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666 lines
34 KiB
C
666 lines
34 KiB
C
/*! \file */
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/* ************************************************************************
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* Copyright (C) 2025 Advanced Micro Devices, Inc. All rights Reserved.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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* THE SOFTWARE.
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*
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* ************************************************************************ */
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#ifndef HIPSPARSE_BSRSM_H
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#define HIPSPARSE_BSRSM_H
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#ifdef __cplusplus
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extern "C" {
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#endif
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#if(!defined(CUDART_VERSION) || CUDART_VERSION < 13000)
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/*! \ingroup level3_module
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* \details
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* \p hipsparseXbsrsm2_zeroPivot returns \ref HIPSPARSE_STATUS_ZERO_PIVOT if either a
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* structural or numerical zero has been found during \ref hipsparseSbsrsm2_analysis "hipsparseXbsrsm2_analysis()"
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* or \ref hipsparseSbsrsm2_solve "hipsparseXbsrsm2_solve()" computation. The first zero pivot \f$j\f$ at \f$A_{j,j}\f$
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* is stored in \p position, using the same index base as the BSR matrix.
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*
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* \p position can be in host or device memory. If no zero pivot has been found,
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* \p position is set to -1 and \ref HIPSPARSE_STATUS_SUCCESS is returned instead.
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*
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* \note \p hipsparseXbsrsm2_zeroPivot is a blocking function. It might negatively
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* influence performance.
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*
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* \deprecated
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* This function is deprecated when using the CUDA backend (CUDA 12.0+) and will be
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* removed in CUDA 13.0. This deprecation does not apply to the ROCm backend.
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*
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* @param[in]
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* handle handle to the hipSPARSE library context queue.
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* @param[in]
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* info structure that holds the information collected during the analysis step.
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* @param[inout]
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* position pointer to zero pivot \f$j\f$, which can be in host or device memory.
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*
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* \retval HIPSPARSE_STATUS_SUCCESS the operation completed successfully.
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* \retval HIPSPARSE_STATUS_NOT_INITIALIZED \p handle is not initialized.
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* \retval HIPSPARSE_STATUS_INVALID_VALUE \p handle, \p info, or \p position is nullptr.
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* \retval HIPSPARSE_STATUS_INTERNAL_ERROR an internal error occurred.
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* \retval HIPSPARSE_STATUS_ZERO_PIVOT zero pivot has been found.
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*/
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DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
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HIPSPARSE_EXPORT
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hipsparseStatus_t
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hipsparseXbsrsm2_zeroPivot(hipsparseHandle_t handle, bsrsm2Info_t info, int* position);
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#endif
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#if(!defined(CUDART_VERSION) || CUDART_VERSION < 13000)
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/*! \ingroup level3_module
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* \details
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* \p hipsparseXbsrsm2_buffer_size returns the size of the temporary storage buffer in bytes
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* that is required by \ref hipsparseSbsrsm2_analysis "hipsparseXbsrsm2_analysis()" and
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* \ref hipsparseSbsrsm2_solve "hipsparseXbsrsm2_solve()". The temporary storage buffer must
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* be allocated by the user.
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*
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* @param[in]
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* handle handle to the hipSPARSE library context queue.
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* @param[in]
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* dirA matrix storage of BSR blocks.
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* @param[in]
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* transA matrix \f$A\f$ operation type.
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* @param[in]
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* transX matrix \f$X\f$ operation type.
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* @param[in]
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* mb number of block rows of the sparse BSR matrix \f$A\f$.
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* @param[in]
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* nrhs number of columns of the dense matrix \f$op(X)\f$.
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* @param[in]
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* nnzb number of non-zero blocks of the sparse BSR matrix \f$A\f$.
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* @param[in]
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* descrA descriptor of the sparse BSR matrix \f$A\f$.
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* @param[in]
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* bsrSortedValA array of \p nnzb blocks of the sparse BSR matrix.
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* @param[in]
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* bsrSortedRowPtrA array of \p mb+1 elements that point to the start of every block row of
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* the sparse BSR matrix.
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* @param[in]
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* bsrSortedColIndA array of \p nnzb containing the block column indices of the sparse
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* BSR matrix.
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* @param[in]
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* blockDim block dimension of the sparse BSR matrix.
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* @param[in]
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* info structure that holds the information collected during the analysis step.
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* @param[out]
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* pBufferSizeInBytes number of bytes of the temporary storage buffer required by
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* \ref hipsparseSbsrsm2_analysis "hipsparseXbsrsm2_analysis()" and
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* \ref hipsparseSbsrsm2_solve "hipsparseXbsrsm2_solve()".
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*
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* \retval HIPSPARSE_STATUS_SUCCESS the operation completed successfully.
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* \retval HIPSPARSE_STATUS_INVALID_VALUE \p handle, \p mb, \p nrhs, \p nnzb, \p blockDim,
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* \p descrA, \p bsrSortedValA, \p bsrSortedRowPtrA, \p bsrSortedColIndA, \p info, or
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* \p pBufferSizeInBytes is invalid.
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* \retval HIPSPARSE_STATUS_INTERNAL_ERROR an internal error occurred.
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* \retval HIPSPARSE_STATUS_NOT_SUPPORTED
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* \p transA == \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE,
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* \p transX == \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE, or
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* \ref hipsparseMatrixType_t != \ref HIPSPARSE_MATRIX_TYPE_GENERAL.
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*/
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/**@{*/
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DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
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HIPSPARSE_EXPORT
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hipsparseStatus_t hipsparseSbsrsm2_bufferSize(hipsparseHandle_t handle,
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hipsparseDirection_t dirA,
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hipsparseOperation_t transA,
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hipsparseOperation_t transX,
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int mb,
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int nrhs,
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int nnzb,
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const hipsparseMatDescr_t descrA,
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float* bsrSortedValA,
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const int* bsrSortedRowPtrA,
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const int* bsrSortedColIndA,
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int blockDim,
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bsrsm2Info_t info,
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int* pBufferSizeInBytes);
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DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
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HIPSPARSE_EXPORT
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hipsparseStatus_t hipsparseDbsrsm2_bufferSize(hipsparseHandle_t handle,
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hipsparseDirection_t dirA,
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hipsparseOperation_t transA,
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hipsparseOperation_t transX,
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int mb,
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int nrhs,
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int nnzb,
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const hipsparseMatDescr_t descrA,
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double* bsrSortedValA,
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const int* bsrSortedRowPtrA,
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const int* bsrSortedColIndA,
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int blockDim,
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bsrsm2Info_t info,
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int* pBufferSizeInBytes);
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DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
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HIPSPARSE_EXPORT
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hipsparseStatus_t hipsparseCbsrsm2_bufferSize(hipsparseHandle_t handle,
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hipsparseDirection_t dirA,
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hipsparseOperation_t transA,
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hipsparseOperation_t transX,
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int mb,
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int nrhs,
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int nnzb,
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const hipsparseMatDescr_t descrA,
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hipComplex* bsrSortedValA,
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const int* bsrSortedRowPtrA,
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const int* bsrSortedColIndA,
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int blockDim,
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bsrsm2Info_t info,
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int* pBufferSizeInBytes);
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DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
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HIPSPARSE_EXPORT
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hipsparseStatus_t hipsparseZbsrsm2_bufferSize(hipsparseHandle_t handle,
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hipsparseDirection_t dirA,
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hipsparseOperation_t transA,
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hipsparseOperation_t transX,
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int mb,
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int nrhs,
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int nnzb,
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const hipsparseMatDescr_t descrA,
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hipDoubleComplex* bsrSortedValA,
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const int* bsrSortedRowPtrA,
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const int* bsrSortedColIndA,
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int blockDim,
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bsrsm2Info_t info,
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int* pBufferSizeInBytes);
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/**@}*/
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#endif
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#if(!defined(CUDART_VERSION) || CUDART_VERSION < 13000)
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/*! \ingroup level3_module
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* \brief Sparse triangular system solve using the BSR storage format.
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*
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* \details
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* \p hipsparseXbsrsm2_analysis performs the analysis step for \ref hipsparseSbsrsm2_solve
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* "hipsparseXbsrsm2_solve()". It is expected that this function will be executed only once
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* for a given matrix and particular operation type.
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*
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* \note
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* If the matrix sparsity pattern changes, the gathered information will become invalid.
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*
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* \note
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* This function is non-blocking and executed asynchronously with respect to the host.
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* It can return before the actual computation has finished.
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*
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* @param[in]
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* handle handle to the hipSPARSE library context queue.
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* @param[in]
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* dirA matrix storage of BSR blocks.
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* @param[in]
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* transA matrix \f$A\f$ operation type.
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* @param[in]
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* transX matrix \f$X\f$ operation type.
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* @param[in]
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* mb number of block rows of the sparse BSR matrix \f$A\f$.
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* @param[in]
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* nrhs number of columns of the dense matrix \f$op(X)\f$.
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* @param[in]
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* nnzb number of non-zero blocks of the sparse BSR matrix \f$A\f$.
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* @param[in]
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* descrA descriptor of the sparse BSR matrix \f$A\f$.
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* @param[in]
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* bsrSortedValA array of \p nnzb blocks of the sparse BSR matrix \f$A\f$.
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* @param[in]
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* bsrSortedRowPtrA array of \p mb+1 elements that point to the start of every block row of
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* the sparse BSR matrix \f$A\f$.
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* @param[in]
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* bsrSortedColIndA array of \p nnzb containing the block column indices of the sparse
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* BSR matrix \f$A\f$.
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* @param[in]
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* blockDim block dimension of the sparse BSR matrix \f$A\f$.
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* @param[out]
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* info structure that holds the information collected during the analysis step.
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* @param[in]
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* policy \ref HIPSPARSE_SOLVE_POLICY_NO_LEVEL or
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* \ref HIPSPARSE_SOLVE_POLICY_USE_LEVEL.
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* @param[in]
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* pBuffer temporary storage buffer allocated by the user.
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*
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* \retval HIPSPARSE_STATUS_SUCCESS the operation completed successfully.
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* \retval HIPSPARSE_STATUS_INVALID_VALUE \p handle, \p mb, \p nrhs, \p nnzb,
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* \p blockDim, \p descrA, \p bsrSortedValA, \p bsrSortedRowPtrA,
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* \p bsrSortedColIndA, \p info, or \p pBuffer is invalid.
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* \retval HIPSPARSE_STATUS_INTERNAL_ERROR an internal error occurred.
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* \retval HIPSPARSE_STATUS_NOT_SUPPORTED
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* \p transA == \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE,
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* \p transX == \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE, or
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* \ref hipsparseMatrixType_t != \ref HIPSPARSE_MATRIX_TYPE_GENERAL.
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*/
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/**@{*/
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DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
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HIPSPARSE_EXPORT
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hipsparseStatus_t hipsparseSbsrsm2_analysis(hipsparseHandle_t handle,
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hipsparseDirection_t dirA,
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hipsparseOperation_t transA,
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hipsparseOperation_t transX,
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int mb,
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int nrhs,
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int nnzb,
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const hipsparseMatDescr_t descrA,
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const float* bsrSortedValA,
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const int* bsrSortedRowPtrA,
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const int* bsrSortedColIndA,
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int blockDim,
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bsrsm2Info_t info,
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hipsparseSolvePolicy_t policy,
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void* pBuffer);
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DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
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HIPSPARSE_EXPORT
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hipsparseStatus_t hipsparseDbsrsm2_analysis(hipsparseHandle_t handle,
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hipsparseDirection_t dirA,
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hipsparseOperation_t transA,
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hipsparseOperation_t transX,
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int mb,
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int nrhs,
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int nnzb,
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const hipsparseMatDescr_t descrA,
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const double* bsrSortedValA,
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const int* bsrSortedRowPtrA,
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const int* bsrSortedColIndA,
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int blockDim,
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bsrsm2Info_t info,
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hipsparseSolvePolicy_t policy,
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void* pBuffer);
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DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
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HIPSPARSE_EXPORT
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hipsparseStatus_t hipsparseCbsrsm2_analysis(hipsparseHandle_t handle,
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hipsparseDirection_t dirA,
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hipsparseOperation_t transA,
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hipsparseOperation_t transX,
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int mb,
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int nrhs,
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int nnzb,
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const hipsparseMatDescr_t descrA,
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const hipComplex* bsrSortedValA,
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const int* bsrSortedRowPtrA,
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const int* bsrSortedColIndA,
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int blockDim,
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bsrsm2Info_t info,
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hipsparseSolvePolicy_t policy,
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void* pBuffer);
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DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
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HIPSPARSE_EXPORT
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hipsparseStatus_t hipsparseZbsrsm2_analysis(hipsparseHandle_t handle,
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hipsparseDirection_t dirA,
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hipsparseOperation_t transA,
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hipsparseOperation_t transX,
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int mb,
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int nrhs,
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int nnzb,
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const hipsparseMatDescr_t descrA,
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const hipDoubleComplex* bsrSortedValA,
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const int* bsrSortedRowPtrA,
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const int* bsrSortedColIndA,
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int blockDim,
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bsrsm2Info_t info,
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hipsparseSolvePolicy_t policy,
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void* pBuffer);
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/**@}*/
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#endif
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#if(!defined(CUDART_VERSION) || CUDART_VERSION < 13000)
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/*! \ingroup level3_module
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* \brief Sparse triangular system solve using the BSR storage format.
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*
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* \details
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* \p hipsparseXbsrsm2_solve solves a sparse triangular linear system of a sparse
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* \f$m \times m\f$ matrix, defined in BSR storage format, a column-oriented dense solution matrix
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* \f$X\f$ and the column-oriented dense right-hand side matrix \f$B\f$ that is multiplied by \f$\alpha\f$,
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* such that
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* \f[
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* op(A) \cdot op(X) = \alpha \cdot op(B),
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* \f]
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* with
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* \f[
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* op(A) = \left\{
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* \begin{array}{ll}
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* A, & \text{if transA == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\
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* A^T, & \text{if transA == HIPSPARSE_OPERATION_TRANSPOSE} \\
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* A^H, & \text{if transA == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE}
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* \end{array}
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* \right.
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* \f]
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* ,
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* \f[
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* op(B) = \left\{
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* \begin{array}{ll}
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* B, & \text{if transX == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\
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* B^T, & \text{if transX == HIPSPARSE_OPERATION_TRANSPOSE} \\
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* B^H, & \text{if transX == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE}
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* \end{array}
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* \right.
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* \f]
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* and
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* \f[
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* op(X) = \left\{
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* \begin{array}{ll}
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* X, & \text{if transX == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\
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* X^T, & \text{if transX == HIPSPARSE_OPERATION_TRANSPOSE} \\
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* X^H, & \text{if transX == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE}
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* \end{array}
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* \right.
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* \f]
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* and where \f$m = blockDim \times mb\f$.
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*
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* Note that, as indicated above, the operation type of both \f$op(B)\f$ and \f$op(X)\f$ is specified by the
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* \p transX parameter and that the operation type of \f$B\f$ and \f$X\f$ must match. For example, if \f$op(B)=B\f$, then
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* \f$op(X)=X\f$. Likewise, if \f$op(B)=B^T\f$, then \f$op(X)=X^T\f$.
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*
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* Given that the sparse matrix \f$A\f$ is a square matrix, its size is \f$m \times m\f$ regardless of
|
|
* whether \f$A\f$ is transposed or not. The size of the column-oriented dense matrices \f$B\f$ and \f$X\f$
|
|
* depends on the value of \p transX:
|
|
*
|
|
* \f[
|
|
* op(B) = \left\{
|
|
* \begin{array}{ll}
|
|
* ldb \times nrhs, \text{ } ldb \ge m, & \text{if transX == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\
|
|
* ldb \times m, \text{ } ldb \ge nrhs, & \text{if transX == HIPSPARSE_OPERATION_TRANSPOSE} \\
|
|
* ldb \times m, \text{ } ldb \ge nrhs, & \text{if transX == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE}
|
|
* \end{array}
|
|
* \right.
|
|
* \f]
|
|
* and
|
|
* \f[
|
|
* op(X) = \left\{
|
|
* \begin{array}{ll}
|
|
* ldb \times nrhs, \text{ } ldb \ge m, & \text{if transX == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\
|
|
* ldb \times m, \text{ } ldb \ge nrhs, & \text{if transX == HIPSPARSE_OPERATION_TRANSPOSE} \\
|
|
* ldb \times m, \text{ } ldb \ge nrhs, & \text{if transX == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE}
|
|
* \end{array}
|
|
* \right.
|
|
* \f]
|
|
*
|
|
* \p hipsparseXbsrsm2_solve requires a user-allocated temporary buffer. Its size is returned by
|
|
* \ref hipsparseSbsrsm2_bufferSize "hipsparseXbsrsm2_bufferSize()". The size of the required buffer is larger
|
|
* when \p transA equals \ref HIPSPARSE_OPERATION_TRANSPOSE or \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE and
|
|
* when \p transX is \ref HIPSPARSE_OPERATION_NON_TRANSPOSE. The subsequent solve will also be faster when \f$A\f$ is
|
|
* non-transposed and \f$B\f$ is transposed (or conjugate transposed). For example, instead of solving:
|
|
*
|
|
* \f[
|
|
* \left[
|
|
* \begin{array}{c | c}
|
|
* \begin{array}{c c}
|
|
* a_{00} & a_{01} \\
|
|
* a_{10} & a_{11}
|
|
* \end{array} &
|
|
* \begin{array}{c c}
|
|
* 0 & 0 \\
|
|
* 0 & 0
|
|
* \end{array} \\
|
|
* \hline
|
|
* \begin{array}{c c}
|
|
* a_{20} & a_{21} \\
|
|
* a_{30} & a_{31}
|
|
* \end{array} &
|
|
* \begin{array}{c c}
|
|
* a_{22} & a_{23} \\
|
|
* a_{32} & a_{33}
|
|
* \end{array} \\
|
|
* \end{array}
|
|
* \right]
|
|
* \cdot
|
|
* \begin{bmatrix}
|
|
* x_{00} & x_{01} \\
|
|
* x_{10} & x_{11} \\
|
|
* x_{20} & x_{21} \\
|
|
* x_{30} & x_{31} \\
|
|
* \end{bmatrix}
|
|
* =
|
|
* \begin{bmatrix}
|
|
* b_{00} & b_{01} \\
|
|
* b_{10} & b_{11} \\
|
|
* b_{20} & b_{21} \\
|
|
* b_{30} & b_{31} \\
|
|
* \end{bmatrix}
|
|
* \f]
|
|
*
|
|
* Consider solving:
|
|
*
|
|
* \f[
|
|
* \left[
|
|
* \begin{array}{c | c}
|
|
* \begin{array}{c c}
|
|
* a_{00} & a_{01} \\
|
|
* a_{10} & a_{11}
|
|
* \end{array} &
|
|
* \begin{array}{c c}
|
|
* 0 & 0 \\
|
|
* 0 & 0
|
|
* \end{array} \\
|
|
* \hline
|
|
* \begin{array}{c c}
|
|
* a_{20} & a_{21} \\
|
|
* a_{30} & a_{31}
|
|
* \end{array} &
|
|
* \begin{array}{c c}
|
|
* a_{22} & a_{23} \\
|
|
* a_{32} & a_{33}
|
|
* \end{array} \\
|
|
* \end{array}
|
|
* \right]
|
|
* \cdot
|
|
* \begin{bmatrix}
|
|
* x_{00} & x_{10} & x_{20} & x_{30} \\
|
|
* x_{01} & x_{11} & x_{21} & x_{31}
|
|
* \end{bmatrix}^{T}
|
|
* =
|
|
* \begin{bmatrix}
|
|
* b_{00} & b_{10} & b_{20} & b_{30} \\
|
|
* b_{01} & b_{11} & b_{21} & b_{31}
|
|
* \end{bmatrix}^{T}
|
|
* \f]
|
|
*
|
|
* After the temporary storage buffer has been allocated, analysis meta data is required. It can be obtained
|
|
* by hipsparseSbsrsm2_analysis "hipsparseXbsrsm2_analysis()". The triangular solve is completed by calling
|
|
* \p hipsparseXbsrsm2_solve, and after all solves are performed, the temporary storage buffer allocated by the
|
|
* user can be freed.
|
|
*
|
|
* Solving a triangular system involves inverting the diagonal blocks. This means that if the sparse matrix is
|
|
* missing the diagonal block (referred to as a structural zero) or the diagonal block is not invertible (referred
|
|
* to as a numerical zero), then a solution is not possible. \p hipsparseXbsrsm2_solve tracks the location of the first
|
|
* zero pivot (either numerical or structural zero). The zero pivot status can be checked by calling \ref hipsparseXbsrsm2_zeroPivot().
|
|
* If \ref hipsparseXbsrsm2_zeroPivot() returns \ref HIPSPARSE_STATUS_SUCCESS, then no zero pivot was found and therefore
|
|
* the matrix does not have a structural or numerical zero.
|
|
*
|
|
* The user can specify that the sparse matrix should be interpreted as having identity blocks on the diagonal by setting the diagonal
|
|
* type on the descriptor \p descrA to \ref HIPSPARSE_DIAG_TYPE_UNIT using \ref hipsparseSetMatDiagType. If
|
|
* \ref hipsparseDiagType_t == \ref HIPSPARSE_DIAG_TYPE_UNIT, no zero pivot will be reported, even if the diagonal block \f$A_{j,j}\f$
|
|
* for some \f$j\f$ is not invertible.
|
|
*
|
|
* The sparse CSR matrix passed to \p hipsparseXbsrsm2_solve does not actually have to be a triangular matrix. Instead, the
|
|
* triangular upper or lower part of the sparse matrix is solved based on \ref hipsparseFillMode_t set on the descriptor
|
|
* \p descrA. If the fill mode is set to \ref HIPSPARSE_FILL_MODE_LOWER, then the lower triangular matrix is solved. If the
|
|
* fill mode is set to \ref HIPSPARSE_FILL_MODE_UPPER, then the upper triangular matrix is solved.
|
|
*
|
|
* \note
|
|
* The sparse BSR matrix has to be sorted.
|
|
*
|
|
* \note
|
|
* Operation type of B and X must match if \f$op(B)=B, op(X)=X\f$.
|
|
*
|
|
* \note
|
|
* This function is non-blocking and executed asynchronously with respect to the host.
|
|
* It can return before the actual computation has finished.
|
|
*
|
|
* \note
|
|
* Currently, only \p transA != \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE and
|
|
* \p transX != \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE is supported.
|
|
*
|
|
* @param[in]
|
|
* handle handle to the hipSPARSE library context queue.
|
|
* @param[in]
|
|
* dirA matrix storage of BSR blocks.
|
|
* @param[in]
|
|
* transA matrix \f$A\f$ operation type.
|
|
* @param[in]
|
|
* transX matrix \f$X\f$ operation type.
|
|
* @param[in]
|
|
* mb number of block rows of the sparse BSR matrix \f$A\f$.
|
|
* @param[in]
|
|
* nrhs number of columns of the dense matrix \f$op(X)\f$.
|
|
* @param[in]
|
|
* nnzb number of non-zero blocks of the sparse BSR matrix \f$A\f$.
|
|
* @param[in]
|
|
* alpha scalar \f$\alpha\f$.
|
|
* @param[in]
|
|
* descrA descriptor of the sparse BSR matrix \f$A\f$.
|
|
* @param[in]
|
|
* bsrSortedValA array of \p nnzb blocks of the sparse BSR matrix.
|
|
* @param[in]
|
|
* bsrSortedRowPtrA array of \p mb+1 elements that point to the start of every block row of
|
|
* the sparse BSR matrix.
|
|
* @param[in]
|
|
* bsrSortedColIndA array of \p nnzb containing the block column indices of the sparse
|
|
* BSR matrix.
|
|
* @param[in]
|
|
* blockDim block dimension of the sparse BSR matrix.
|
|
* @param[in]
|
|
* info structure that holds the information collected during the analysis step.
|
|
* @param[in]
|
|
* B rhs matrix B with leading dimension \p ldb.
|
|
* @param[in]
|
|
* ldb leading dimension of rhs matrix \f$B\f$.
|
|
* @param[out]
|
|
* X solution matrix X with leading dimension \p ldx.
|
|
* @param[in]
|
|
* ldx leading dimension of solution matrix \f$X\f$.
|
|
* @param[in]
|
|
* policy \ref HIPSPARSE_SOLVE_POLICY_NO_LEVEL or \ref HIPSPARSE_SOLVE_POLICY_USE_LEVEL.
|
|
* @param[in]
|
|
* pBuffer temporary storage buffer allocated by the user.
|
|
*
|
|
* \retval HIPSPARSE_STATUS_SUCCESS the operation completed successfully.
|
|
* \retval HIPSPARSE_STATUS_INVALID_VALUE \p handle, \p mb, \p nrhs, \p nnzb, \p blockDim,
|
|
* \p alpha, \p descrA, \p bsrSortedValA, \p bsrSortedRowPtrA, \p bsrSortedColIndA,
|
|
* \p B, \p X \p info, or \p pBuffer is invalid.
|
|
* \retval HIPSPARSE_STATUS_INTERNAL_ERROR an internal error occurred.
|
|
* \retval HIPSPARSE_STATUS_NOT_SUPPORTED
|
|
* \p transA == \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE,
|
|
* \p transX == \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE or
|
|
* \ref hipsparseMatrixType_t != \ref HIPSPARSE_MATRIX_TYPE_GENERAL.
|
|
*/
|
|
/**@{*/
|
|
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
|
|
HIPSPARSE_EXPORT
|
|
hipsparseStatus_t hipsparseSbsrsm2_solve(hipsparseHandle_t handle,
|
|
hipsparseDirection_t dirA,
|
|
hipsparseOperation_t transA,
|
|
hipsparseOperation_t transX,
|
|
int mb,
|
|
int nrhs,
|
|
int nnzb,
|
|
const float* alpha,
|
|
const hipsparseMatDescr_t descrA,
|
|
const float* bsrSortedValA,
|
|
const int* bsrSortedRowPtrA,
|
|
const int* bsrSortedColIndA,
|
|
int blockDim,
|
|
bsrsm2Info_t info,
|
|
const float* B,
|
|
int ldb,
|
|
float* X,
|
|
int ldx,
|
|
hipsparseSolvePolicy_t policy,
|
|
void* pBuffer);
|
|
|
|
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
|
|
HIPSPARSE_EXPORT
|
|
hipsparseStatus_t hipsparseDbsrsm2_solve(hipsparseHandle_t handle,
|
|
hipsparseDirection_t dirA,
|
|
hipsparseOperation_t transA,
|
|
hipsparseOperation_t transX,
|
|
int mb,
|
|
int nrhs,
|
|
int nnzb,
|
|
const double* alpha,
|
|
const hipsparseMatDescr_t descrA,
|
|
const double* bsrSortedValA,
|
|
const int* bsrSortedRowPtrA,
|
|
const int* bsrSortedColIndA,
|
|
int blockDim,
|
|
bsrsm2Info_t info,
|
|
const double* B,
|
|
int ldb,
|
|
double* X,
|
|
int ldx,
|
|
hipsparseSolvePolicy_t policy,
|
|
void* pBuffer);
|
|
|
|
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
|
|
HIPSPARSE_EXPORT
|
|
hipsparseStatus_t hipsparseCbsrsm2_solve(hipsparseHandle_t handle,
|
|
hipsparseDirection_t dirA,
|
|
hipsparseOperation_t transA,
|
|
hipsparseOperation_t transX,
|
|
int mb,
|
|
int nrhs,
|
|
int nnzb,
|
|
const hipComplex* alpha,
|
|
const hipsparseMatDescr_t descrA,
|
|
const hipComplex* bsrSortedValA,
|
|
const int* bsrSortedRowPtrA,
|
|
const int* bsrSortedColIndA,
|
|
int blockDim,
|
|
bsrsm2Info_t info,
|
|
const hipComplex* B,
|
|
int ldb,
|
|
hipComplex* X,
|
|
int ldx,
|
|
hipsparseSolvePolicy_t policy,
|
|
void* pBuffer);
|
|
|
|
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
|
|
HIPSPARSE_EXPORT
|
|
hipsparseStatus_t hipsparseZbsrsm2_solve(hipsparseHandle_t handle,
|
|
hipsparseDirection_t dirA,
|
|
hipsparseOperation_t transA,
|
|
hipsparseOperation_t transX,
|
|
int mb,
|
|
int nrhs,
|
|
int nnzb,
|
|
const hipDoubleComplex* alpha,
|
|
const hipsparseMatDescr_t descrA,
|
|
const hipDoubleComplex* bsrSortedValA,
|
|
const int* bsrSortedRowPtrA,
|
|
const int* bsrSortedColIndA,
|
|
int blockDim,
|
|
bsrsm2Info_t info,
|
|
const hipDoubleComplex* B,
|
|
int ldb,
|
|
hipDoubleComplex* X,
|
|
int ldx,
|
|
hipsparseSolvePolicy_t policy,
|
|
void* pBuffer);
|
|
/**@}*/
|
|
#endif
|
|
|
|
#ifdef __cplusplus
|
|
}
|
|
#endif
|
|
|
|
#endif /* HIPSPARSE_BSRSM_H */
|