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619 lines
33 KiB
C

/*! \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 */