const
+ {
+ TNL_ASSERT_TRUE( matrix, "matrix was not initialized" );
+#ifdef HAVE_CUDA
+#if CUDART_VERSION >= 11000
+ throw std::runtime_error("cusparseDcsrmv was removed in CUDA 11.");
+#else
+ double d = 1.0;
+ double* alpha = &d;
+ cusparseDcsrmv( *( this->cusparseHandle ),
+ CUSPARSE_OPERATION_NON_TRANSPOSE,
+ this->matrix->getRows(),
+ this->matrix->getColumns(),
+ this->matrix->getValues().getSize(),
+ alpha,
+ this->matrixDescriptor,
+ this->matrix->getValues().getData(),
+ this->matrix->getRowPointers().getData(),
+ this->matrix->getColumnIndexes().getData(),
+ inVector.getData(),
+ alpha,
+ outVector.getData() );
+#endif
+#endif
+ }
+};
+
+template<>
+class CusparseCSRLegacy< float > : public CusparseCSRBaseLegacy< float >
+{
+ public:
+
+ template< typename InVector,
+ typename OutVector >
+ void vectorProduct( const InVector& inVector,
+ OutVector& outVector ) const
+ {
+ TNL_ASSERT_TRUE( matrix, "matrix was not initialized" );
+#ifdef HAVE_CUDA
+#if CUDART_VERSION >= 11000
+ throw std::runtime_error("cusparseScsrmv was removed in CUDA 11.");
+#else
+ float d = 1.0;
+ float* alpha = &d;
+ cusparseScsrmv( *( this->cusparseHandle ),
+ CUSPARSE_OPERATION_NON_TRANSPOSE,
+ this->matrix->getRows(),
+ this->matrix->getColumns(),
+ this->matrix->getValues().getSize(),
+ alpha,
+ this->matrixDescriptor,
+ this->matrix->getValues().getData(),
+ this->matrix->getRowPointers().getData(),
+ this->matrix->getColumnIndexes().getData(),
+ inVector.getData(),
+ alpha,
+ outVector.getData() );
+#endif
+#endif
+ }
+};
+
+} // namespace TNL
diff --git a/src/Benchmarks/SpMV/spmv-legacy.h b/src/Benchmarks/SpMV/spmv-legacy.h
index 690bbed7e810b31f14d2d79441f066f05d412225..7c7e19d8074e9ec6c796e87e8e136af07f9dd44c 100644
--- a/src/Benchmarks/SpMV/spmv-legacy.h
+++ b/src/Benchmarks/SpMV/spmv-legacy.h
@@ -38,6 +38,7 @@
using namespace TNL::Matrices;
#include <Benchmarks/SpMV/ReferenceFormats/cusparseCSRMatrix.h>
+#include <Benchmarks/SpMV/ReferenceFormats/cusparseCSRMatrixLegacy.h>
namespace TNL {
namespace Benchmarks {
@@ -240,9 +241,27 @@ benchmarkSpmvSynthetic( Benchmark& benchmark,
const Config::ParameterContainer& parameters,
bool verboseMR )
{
+ // The following is another workaround because of a bug in nvcc versions 10 and 11.
+ // If we use the current matrix formats, not the legacy ones, we get
+ // ' error: redefinition of â€void TNL::Algorithms::__wrapper__device_stub_CudaReductionKernel...'
+ // It seems that there is a problem with lambda functions identification when we create
+ // two instances of TNL::Matrices::SparseMatrix. The second one comes from calling of
+ // `benchmarkSpMV< Real, SparseMatrix_CSR_Scalar >( benchmark, hostOutVector, inputFileName, verboseMR );`
+ // and simillar later in this function. Maybe splitting this function into two might help.
+#define USE_LEGACY_FORMATS
+#ifdef USE_LEGACY_FORMATS
+ // Here we use 'int' instead of 'Index' because of compatibility with cusparse.
+ using CSRHostMatrix = SpMV::ReferenceFormats::Legacy::CSR< Real, Devices::Host, int >;
+ using CSRCudaMatrix = SpMV::ReferenceFormats::Legacy::CSR< Real, Devices::Cuda, int >;
+ using CusparseMatrix = TNL::CusparseCSRLegacy< Real >;
+#else
// Here we use 'int' instead of 'Index' because of compatibility with cusparse.
using CSRHostMatrix = TNL::Matrices::SparseMatrix< Real, TNL::Devices::Host, int >;
using CSRCudaMatrix = TNL::Matrices::SparseMatrix< Real, TNL::Devices::Cuda, int >;
+ using CusparseMatrix = TNL::CusparseCSR< Real >;
+#endif
+
+
using HostVector = Containers::Vector< Real, Devices::Host, int >;
using CudaVector = Containers::Vector< Real, Devices::Cuda, int >;
@@ -302,7 +321,7 @@ benchmarkSpmvSynthetic( Benchmark& benchmark,
// Delete the CSRhostMatrix, so it doesn't take up unnecessary space
csrHostMatrix.reset();
- TNL::CusparseCSR< Real > cusparseMatrix;
+ CusparseMatrix cusparseMatrix;
cusparseMatrix.init( csrCudaMatrix, &cusparseHandle );
CudaVector cusparseInVector( csrCudaMatrix.getColumns() ), cusparseOutVector( csrCudaMatrix.getRows() );
@@ -323,14 +342,14 @@ benchmarkSpmvSynthetic( Benchmark& benchmark,
/////
// Benchmarking TNL formats
benchmarkSpMVLegacy< Real, SparseMatrix_CSR_Scalar >( benchmark, hostOutVector, inputFileName, verboseMR );
- /*benchmarkSpMV< Real, SparseMatrix_CSR_Vector >( benchmark, hostOutVector, inputFileName, verboseMR );
- benchmarkSpMV< Real, SparseMatrix_CSR_Hybrid >( benchmark, hostOutVector, inputFileName, verboseMR );
- benchmarkSpMV< Real, SparseMatrix_CSR_Adaptive >( benchmark, hostOutVector, inputFileName, verboseMR );
- benchmarkSpMV< Real, SparseMatrix_Ellpack >( benchmark, hostOutVector, inputFileName, verboseMR );
- benchmarkSpMV< Real, SlicedEllpackAlias >( benchmark, hostOutVector, inputFileName, verboseMR );
- benchmarkSpMV< Real, SparseMatrix_SlicedEllpack >( benchmark, hostOutVector, inputFileName, verboseMR );
- benchmarkSpMV< Real, SparseMatrix_ChunkedEllpack >( benchmark, hostOutVector, inputFileName, verboseMR );
- benchmarkSpMV< Real, SparseMatrix_BiEllpack >( benchmark, hostOutVector, inputFileName, verboseMR );*/
+ benchmarkSpMVLegacy< Real, SparseMatrix_CSR_Vector >( benchmark, hostOutVector, inputFileName, verboseMR );
+ benchmarkSpMVLegacy< Real, SparseMatrix_CSR_Hybrid >( benchmark, hostOutVector, inputFileName, verboseMR );
+ benchmarkSpMVLegacy< Real, SparseMatrix_CSR_Adaptive >( benchmark, hostOutVector, inputFileName, verboseMR );
+ benchmarkSpMVLegacy< Real, SparseMatrix_Ellpack >( benchmark, hostOutVector, inputFileName, verboseMR );
+ benchmarkSpMVLegacy< Real, SlicedEllpackAlias >( benchmark, hostOutVector, inputFileName, verboseMR );
+ benchmarkSpMVLegacy< Real, SparseMatrix_SlicedEllpack >( benchmark, hostOutVector, inputFileName, verboseMR );
+ benchmarkSpMVLegacy< Real, SparseMatrix_ChunkedEllpack >( benchmark, hostOutVector, inputFileName, verboseMR );
+ benchmarkSpMVLegacy< Real, SparseMatrix_BiEllpack >( benchmark, hostOutVector, inputFileName, verboseMR );
const bool withSymmetricMatrices = parameters.getParameter< bool >("with-symmetric-matrices");