/*! \file */ /* ************************************************************************ * Copyright (C) 2025 Advanced Micro Devices, Inc. All rights Reserved. * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * THE SOFTWARE. * * ************************************************************************ */ #ifndef HIPSPARSE_CSRSM_H #define HIPSPARSE_CSRSM_H #ifdef __cplusplus extern "C" { #endif #if(!defined(CUDART_VERSION) || CUDART_VERSION < 12000) /*! \ingroup level3_module * \details * \p hipsparseXcsrsm2_zeroPivot returns \ref HIPSPARSE_STATUS_ZERO_PIVOT if either a * structural or numerical zero has been found during \ref hipsparseScsrsm2_analysis * "hipsparseXcsrsm2_analysis()" or \ref hipsparseScsrsm2_solve "hipsparseXcsrsm2_solve()" * computation. The first zero pivot \f$j\f$ at \f$A_{j,j}\f$ is stored in \p position, * using the same index base as the CSR matrix. * * \p position can be in host or device memory. If no zero pivot has been found, * \p position is set to -1 and \ref HIPSPARSE_STATUS_SUCCESS is returned instead. * * \note \p hipsparseXcsrsm2_zeroPivot is a blocking function. It might negatively * influence performance. * * \deprecated * This function is deprecated when using the CUDA backend (CUDA 11.0+) and will be * removed in CUDA 12.0. This deprecation does not apply to the ROCm backend. * * @param[in] * handle handle to the hipSPARSE library context queue. * @param[in] * info structure that holds the information collected during the analysis step. * @param[inout] * position pointer to zero pivot \f$j\f$, which can be in host or device memory. * * \retval HIPSPARSE_STATUS_SUCCESS the operation completed successfully. * \retval HIPSPARSE_STATUS_NOT_INITIALIZED \p handle is not initialized. * \retval HIPSPARSE_STATUS_INVALID_VALUE \p handle, \p info, or \p position is nullptr. * \retval HIPSPARSE_STATUS_INTERNAL_ERROR an internal error occurred. * \retval HIPSPARSE_STATUS_ZERO_PIVOT zero pivot has been found. */ DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseXcsrsm2_zeroPivot(hipsparseHandle_t handle, csrsm2Info_t info, int* position); #endif #if(!defined(CUDART_VERSION) || CUDART_VERSION < 12000) /*! \ingroup level3_module * \details * \p hipsparseXcsrsm2_bufferSizeExt returns the size of the temporary storage buffer * in bytes that is required by \ref hipsparseScsrsm2_analysis "hipsparseXcsrsm2_analysis()" * and \ref hipsparseScsrsm2_solve "hipsparseXcsrsm2_solve()". The temporary storage buffer * must be allocated by the user. * * @param[in] * handle handle to the hipSPARSE library context queue. * @param[in] * algo algorithm to use. * @param[in] * transA matrix \f$A\f$ operation type. * @param[in] * transB matrix \f$B\f$ operation type. * @param[in] * m number of rows of the sparse CSR matrix \f$A\f$. * @param[in] * nrhs number of columns of the dense matrix \f$op(B)\f$. * @param[in] * nnz number of non-zero entries of the sparse CSR matrix \f$A\f$. * @param[in] * alpha scalar \f$\alpha\f$. * @param[in] * descrA descriptor of the sparse CSR matrix \f$A\f$. * @param[in] * csrSortedValA array of \p nnz elements of the sparse CSR matrix \f$A\f$. * @param[in] * csrSortedRowPtrA array of \p m+1 elements that point to the start of every row of the * sparse CSR matrix \f$A\f$. * @param[in] * csrSortedColIndA array of \p nnz elements containing the column indices of the sparse * CSR matrix \f$A\f$. * @param[in] * B array of \p m \f$\times\f$ \p nrhs elements of the rhs matrix \f$B\f$. * @param[in] * ldb leading dimension of rhs matrix \f$B\f$. * @param[in] * info structure that holds the information collected during the analysis step. * @param[in] * policy \ref HIPSPARSE_SOLVE_POLICY_NO_LEVEL or * \ref HIPSPARSE_SOLVE_POLICY_USE_LEVEL. * @param[out] * pBufferSizeInBytes number of bytes of the temporary storage buffer required by * \ref hipsparseScsrsm2_analysis "hipsparseXcsrsm2_analysis()" and * \ref hipsparseScsrsm2_solve "hipsparseXcsrsm2_solve()". * * \retval HIPSPARSE_STATUS_SUCCESS the operation completed successfully. * \retval HIPSPARSE_STATUS_INVALID_VALUE \p handle, \p m, \p nrhs, \p nnz, \p alpha, * \p descrA, \p csrSortedValA, \p csrSortedRowPtrA, \p csrSortedColIndA, \p B, * \p info, or \p pBufferSizeInBytes is invalid. * \retval HIPSPARSE_STATUS_INTERNAL_ERROR an internal error occurred. * \retval HIPSPARSE_STATUS_NOT_SUPPORTED * \p transA == \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE, * \p transB == \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE, or * \ref hipsparseMatrixType_t != \ref HIPSPARSE_MATRIX_TYPE_GENERAL. */ /**@{*/ DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseScsrsm2_bufferSizeExt(hipsparseHandle_t handle, int algo, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int nrhs, int nnz, const float* alpha, const hipsparseMatDescr_t descrA, const float* csrSortedValA, const int* csrSortedRowPtrA, const int* csrSortedColIndA, const float* B, int ldb, csrsm2Info_t info, hipsparseSolvePolicy_t policy, size_t* pBufferSizeInBytes); DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseDcsrsm2_bufferSizeExt(hipsparseHandle_t handle, int algo, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int nrhs, int nnz, const double* alpha, const hipsparseMatDescr_t descrA, const double* csrSortedValA, const int* csrSortedRowPtrA, const int* csrSortedColIndA, const double* B, int ldb, csrsm2Info_t info, hipsparseSolvePolicy_t policy, size_t* pBufferSizeInBytes); DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseCcsrsm2_bufferSizeExt(hipsparseHandle_t handle, int algo, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int nrhs, int nnz, const hipComplex* alpha, const hipsparseMatDescr_t descrA, const hipComplex* csrSortedValA, const int* csrSortedRowPtrA, const int* csrSortedColIndA, const hipComplex* B, int ldb, csrsm2Info_t info, hipsparseSolvePolicy_t policy, size_t* pBufferSizeInBytes); DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseZcsrsm2_bufferSizeExt(hipsparseHandle_t handle, int algo, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int nrhs, int nnz, const hipDoubleComplex* alpha, const hipsparseMatDescr_t descrA, const hipDoubleComplex* csrSortedValA, const int* csrSortedRowPtrA, const int* csrSortedColIndA, const hipDoubleComplex* B, int ldb, csrsm2Info_t info, hipsparseSolvePolicy_t policy, size_t* pBufferSizeInBytes); /**@}*/ #endif #if(!defined(CUDART_VERSION) || CUDART_VERSION < 12000) /*! \ingroup level3_module * \details * \p hipsparseXcsrsm2_analysis performs the analysis step for \ref hipsparseScsrsm2_solve * "hipsparseXcsrsm2_solve()". It is expected that this function will be executed only once * for a given matrix and particular operation type. * * \note * If the matrix sparsity pattern changes, the gathered information will become invalid. * * \note * This function is non-blocking and executed asynchronously with respect to the host. * It can return before the actual computation has finished. * * @param[in] * handle handle to the hipSPARSE library context queue. * @param[in] * algo algorithm to use. * @param[in] * transA matrix \f$A\f$ operation type. * @param[in] * transB matrix \f$B\f$ operation type. * @param[in] * m number of rows of the sparse CSR matrix \f$A\f$. * @param[in] * nrhs number of columns of the dense matrix \f$op(B)\f$. * @param[in] * nnz number of non-zero entries of the sparse CSR matrix \f$A\f$. * @param[in] * alpha scalar \f$\alpha\f$. * @param[in] * descrA descriptor of the sparse CSR matrix \f$A\f$. * @param[in] * csrSortedValA array of \p nnz elements of the sparse CSR matrix \f$A\f$. * @param[in] * csrSortedRowPtrA array of \p m+1 elements that point to the start of every row of the * sparse CSR matrix \f$A\f$. * @param[in] * csrSortedColIndA array of \p nnz elements containing the column indices of the sparse * CSR matrix \f$A\f$. * @param[in] * B array of \p m \f$\times\f$ \p nrhs elements of the rhs matrix \f$B\f$. * @param[in] * ldb leading dimension of rhs matrix \f$B\f$. * @param[out] * info structure that holds the information collected during the analysis step. * @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 m, \p nrhs, \p nnz, \p alpha, * \p descrA, \p csrSortedValA, \p csrSortedRowPtrA, \p csrSortedColIndA, \p B, * \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 transB == \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE, or * \ref hipsparseMatrixType_t != \ref HIPSPARSE_MATRIX_TYPE_GENERAL. */ /**@{*/ DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseScsrsm2_analysis(hipsparseHandle_t handle, int algo, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int nrhs, int nnz, const float* alpha, const hipsparseMatDescr_t descrA, const float* csrSortedValA, const int* csrSortedRowPtrA, const int* csrSortedColIndA, const float* B, int ldb, csrsm2Info_t info, hipsparseSolvePolicy_t policy, void* pBuffer); DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseDcsrsm2_analysis(hipsparseHandle_t handle, int algo, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int nrhs, int nnz, const double* alpha, const hipsparseMatDescr_t descrA, const double* csrSortedValA, const int* csrSortedRowPtrA, const int* csrSortedColIndA, const double* B, int ldb, csrsm2Info_t info, hipsparseSolvePolicy_t policy, void* pBuffer); DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseCcsrsm2_analysis(hipsparseHandle_t handle, int algo, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int nrhs, int nnz, const hipComplex* alpha, const hipsparseMatDescr_t descrA, const hipComplex* csrSortedValA, const int* csrSortedRowPtrA, const int* csrSortedColIndA, const hipComplex* B, int ldb, csrsm2Info_t info, hipsparseSolvePolicy_t policy, void* pBuffer); DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseZcsrsm2_analysis(hipsparseHandle_t handle, int algo, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int nrhs, int nnz, const hipDoubleComplex* alpha, const hipsparseMatDescr_t descrA, const hipDoubleComplex* csrSortedValA, const int* csrSortedRowPtrA, const int* csrSortedColIndA, const hipDoubleComplex* B, int ldb, csrsm2Info_t info, hipsparseSolvePolicy_t policy, void* pBuffer); /**@}*/ #endif #if(!defined(CUDART_VERSION) || CUDART_VERSION < 12000) /*! \ingroup level3_module * \brief Sparse triangular system solve using the CSR storage format * * \details * \p hipsparseXcsrsm2_solve solves a sparse triangular linear system of a sparse * \f$m \times m\f$ matrix, defined in CSR storage format, a column-oriented dense solution matrix * \f$X\f$, and the column-oriented dense right-hand side matrix \f$B\f$ that is multiplied by \f$\alpha\f$, such that * \f[ * op(A) \cdot op(X) = \alpha \cdot op(B), * \f] * with * \f[ * op(A) = \left\{ * \begin{array}{ll} * A, & \text{if transA == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ * A^T, & \text{if transA == HIPSPARSE_OPERATION_TRANSPOSE} \\ * A^H, & \text{if transA == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} * \end{array} * \right. * \f] * , * \f[ * op(B) = \left\{ * \begin{array}{ll} * B, & \text{if transB == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ * B^T, & \text{if transB == HIPSPARSE_OPERATION_TRANSPOSE} \\ * B^H, & \text{if transB == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} * \end{array} * \right. * \f] * and * \f[ * op(X) = \left\{ * \begin{array}{ll} * X, & \text{if transB == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ * X^T, & \text{if transB == HIPSPARSE_OPERATION_TRANSPOSE} \\ * X^H, & \text{if transB == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} * \end{array} * \right. * \f] * * The solution is performed in-place, meaning that the matrix \f$B\f$ is overwritten with the solution * \f$X\f$ after calling \p hipsparseXcsrsm2_solve. 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$X\f$ depend on the value of \p transB * * \f[ * op(B)/op(X) = \left\{ * \begin{array}{ll} * ldb \times nrhs, \text{ } ldb \ge m, & \text{if transB == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ * ldb \times m, \text{ } ldb \ge nrhs, & \text{if transB == HIPSPARSE_OPERATION_TRANSPOSE} \\ * ldb \times m, \text{ } ldb \ge nrhs, & \text{if transB == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} * \end{array} * \right. * \f] * * \p hipsparseXcsrsm2_solve requires a user-allocated temporary buffer. Its size is returned by * \ref hipsparseScsrsm2_bufferSizeExt "hipsparseXcsrsm2_bufferSizeExt()". 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 transB 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[ * \begin{bmatrix} * a_{00} & 0 & 0 \\ * a_{10} & a_{11} & 0 \\ * a_{20} & a_{21} & a_{22} \\ * \end{bmatrix} * \cdot * \begin{bmatrix} * x_{00} & x_{01} \\ * x_{10} & x_{11} \\ * x_{20} & x_{21} \\ * \end{bmatrix} * = * \begin{bmatrix} * b_{00} & b_{01} \\ * b_{10} & b_{11} \\ * b_{20} & b_{21} \\ * \end{bmatrix} * \f] * * Consider solving: * * \f[ * \begin{bmatrix} * a_{00} & 0 & 0 \\ * a_{10} & a_{11} & 0 \\ * a_{20} & a_{21} & a_{22} * \end{bmatrix} * \cdot * \begin{bmatrix} * x_{00} & x_{10} & x_{20} \\ * x_{01} & x_{11} & x_{21} * \end{bmatrix}^{T} * = * \begin{bmatrix} * b_{00} & b_{10} & b_{20} \\ * b_{01} & b_{11} & b_{21} * \end{bmatrix}^{T} * \f] * * After the temporary storage buffer has been allocated, analysis meta data is required. It can be obtained by * \ref hipsparseScsrsm2_analysis "hipsparseXcsrsm2_analysis()". The triangular solve is completed by calling * \p hipsparseXcsrsm2_solve. After all solves are performed, the temporary storage buffer allocated by the * user can be freed. * * Solving a triangular system involves division by the diagonal elements. This means that if the sparse matrix is * missing the diagonal entry (referred to as a structural zero) or the diagonal entry is zero (referred to as a numerical zero), * then a division by zero would occur. \p hipsparseXcsrsm2_solve tracks the location of the first zero pivot (either numerical * or structural zero). The zero pivot status can be checked by calling \ref hipsparseXcsrsm2_zeroPivot(). If * \ref hipsparseXcsrsm2_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 ones 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 \f$A_{j,j} = 0\f$ for * some \f$j\f$. * * The sparse CSR matrix passed to \p hipsparseXcsrsm2_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 the \ref hipsparseFillMode_t setting 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 CSR matrix has to be sorted. This can be achieved by calling * hipsparseXcsrsort(). * * \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 transB != \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE is supported. * * @param[in] * handle handle to the hipSPARSE library context queue. * @param[in] * algo algorithm to use. * @param[in] * transA matrix \f$A\f$ operation type. * @param[in] * transB matrix \f$B\f$ operation type. * @param[in] * m number of rows of the sparse CSR matrix \f$A\f$. * @param[in] * nrhs number of columns of the dense matrix \f$op(B)\f$. * @param[in] * nnz number of non-zero entries of the sparse CSR matrix \f$A\f$. * @param[in] * alpha scalar \f$\alpha\f$. * @param[in] * descrA descriptor of the sparse CSR matrix \f$A\f$. * @param[in] * csrSortedValA array of \p nnz elements of the sparse CSR matrix \f$A\f$. * @param[in] * csrSortedRowPtrA array of \p m+1 elements that point to the start of every row of the * sparse CSR matrix \f$A\f$. * @param[in] * csrSortedColIndA array of \p nnz elements containing the column indices of the sparse * CSR matrix \f$A\f$. * @param[inout] * B array of \p m \f$\times\f$ \p nrhs elements of the rhs matrix \f$B\f$. * @param[in] * ldb leading dimension of rhs matrix \f$B\f$. * @param[in] * info structure that holds the information collected during the analysis step. * @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 m, \p nrhs, \p nnz, \p alpha, * \p descrA, \p csrSortedValA, \p csrSortedRowPtrA, \p csrSortedColIndA, \p B, * \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 transB == \ref HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE, or * \ref hipsparseMatrixType_t != \ref HIPSPARSE_MATRIX_TYPE_GENERAL. */ /**@{*/ DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseScsrsm2_solve(hipsparseHandle_t handle, int algo, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int nrhs, int nnz, const float* alpha, const hipsparseMatDescr_t descrA, const float* csrSortedValA, const int* csrSortedRowPtrA, const int* csrSortedColIndA, float* B, int ldb, csrsm2Info_t info, hipsparseSolvePolicy_t policy, void* pBuffer); DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseDcsrsm2_solve(hipsparseHandle_t handle, int algo, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int nrhs, int nnz, const double* alpha, const hipsparseMatDescr_t descrA, const double* csrSortedValA, const int* csrSortedRowPtrA, const int* csrSortedColIndA, double* B, int ldb, csrsm2Info_t info, hipsparseSolvePolicy_t policy, void* pBuffer); DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseCcsrsm2_solve(hipsparseHandle_t handle, int algo, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int nrhs, int nnz, const hipComplex* alpha, const hipsparseMatDescr_t descrA, const hipComplex* csrSortedValA, const int* csrSortedRowPtrA, const int* csrSortedColIndA, hipComplex* B, int ldb, csrsm2Info_t info, hipsparseSolvePolicy_t policy, void* pBuffer); DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseZcsrsm2_solve(hipsparseHandle_t handle, int algo, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int nrhs, int nnz, const hipDoubleComplex* alpha, const hipsparseMatDescr_t descrA, const hipDoubleComplex* csrSortedValA, const int* csrSortedRowPtrA, const int* csrSortedColIndA, hipDoubleComplex* B, int ldb, csrsm2Info_t info, hipsparseSolvePolicy_t policy, void* pBuffer); /**@}*/ #endif #ifdef __cplusplus } #endif #endif /* HIPSPARSE_CSRSM_H */