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585 lines
32 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_CSRILU0_H
#define HIPSPARSE_CSRILU0_H
#ifdef __cplusplus
extern "C" {
#endif
#if(!defined(CUDART_VERSION) || CUDART_VERSION < 13000)
/*! \ingroup precond_module
* \details
* \p hipsparseXcsrilu02_zeroPivot returns \ref HIPSPARSE_STATUS_ZERO_PIVOT if either a
* structural or numerical zero has been found during \ref hipsparseScsrilu02 "hipsparseXcsrilu02()"
* 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 hipsparseXcsrilu02_zeroPivot is a blocking function. It might negatively influence
* performance.
*
* \deprecated
* This function is deprecated when using the CUDA backend (CUDA 12.0+) and will be
* removed in CUDA 13.0. 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_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t
hipsparseXcsrilu02_zeroPivot(hipsparseHandle_t handle, csrilu02Info_t info, int* position);
#endif
#if(!defined(CUDART_VERSION) || CUDART_VERSION < 13000)
/*! \ingroup precond_module
* \details
* \p hipsparseXcsrilu02_numericBoost enables the user to replace a numerical value in
* an incomplete LU factorization. \p tol is used to determine whether a numerical value
* is replaced by \p boost_val, such that \f$A_{j,j} = \text{boost_val}\f$ if
* \f$\text{tol} \ge \left|A_{j,j}\right|\f$.
*
* \note The boost value is enabled by setting \p enable_boost to 1 or disabled by
* setting \p enable_boost to 0.
*
* \note \p tol and \p boost_val can be in host or device memory.
*
* \deprecated
* This function is deprecated when using the CUDA backend (CUDA 12.0+) and will be
* removed in CUDA 13.0. 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[in]
* enable_boost enable/disable numeric boost.
* @param[in]
* tol tolerance to determine whether a numerical value is replaced or not.
* @param[in]
* boost_val boost value to replace a numerical value.
*
* \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, \p tol, or \p boost_val is nullptr.
* \retval HIPSPARSE_STATUS_INTERNAL_ERROR an internal error occurred.
*/
/**@{*/
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseScsrilu02_numericBoost(
hipsparseHandle_t handle, csrilu02Info_t info, int enable_boost, double* tol, float* boost_val);
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseDcsrilu02_numericBoost(hipsparseHandle_t handle,
csrilu02Info_t info,
int enable_boost,
double* tol,
double* boost_val);
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseCcsrilu02_numericBoost(hipsparseHandle_t handle,
csrilu02Info_t info,
int enable_boost,
double* tol,
hipComplex* boost_val);
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseZcsrilu02_numericBoost(hipsparseHandle_t handle,
csrilu02Info_t info,
int enable_boost,
double* tol,
hipDoubleComplex* boost_val);
/**@}*/
#endif
#if(!defined(CUDART_VERSION) || CUDART_VERSION < 13000)
/*! \ingroup precond_module
* \details
* \p hipsparseXcsrilu02_bufferSize returns the size of the temporary storage buffer
* in bytes that is required by \ref hipsparseScsrilu02_analysis "hipsparseXcsrilu02_analysis()"
* and \ref hipsparseScsrilu02 "hipsparseXcsrilu02()". The temporary storage buffer
* must be allocated by the user.
*
* @param[in]
* handle handle to the hipSPARSE library context queue.
* @param[in]
* m number of rows of the sparse CSR matrix.
* @param[in]
* nnz number of non-zero entries of the sparse CSR matrix.
* @param[in]
* descrA descriptor of the sparse CSR matrix.
* @param[in]
* csrSortedValA array of \p nnz elements of the sparse CSR matrix.
* @param[in]
* csrSortedRowPtrA array of \p m+1 elements that point to the start of every row of the
* sparse CSR matrix.
* @param[in]
* csrSortedColIndA array of \p nnz elements containing the column indices of the sparse
* CSR matrix.
* @param[out]
* info structure that holds the information collected during the analysis step.
* @param[out]
* pBufferSizeInBytes number of bytes of the temporary storage buffer required by
* \ref hipsparseScsrilu02_analysis "hipsparseXcsrilu02_analysis()" and
* \ref hipsparseScsrilu02 "hipsparseXcsrilu02()".
*
* \retval HIPSPARSE_STATUS_SUCCESS the operation completed successfully.
* \retval HIPSPARSE_STATUS_INVALID_VALUE \p handle, \p m, \p nnz, \p descrA, \p csrSortedValA,
* \p csrSortedRowPtrA, \p csrSortedColIndA, \p info, or \p pBufferSizeInBytes pointer
* is invalid.
* \retval HIPSPARSE_STATUS_INTERNAL_ERROR an internal error occurred.
*/
/**@{*/
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseScsrilu02_bufferSize(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
float* csrSortedValA,
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
int* pBufferSizeInBytes);
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseDcsrilu02_bufferSize(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
double* csrSortedValA,
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
int* pBufferSizeInBytes);
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseCcsrilu02_bufferSize(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
hipComplex* csrSortedValA,
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
int* pBufferSizeInBytes);
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseZcsrilu02_bufferSize(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
hipDoubleComplex* csrSortedValA,
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
int* pBufferSizeInBytes);
/**@}*/
#endif
/*! \ingroup precond_module
* \details
* \p hipsparseXcsrilu02_bufferSizeExt returns the size of the temporary storage buffer
* in bytes that is required by \ref hipsparseScsrilu02_analysis "hipsparseXcsrilu02_analysis()"
* and \ref hipsparseScsrilu02 "hipsparseXcsrilu02()". The temporary storage buffer
* must be allocated by the user.
*
* @param[in]
* handle handle to the hipSPARSE library context queue.
* @param[in]
* m number of rows of the sparse CSR matrix.
* @param[in]
* nnz number of non-zero entries of the sparse CSR matrix.
* @param[in]
* descrA descriptor of the sparse CSR matrix.
* @param[in]
* csrSortedValA array of \p nnz elements of the sparse CSR matrix.
* @param[in]
* csrSortedRowPtrA array of \p m+1 elements that point to the start of every row of the
* sparse CSR matrix.
* @param[in]
* csrSortedColIndA array of \p nnz elements containing the column indices of the sparse
* CSR matrix.
* @param[out]
* info structure that holds the information collected during the analysis step.
* @param[out]
* pBufferSizeInBytes number of bytes of the temporary storage buffer required by
* \ref hipsparseScsrilu02_analysis "hipsparseXcsrilu02_analysis()" and
* \ref hipsparseScsrilu02 "hipsparseXcsrilu02()".
*
* \retval HIPSPARSE_STATUS_SUCCESS the operation completed successfully.
* \retval HIPSPARSE_STATUS_INVALID_VALUE \p handle, \p m, \p nnz, \p descrA, \p csrSortedValA,
* \p csrSortedRowPtrA, \p csrSortedColIndA, \p info, or \p pBufferSizeInBytes pointer
* is invalid.
* \retval HIPSPARSE_STATUS_INTERNAL_ERROR an internal error occurred.
*/
/**@{*/
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseScsrilu02_bufferSizeExt(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
float* csrSortedValA,
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
size_t* pBufferSizeInBytes);
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseDcsrilu02_bufferSizeExt(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
double* csrSortedValA,
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
size_t* pBufferSizeInBytes);
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseCcsrilu02_bufferSizeExt(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
hipComplex* csrSortedValA,
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
size_t* pBufferSizeInBytes);
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseZcsrilu02_bufferSizeExt(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
hipDoubleComplex* csrSortedValA,
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
size_t* pBufferSizeInBytes);
/**@}*/
#if(!defined(CUDART_VERSION) || CUDART_VERSION < 13000)
/*! \ingroup precond_module
* \details
* \p hipsparseXcsrilu02_analysis performs the analysis step for \ref hipsparseScsrilu02
* "hipsparseXcsrilu02()". 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]
* m number of rows of the sparse CSR matrix.
* @param[in]
* nnz number of non-zero entries of the sparse CSR matrix.
* @param[in]
* descrA descriptor of the sparse CSR matrix.
* @param[in]
* csrSortedValA array of \p nnz elements of the sparse CSR matrix.
* @param[in]
* csrSortedRowPtrA array of \p m+1 elements that point to the start of every row of the
* sparse CSR matrix.
* @param[in]
* csrSortedColIndA array of \p nnz elements containing the column indices of the sparse
* CSR matrix.
* @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 nnz, \p descrA, \p csrSortedValA,
* \p csrSortedRowPtrA, \p csrSortedColIndA, \p info, or \p pBuffer pointer is invalid.
* \retval HIPSPARSE_STATUS_INTERNAL_ERROR an internal error occurred.
*/
/**@{*/
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseScsrilu02_analysis(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
const float* csrSortedValA,
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
hipsparseSolvePolicy_t policy,
void* pBuffer);
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseDcsrilu02_analysis(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
const double* csrSortedValA,
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
hipsparseSolvePolicy_t policy,
void* pBuffer);
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseCcsrilu02_analysis(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
const hipComplex* csrSortedValA,
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
hipsparseSolvePolicy_t policy,
void* pBuffer);
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseZcsrilu02_analysis(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
const hipDoubleComplex* csrSortedValA,
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
hipsparseSolvePolicy_t policy,
void* pBuffer);
/**@}*/
#endif
#if(!defined(CUDART_VERSION) || CUDART_VERSION < 13000)
/*! \ingroup precond_module
* \brief Incomplete LU factorization with 0 fill-ins and no pivoting using the CSR
* storage format.
*
* \details
* \p hipsparseXcsrilu02 computes the incomplete LU factorization with 0 fill-ins and no
* pivoting of a sparse \f$m \times m\f$ CSR matrix \f$A\f$, such that
* \f[
* A \approx LU
* \f]
* where the lower triangular matrix \f$L\f$ and the upper triangular matrix \f$U\f$ are computed using:
* \f[
* \begin{array}{ll}
* L_{ij} = \frac{1}{U_{jj}}(A_{ij} - \sum_{k=0}^{j-1}L_{ik} \times U_{kj}), & \text{if i > j} \\
* U_{ij} = (A_{ij} - \sum_{k=0}^{j-1}L_{ik} \times U_{kj}), & \text{if i <= j}
* \end{array}
* \f]
* for each entry found in the CSR matrix \f$A\f$.
*
* Computing the above incomplete \f$LU\f$ factorization requires three steps to complete. First,
* the user determines the size of the required temporary storage buffer by calling
* \ref hipsparseScsrilu02_bufferSize "hipsparseXcsrilu02_bufferSize()". After this buffer size has been determined,
* the user allocates the buffer and passes it to \ref hipsparseScsrilu02_analysis "hipsparseXcsrilu02_analysis()".
* This will perform analysis on the sparsity pattern of the matrix. Finally, the user calls \p hipsparseScsrilu02,
* \p hipsparseDcsrilu02, \p hipsparseCcsrilu02, or \p hipsparseZcsrilu02 to perform the actual factorization. The calculation
* of the buffer size and the analysis of the sparse matrix only need to be performed once for a given sparsity pattern,
* while the factorization can be repeatedly applied to multiple matrices having the same sparsity pattern. After all calls
* to \ref hipsparseScsrilu02 "hipsparseXcsrilu02()" are complete, the temporary buffer can be deallocated.
*
* When computing the \f$LU\f$ factorization, it is possible that \f$U_{jj} == 0\f$ which would result in a division by zero.
* This could occur from either \f$A_{jj}\f$ not existing in the sparse CSR matrix (referred to as a structural zero) or because
* \f$A_{ij} - \sum_{k=0}^{j-1}L_{ik} \times U_{kj} == 0\f$ (referred to as a numerical zero). For example, running the
* \f$LU\f$ factorization on the following matrix:
* \f[
* \begin{bmatrix}
* 2 & 1 & 0 \\
* 1 & 2 & 1 \\
* 0 & 1 & 2
* \end{bmatrix}
* \f]
* results in a successful \f$LU\f$ factorization. However, running with the matrix:
* \f[
* \begin{bmatrix}
* 2 & 1 & 0 \\
* 1 & 1/2 & 1 \\
* 0 & 1 & 2
* \end{bmatrix}
* \f]
* results in a numerical zero because:
* \f[
* \begin{array}{ll}
* U_{00} &= 2 \\
* U_{01} &= 1 \\
* L_{10} &= \frac{1}{2} \\
* U_{11} &= \frac{1}{2} - \frac{1}{2}
* &= 0
* \end{array}
* \f]
* The user can detect the presence of a structural zero by calling \ref hipsparseXcsrilu02_zeroPivot() after
* \ref hipsparseScsrilu02_analysis "hipsparseXcsrilu02_analysis()" and/or the presence of a structural or
* numerical zero by calling \ref hipsparseXcsrilu02_zeroPivot() after \ref hipsparseScsrilu02 "hipsparseXcsrilu02()".
* In both cases, \ref hipsparseXcsrilu02_zeroPivot() will report the first zero pivot (either numerical or structural)
* found. See the example below. The user can also set the diagonal type to be \f$1\f$ using \ref hipsparseSetMatDiagType(),
* which will interpret the matrix \f$A\f$ as having ones on its diagonal (even if no nonzero exists in the sparsity pattern).
*
* \p hipsparseXcsrilu02 computes the \f$LU\f$ factorization inplace, meaning that the values array \p csrSortedValA_valM of the \f$A\f$
* matrix is overwritten with the \f$L\f$ matrix stored in the strictly lower triangular part of \f$A\f$ and the \f$U\f$ matrix
* stored in the upper part of \f$A\f$:
*
* \f[
* \begin{align}
* \begin{bmatrix}
* a_{00} & a_{01} & a_{02} \\
* a_{10} & a_{11} & a_{12} \\
* a_{20} & a_{21} & a_{22}
* \end{bmatrix}
* \rightarrow
* \begin{bmatrix}
* u_{00} & u_{01} & u_{02} \\
* l_{10} & u_{11} & u_{12} \\
* l_{20} & l_{21} & u_{22}
* \end{bmatrix}
* \end{align}
* \f]
* The row pointer array \p csrSortedRowPtrA and the column indices array \p csrSortedColIndA remain the same for \f$A\f$ and \f$LU\f$ as
* the incomplete factorization does not generate new non-zeros in \f$LU\f$ which do not already exist in \f$A\f$.
*
* The performance of computing \f$LU\f$ factorization with hipSPARSE greatly depends on the sparsity pattern
* of the matrix \f$A\f$, because this is what determines the amount of parallelism available.
*
* \note
* The sparse CSR matrix has to be sorted. This can be achieved by calling
* \ref hipsparseXcsrsort().
*
* \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]
* m number of rows of the sparse CSR matrix.
* @param[in]
* nnz number of non-zero entries of the sparse CSR matrix.
* @param[in]
* descrA descriptor of the sparse CSR matrix.
* @param[inout]
* csrSortedValA_valM array of \p nnz elements of the sparse CSR matrix.
* @param[in]
* csrSortedRowPtrA array of \p m+1 elements that point to the start
* of every row of the sparse CSR matrix.
* @param[in]
* csrSortedColIndA array of \p nnz elements containing the column indices of the sparse
* CSR matrix.
* @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 nnz, \p descrA, \p csrSortedValA_valM,
* \p csrSortedRowPtrA, or \p csrSortedColIndA pointer is invalid.
* \retval HIPSPARSE_STATUS_ARCH_MISMATCH the device is not supported.
* \retval HIPSPARSE_STATUS_INTERNAL_ERROR an internal error occurred.
*/
/**@{*/
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseScsrilu02(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
float* csrSortedValA_valM,
/* matrix A values are updated inplace
to be the preconditioner M values */
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
hipsparseSolvePolicy_t policy,
void* pBuffer);
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseDcsrilu02(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
double* csrSortedValA_valM,
/* matrix A values are updated inplace
to be the preconditioner M values */
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
hipsparseSolvePolicy_t policy,
void* pBuffer);
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseCcsrilu02(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
hipComplex* csrSortedValA_valM,
/* matrix A values are updated inplace
to be the preconditioner M values */
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
hipsparseSolvePolicy_t policy,
void* pBuffer);
DEPRECATED_CUDA_12000("The routine will be removed in CUDA 13")
HIPSPARSE_EXPORT
hipsparseStatus_t hipsparseZcsrilu02(hipsparseHandle_t handle,
int m,
int nnz,
const hipsparseMatDescr_t descrA,
hipDoubleComplex* csrSortedValA_valM,
/* matrix A values are updated inplace
to be the preconditioner M values */
const int* csrSortedRowPtrA,
const int* csrSortedColIndA,
csrilu02Info_t info,
hipsparseSolvePolicy_t policy,
void* pBuffer);
/**@}*/
#endif
#ifdef __cplusplus
}
#endif
#endif /* HIPSPARSE_CSRILU0_H */