User Manual

Contents

User Manual#

Introduction#

hipSPARSE is a library that contains basic linear algebra subroutines for sparse matrices and vectors written in HIP for GPU devices. It is designed to be used from C and C++ code. The functionality of hipSPARSE is organized in the following categories:

The code is open and hosted here: ROCmSoftwarePlatform/hipSPARSE

hipSPARSE is a SPARSE marshalling library, with multiple supported backends. It sits between the application and a worker SPARSE library, marshalling inputs into the backend library and marshalling results back to the application. hipSPARSE exports an interface that does not require the client to change, regardless of the chosen backend. Currently, hipSPARSE supports rocSPARSE and cuSPARSE as backends. hipSPARSE focuses on convenience and portability. If performance outweighs these factors, then using rocSPARSE itself is highly recommended. rocSPARSE can also be found on GitHub.

Building and Installing#

Prerequisites#

hipSPARSE requires a ROCm enabled platform, more information here.

Installing pre-built packages#

hipSPARSE can be installed from AMD ROCm repository. For detailed instructions on how to set up ROCm on different platforms, see the AMD ROCm Platform Installation Guide for Linux.

hipSPARSE can be installed on e.g. Ubuntu using

$ sudo apt-get update
$ sudo apt-get install hipsparse

Once installed, hipSPARSE can be used just like any other library with a C API. The header file will need to be included in the user code in order to make calls into hipSPARSE, and the hipSPARSE shared library will become link-time and run-time dependent for the user application.

Building hipSPARSE from source#

Building from source is not necessary, as hipSPARSE can be used after installing the pre-built packages as described above. If desired, the following instructions can be used to build hipSPARSE from source. Furthermore, the following compile-time dependencies must be met

Download hipSPARSE#

The hipSPARSE source code is available at the hipSPARSE GitHub page. Download the master branch using:

$ git clone -b master https://github.com/ROCmSoftwarePlatform/hipSPARSE.git
$ cd hipSPARSE

Below are steps to build different packages of the library, including dependencies and clients. It is recommended to install hipSPARSE using the install.sh script.

Using install.sh to build hipSPARSE with dependencies#

The following table lists common uses of install.sh to build dependencies + library.

Command

Description

./install.sh -h

Print help information.

./install.sh -d

Build dependencies and library in your local directory. The -d flag only needs to be used once. For subsequent invocations of install.sh it is not necessary to rebuild the dependencies.

./install.sh

Build library in your local directory. It is assumed dependencies are available.

./install.sh -i

Build library, then build and install hipSPARSE package in /opt/rocm/hipsparse. You will be prompted for sudo access. This will install for all users.

Using install.sh to build hipSPARSE with dependencies and clients#

The client contains example code and unit tests. Common uses of install.sh to build them are listed in the table below.

Command

Description

./install.sh -h

Print help information.

./install.sh -dc

Build dependencies, library and client in your local directory. The -d flag only needs to be used once. For subsequent invocations of install.sh it is not necessary to rebuild the dependencies.

./install.sh -c

Build library and client in your local directory. It is assumed dependencies are available.

./install.sh -idc

Build library, dependencies and client, then build and install hipSPARSE package in /opt/rocm/hipsparse. You will be prompted for sudo access. This will install for all users.

./install.sh -ic

Build library and client, then build and install hipSPARSE package in opt/rocm/hipsparse. You will be prompted for sudo access. This will install for all users.

Using individual commands to build hipSPARSE#

CMake 3.5 or later is required in order to build hipSPARSE.

hipSPARSE can be built using the following commands:

# Create and change to build directory
$ mkdir -p build/release ; cd build/release

# Default install path is /opt/rocm, use -DCMAKE_INSTALL_PREFIX=<path> to adjust it
$ cmake ../..

# Compile hipSPARSE library
$ make -j$(nproc)

# Install hipSPARSE to /opt/rocm
$ make install

GoogleTest is required in order to build hipSPARSE clients.

hipSPARSE with dependencies and clients can be built using the following commands:

# Install googletest
$ mkdir -p build/release/deps ; cd build/release/deps
$ cmake ../../../deps
$ make -j$(nproc) install

# Change to build directory
$ cd ..

# Default install path is /opt/rocm, use -DCMAKE_INSTALL_PREFIX=<path> to adjust it
$ cmake ../.. -DBUILD_CLIENTS_TESTS=ON -DBUILD_CLIENTS_SAMPLES=ON

# Compile hipSPARSE library
$ make -j$(nproc)

# Install hipSPARSE to /opt/rocm
$ make install

Simple Test#

You can test the installation by running one of the hipSPARSE examples, after successfully compiling the library with clients.

# Navigate to clients binary directory
$ cd hipSPARSE/build/release/clients/staging

# Execute hipSPARSE example
$ ./example_csrmv 1000

Supported Targets#

Currently, hipSPARSE is supported under the following operating systems

To compile and run hipSPARSE, AMD ROCm Platform is required.

Device and Stream Management#

hipSetDevice() and hipGetDevice() are HIP device management APIs. They are NOT part of the hipSPARSE API.

Asynchronous Execution#

All hipSPARSE library functions, unless otherwise stated, are non blocking and executed asynchronously with respect to the host. They may return before the actual computation has finished. To force synchronization, hipDeviceSynchronize() or hipStreamSynchronize() can be used. This will ensure that all previously executed hipSPARSE functions on the device / this particular stream have completed.

HIP Device Management#

Before a HIP kernel invocation, users need to call hipSetDevice() to set a device, e.g. device 1. If users do not explicitly call it, the system by default sets it as device 0. Unless users explicitly call hipSetDevice() to set to another device, their HIP kernels are always launched on device 0.

The above is a HIP (and CUDA) device management approach and has nothing to do with hipSPARSE. hipSPARSE honors the approach above and assumes users have already set the device before a hipSPARSE routine call.

Once users set the device, they create a handle with hipsparseCreate().

Subsequent hipSPARSE routines take this handle as an input parameter. hipSPARSE ONLY queries (by hipGetDevice()) the user’s device; hipSPARSE does NOT set the device for users. If hipSPARSE does not see a valid device, it returns an error message. It is the users’ responsibility to provide a valid device to hipSPARSE and ensure the device safety.

Users CANNOT switch devices between hipsparseCreate() and hipsparseDestroy(). If users want to change device, they must destroy the current handle and create another hipSPARSE handle.

HIP Stream Management#

HIP kernels are always launched in a queue (also known as stream).

If users do not explicitly specify a stream, the system provides a default stream, maintained by the system. Users cannot create or destroy the default stream. However, users can freely create new streams (with hipStreamCreate()) and bind it to the hipSPARSE handle using hipsparseGetVersion(). HIP kernels are invoked in hipSPARSE routines. The hipSPARSE handle is always associated with a stream, and hipSPARSE passes its stream to the kernels inside the routine. One hipSPARSE routine only takes one stream in a single invocation. If users create a stream, they are responsible for destroying it.

Multiple Streams and Multiple Devices#

If the system under test has multiple HIP devices, users can run multiple hipSPARSE handles concurrently, but can NOT run a single hipSPARSE handle on different discrete devices. Each handle is associated with a particular singular device, and a new handle should be created for each additional device.

Storage Formats#

COO storage format#

The Coordinate (COO) storage format represents a \(m \times n\) matrix by

m

number of rows (integer).

n

number of columns (integer).

nnz

number of non-zero elements (integer).

coo_val

array of nnz elements containing the data (floating point).

coo_row_ind

array of nnz elements containing the row indices (integer).

coo_col_ind

array of nnz elements containing the column indices (integer).

The COO matrix is expected to be sorted by row indices and column indices per row. Furthermore, each pair of indices should appear only once. Consider the following \(3 \times 5\) matrix and the corresponding COO structures, with \(m = 3, n = 5\) and \(\text{nnz} = 8\) using zero based indexing:

\[\begin{split}A = \begin{pmatrix} 1.0 & 2.0 & 0.0 & 3.0 & 0.0 \\ 0.0 & 4.0 & 5.0 & 0.0 & 0.0 \\ 6.0 & 0.0 & 0.0 & 7.0 & 8.0 \\ \end{pmatrix}\end{split}\]

where

\[\begin{split}\begin{array}{ll} \text{coo_val}[8] & = \{1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0\} \\ \text{coo_row_ind}[8] & = \{0, 0, 0, 1, 1, 2, 2, 2\} \\ \text{coo_col_ind}[8] & = \{0, 1, 3, 1, 2, 0, 3, 4\} \end{array}\end{split}\]

COO (AoS) storage format#

The Coordinate (COO) Array of Structure (AoS) storage format represents a \(m \times n\) matrix by

m

number of rows (integer).

n

number of columns (integer).

nnz

number of non-zero elements (integer).

coo_val

array of nnz elements containing the data (floating point).

coo_ind

array of 2 * nnz elements containing alternating row and column indices (integer).

The COO (AoS) matrix is expected to be sorted by row indices and column indices per row. Furthermore, each pair of indices should appear only once. Consider the following \(3 \times 5\) matrix and the corresponding COO (AoS) structures, with \(m = 3, n = 5\) and \(\text{nnz} = 8\) using zero based indexing:

\[\begin{split}A = \begin{pmatrix} 1.0 & 2.0 & 0.0 & 3.0 & 0.0 \\ 0.0 & 4.0 & 5.0 & 0.0 & 0.0 \\ 6.0 & 0.0 & 0.0 & 7.0 & 8.0 \\ \end{pmatrix}\end{split}\]

where

\[\begin{split}\begin{array}{ll} \text{coo_val}[8] & = \{1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0\} \\ \text{coo_ind}[16] & = \{0, 0, 0, 1, 0, 3, 1, 1, 1, 2, 2, 0, 2, 3, 2, 4\} \\ \end{array}\end{split}\]

CSR storage format#

The Compressed Sparse Row (CSR) storage format represents a \(m \times n\) matrix by

m

number of rows (integer).

n

number of columns (integer).

nnz

number of non-zero elements (integer).

csr_val

array of nnz elements containing the data (floating point).

csr_row_ptr

array of m+1 elements that point to the start of every row (integer).

csr_col_ind

array of nnz elements containing the column indices (integer).

The CSR matrix is expected to be sorted by column indices within each row. Furthermore, each pair of indices should appear only once. Consider the following \(3 \times 5\) matrix and the corresponding CSR structures, with \(m = 3, n = 5\) and \(\text{nnz} = 8\) using one based indexing:

\[\begin{split}A = \begin{pmatrix} 1.0 & 2.0 & 0.0 & 3.0 & 0.0 \\ 0.0 & 4.0 & 5.0 & 0.0 & 0.0 \\ 6.0 & 0.0 & 0.0 & 7.0 & 8.0 \\ \end{pmatrix}\end{split}\]

where

\[\begin{split}\begin{array}{ll} \text{csr_val}[8] & = \{1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0\} \\ \text{csr_row_ptr}[4] & = \{1, 4, 6, 9\} \\ \text{csr_col_ind}[8] & = \{1, 2, 4, 2, 3, 1, 4, 5\} \end{array}\end{split}\]

BSR storage format#

The Block Compressed Sparse Row (BSR) storage format represents a \((mb \cdot \text{bsr_dim}) \times (nb \cdot \text{bsr_dim})\) matrix by

mb

number of block rows (integer)

nb

number of block columns (integer)

nnzb

number of non-zero blocks (integer)

bsr_val

array of nnzb * bsr_dim * bsr_dim elements containing the data (floating point). Blocks can be stored column-major or row-major.

bsr_row_ptr

array of mb+1 elements that point to the start of every block row (integer).

bsr_col_ind

array of nnzb elements containing the block column indices (integer).

bsr_dim

dimension of each block (integer).

The BSR matrix is expected to be sorted by column indices within each row. If \(m\) or \(n\) are not evenly divisible by the block dimension, then zeros are padded to the matrix, such that \(mb = (m + \text{bsr_dim} - 1) / \text{bsr_dim}\) and \(nb = (n + \text{bsr_dim} - 1) / \text{bsr_dim}\). Consider the following \(4 \times 3\) matrix and the corresponding BSR structures, with \(\text{bsr_dim} = 2, mb = 2, nb = 2\) and \(\text{nnzb} = 4\) using zero based indexing and column-major storage:

\[\begin{split}A = \begin{pmatrix} 1.0 & 0.0 & 2.0 \\ 3.0 & 0.0 & 4.0 \\ 5.0 & 6.0 & 0.0 \\ 7.0 & 0.0 & 8.0 \\ \end{pmatrix}\end{split}\]

with the blocks \(A_{ij}\)

\[\begin{split}A_{00} = \begin{pmatrix} 1.0 & 0.0 \\ 3.0 & 0.0 \\ \end{pmatrix}, A_{01} = \begin{pmatrix} 2.0 & 0.0 \\ 4.0 & 0.0 \\ \end{pmatrix}, A_{10} = \begin{pmatrix} 5.0 & 6.0 \\ 7.0 & 0.0 \\ \end{pmatrix}, A_{11} = \begin{pmatrix} 0.0 & 0.0 \\ 8.0 & 0.0 \\ \end{pmatrix}\end{split}\]

such that

\[\begin{split}A = \begin{pmatrix} A_{00} & A_{01} \\ A_{10} & A_{11} \\ \end{pmatrix}\end{split}\]

with arrays representation

\[\begin{split}\begin{array}{ll} \text{bsr_val}[16] & = \{1.0, 3.0, 0.0, 0.0, 2.0, 4.0, 0.0, 0.0, 5.0, 7.0, 6.0, 0.0, 0.0, 8.0, 0.0, 0.0\} \\ \text{bsr_row_ptr}[3] & = \{0, 2, 4\} \\ \text{bsr_col_ind}[4] & = \{0, 1, 0, 1\} \end{array}\end{split}\]

GEBSR storage format#

The General Block Compressed Sparse Row (GEBSR) storage format represents a \((mb \cdot \text{bsr_row_dim}) \times (nb \cdot \text{bsr_col_dim})\) matrix by

mb

number of block rows (integer)

nb

number of block columns (integer)

nnzb

number of non-zero blocks (integer)

bsr_val

array of nnzb * bsr_row_dim * bsr_col_dim elements containing the data (floating point). Blocks can be stored column-major or row-major.

bsr_row_ptr

array of mb+1 elements that point to the start of every block row (integer).

bsr_col_ind

array of nnzb elements containing the block column indices (integer).

bsr_row_dim

row dimension of each block (integer).

bsr_col_dim

column dimension of each block (integer).

The GEBSR matrix is expected to be sorted by column indices within each row. If \(m\) is not evenly divisible by the row block dimension or \(n\) is not evenly divisible by the column block dimension, then zeros are padded to the matrix, such that \(mb = (m + \text{bsr_row_dim} - 1) / \text{bsr_row_dim}\) and \(nb = (n + \text{bsr_col_dim} - 1) / \text{bsr_col_dim}\). Consider the following \(4 \times 5\) matrix and the corresponding GEBSR structures, with \(\text{bsr_row_dim} = 2\), \(\text{bsr_col_dim} = 3\), mb = 2, nb = 2` and \(\text{nnzb} = 4\) using zero based indexing and column-major storage:

\[\begin{split}A = \begin{pmatrix} 1.0 & 0.0 & 0.0 & 2.0 & 0.0 \\ 3.0 & 0.0 & 4.0 & 0.0 & 0.0 \\ 5.0 & 6.0 & 0.0 & 7.0 & 0.0 \\ 0.0 & 0.0 & 8.0 & 0.0 & 9.0 \\ \end{pmatrix}\end{split}\]

with the blocks \(A_{ij}\)

\[\begin{split}A_{00} = \begin{pmatrix} 1.0 & 0.0 & 0.0 \\ 3.0 & 0.0 & 4.0 \\ \end{pmatrix}, A_{01} = \begin{pmatrix} 2.0 & 0.0 & 0.0 \\ 0.0 & 0.0 & 0.0 \\ \end{pmatrix}, A_{10} = \begin{pmatrix} 5.0 & 6.0 & 0.0 \\ 0.0 & 0.0 & 8.0 \\ \end{pmatrix}, A_{11} = \begin{pmatrix} 7.0 & 0.0 & 0.0 \\ 0.0 & 9.0 & 0.0 \\ \end{pmatrix}\end{split}\]

such that

\[\begin{split}A = \begin{pmatrix} A_{00} & A_{01} \\ A_{10} & A_{11} \\ \end{pmatrix}\end{split}\]

with arrays representation

\[\begin{split}\begin{array}{ll} \text{bsr_val}[24] & = \{1.0, 3.0, 0.0, 0.0, 0.0, 4.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 5.0, 0.0, 6.0, 0.0, 0.0, 8.0, 7.0, 0.0, 0.0, 9.0, 0.0, 0.0\} \\ \text{bsr_row_ptr}[3] & = \{0, 2, 4\} \\ \text{bsr_col_ind}[4] & = \{0, 1, 0, 1\} \end{array}\end{split}\]

ELL storage format#

The Ellpack-Itpack (ELL) storage format represents a \(m \times n\) matrix by

m

number of rows (integer).

n

number of columns (integer).

ell_width

maximum number of non-zero elements per row (integer)

ell_val

array of m times ell_width elements containing the data (floating point).

ell_col_ind

array of m times ell_width elements containing the column indices (integer).

The ELL matrix is assumed to be stored in column-major format. Rows with less than ell_width non-zero elements are padded with zeros (ell_val) and \(-1\) (ell_col_ind). Consider the following \(3 \times 5\) matrix and the corresponding ELL structures, with \(m = 3, n = 5\) and \(\text{ell_width} = 3\) using zero based indexing:

\[\begin{split}A = \begin{pmatrix} 1.0 & 2.0 & 0.0 & 3.0 & 0.0 \\ 0.0 & 4.0 & 5.0 & 0.0 & 0.0 \\ 6.0 & 0.0 & 0.0 & 7.0 & 8.0 \\ \end{pmatrix}\end{split}\]

where

\[\begin{split}\begin{array}{ll} \text{ell_val}[9] & = \{1.0, 4.0, 6.0, 2.0, 5.0, 7.0, 3.0, 0.0, 8.0\} \\ \text{ell_col_ind}[9] & = \{0, 1, 0, 1, 2, 3, 3, -1, 4\} \end{array}\end{split}\]

HYB storage format#

The Hybrid (HYB) storage format represents a \(m \times n\) matrix by

m

number of rows (integer).

n

number of columns (integer).

nnz

number of non-zero elements of the COO part (integer)

ell_width

maximum number of non-zero elements per row of the ELL part (integer)

ell_val

array of m times ell_width elements containing the ELL part data (floating point).

ell_col_ind

array of m times ell_width elements containing the ELL part column indices (integer).

coo_val

array of nnz elements containing the COO part data (floating point).

coo_row_ind

array of nnz elements containing the COO part row indices (integer).

coo_col_ind

array of nnz elements containing the COO part column indices (integer).

The HYB format is a combination of the ELL and COO sparse matrix formats. Typically, the regular part of the matrix is stored in ELL storage format, and the irregular part of the matrix is stored in COO storage format. Three different partitioning schemes can be applied when converting a CSR matrix to a matrix in HYB storage format. For further details on the partitioning schemes, see hipsparseHybPartition_t.

Types#

hipsparseHandle_t#

typedef void *hipsparseHandle_t#

Handle to the hipSPARSE library context queue.

The hipSPARSE handle is a structure holding the hipSPARSE library context. It must be initialized using hipsparseCreate() and the returned handle must be passed to all subsequent library function calls. It should be destroyed at the end using hipsparseDestroy().

hipsparseMatDescr_t#

typedef void *hipsparseMatDescr_t#

Descriptor of the matrix.

The hipSPARSE matrix descriptor is a structure holding all properties of a matrix. It must be initialized using hipsparseCreateMatDescr() and the returned descriptor must be passed to all subsequent library calls that involve the matrix. It should be destroyed at the end using hipsparseDestroyMatDescr().

hipsparseHybMat_t#

typedef void *hipsparseHybMat_t#

HYB matrix storage format.

The hipSPARSE HYB matrix structure holds the HYB matrix. It must be initialized using hipsparseCreateHybMat() and the returned HYB matrix must be passed to all subsequent library calls that involve the matrix. It should be destroyed at the end using hipsparseDestroyHybMat().

For more details on the HYB format, see HYB storage format.

hipsparseColorInfo_t#

typedef void *hipsparseColorInfo_t#

Coloring info.

The hipSPARSE ColorInfo structure holds the coloring information. It must be initialized using hipsparseCreateColorInfo() and the returned structure must be passed to all subsequent library calls that involve the coloring. It should be destroyed at the end using hipsparseDestroyColorInfo().

bsrsv2Info_t#

typedef struct bsrsv2Info *bsrsv2Info_t#

bsrsm2Info_t#

typedef struct bsrsm2Info *bsrsm2Info_t#

bsrilu02Info_t#

typedef struct bsrilu02Info *bsrilu02Info_t#

bsric02Info_t#

typedef struct bsric02Info *bsric02Info_t#

csrsv2Info_t#

typedef struct csrsv2Info *csrsv2Info_t#

csrsm2Info_t#

typedef struct csrsm2Info *csrsm2Info_t#

csrilu02Info_t#

typedef struct csrilu02Info *csrilu02Info_t#

csric02Info_t#

typedef struct csric02Info *csric02Info_t#

csrgemm2Info_t#

typedef struct csrgemm2Info *csrgemm2Info_t#

pruneInfo_t#

typedef struct pruneInfo *pruneInfo_t#

csru2csrInfo_t#

typedef struct csru2csrInfo *csru2csrInfo_t#

hipsparseSpVecDescr_t#

typedef void *hipsparseSpVecDescr_t#

hipsparseSpMatDescr_t#

typedef void *hipsparseSpMatDescr_t#

hipsparseDnVecDescr_t#

typedef void *hipsparseDnVecDescr_t#

hipsparseDnMatDescr_t#

typedef void *hipsparseDnMatDescr_t#

hipsparseSpGEMMDescr_t#

typedef struct hipsparseSpGEMMDescr *hipsparseSpGEMMDescr_t#

hipsparseSpSVDescr_t#

typedef struct hipsparseSpSVDescr *hipsparseSpSVDescr_t#

hipsparseSpSMDescr_t#

typedef struct hipsparseSpSMDescr *hipsparseSpSMDescr_t#

hipsparseStatus_t#

enum hipsparseStatus_t#

List of hipsparse status codes definition.

This is a list of the hipsparseStatus_t types that are used by the hipSPARSE library.

Values:

enumerator HIPSPARSE_STATUS_SUCCESS#
enumerator HIPSPARSE_STATUS_NOT_INITIALIZED#
enumerator HIPSPARSE_STATUS_ALLOC_FAILED#
enumerator HIPSPARSE_STATUS_INVALID_VALUE#
enumerator HIPSPARSE_STATUS_ARCH_MISMATCH#
enumerator HIPSPARSE_STATUS_MAPPING_ERROR#
enumerator HIPSPARSE_STATUS_EXECUTION_FAILED#
enumerator HIPSPARSE_STATUS_INTERNAL_ERROR#
enumerator HIPSPARSE_STATUS_MATRIX_TYPE_NOT_SUPPORTED#
enumerator HIPSPARSE_STATUS_ZERO_PIVOT#
enumerator HIPSPARSE_STATUS_NOT_SUPPORTED#
enumerator HIPSPARSE_STATUS_INSUFFICIENT_RESOURCES#

hipsparsePointerMode_t#

enum hipsparsePointerMode_t#

Indicates if the pointer is device pointer or host pointer.

The hipsparsePointerMode_t indicates whether scalar values are passed by reference on the host or device. The hipsparsePointerMode_t can be changed by hipsparseSetPointerMode(). The currently used pointer mode can be obtained by hipsparseGetPointerMode().

Values:

enumerator HIPSPARSE_POINTER_MODE_HOST#
enumerator HIPSPARSE_POINTER_MODE_DEVICE#

hipsparseAction_t#

enum hipsparseAction_t#

Specify where the operation is performed on.

The hipsparseAction_t indicates whether the operation is performed on the full matrix, or only on the sparsity pattern of the matrix.

Values:

enumerator HIPSPARSE_ACTION_SYMBOLIC#
enumerator HIPSPARSE_ACTION_NUMERIC#

hipsparseMatrixType_t#

enum hipsparseMatrixType_t#

Specify the matrix type.

The hipsparseMatrixType_t indices the type of a matrix. For a given hipsparseMatDescr_t, the hipsparseMatrixType_t can be set using hipsparseSetMatType(). The current hipsparseMatrixType_t of a matrix can be obtained by hipsparseGetMatType().

Values:

enumerator HIPSPARSE_MATRIX_TYPE_GENERAL#
enumerator HIPSPARSE_MATRIX_TYPE_SYMMETRIC#
enumerator HIPSPARSE_MATRIX_TYPE_HERMITIAN#
enumerator HIPSPARSE_MATRIX_TYPE_TRIANGULAR#

hipsparseFillMode_t#

enum hipsparseFillMode_t#

Specify the matrix fill mode.

The hipsparseFillMode_t indicates whether the lower or the upper part is stored in a sparse triangular matrix. For a given hipsparseMatDescr_t, the hipsparseFillMode_t can be set using hipsparseSetMatFillMode(). The current hipsparseFillMode_t of a matrix can be obtained by hipsparseGetMatFillMode().

Values:

enumerator HIPSPARSE_FILL_MODE_LOWER#
enumerator HIPSPARSE_FILL_MODE_UPPER#

hipsparseDiagType_t#

enum hipsparseDiagType_t#

Indicates if the diagonal entries are unity.

The hipsparseDiagType_t indicates whether the diagonal entries of a matrix are unity or not. If HIPSPARSE_DIAG_TYPE_UNIT is specified, all present diagonal values will be ignored. For a given hipsparseMatDescr_t, the hipsparseDiagType_t can be set using hipsparseSetMatDiagType(). The current hipsparseDiagType_t of a matrix can be obtained by hipsparseGetMatDiagType().

Values:

enumerator HIPSPARSE_DIAG_TYPE_NON_UNIT#
enumerator HIPSPARSE_DIAG_TYPE_UNIT#

hipsparseIndexBase_t#

enum hipsparseIndexBase_t#

Specify the matrix index base.

The hipsparseIndexBase_t indicates the index base of the indices. For a given hipsparseMatDescr_t, the hipsparseIndexBase_t can be set using hipsparseSetMatIndexBase(). The current hipsparseIndexBase_t of a matrix can be obtained by hipsparseGetMatIndexBase().

Values:

enumerator HIPSPARSE_INDEX_BASE_ZERO#
enumerator HIPSPARSE_INDEX_BASE_ONE#

hipsparseOperation_t#

enum hipsparseOperation_t#

Specify whether the matrix is to be transposed or not.

The hipsparseOperation_t indicates the operation performed with the given matrix.

Values:

enumerator HIPSPARSE_OPERATION_NON_TRANSPOSE#
enumerator HIPSPARSE_OPERATION_TRANSPOSE#
enumerator HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE#

hipsparseHybPartition_t#

enum hipsparseHybPartition_t#

HYB matrix partitioning type.

The hipsparseHybPartition_t type indicates how the hybrid format partitioning between COO and ELL storage formats is performed.

Values:

enumerator HIPSPARSE_HYB_PARTITION_AUTO#
enumerator HIPSPARSE_HYB_PARTITION_USER#
enumerator HIPSPARSE_HYB_PARTITION_MAX#

hipsparseSolvePolicy_t#

enum hipsparseSolvePolicy_t#

Specify policy in triangular solvers and factorizations.

The hipsparseSolvePolicy_t type indicates the solve policy for the triangular solve.

Values:

enumerator HIPSPARSE_SOLVE_POLICY_NO_LEVEL#
enumerator HIPSPARSE_SOLVE_POLICY_USE_LEVEL#

hipsparseSideMode_t#

enum hipsparseSideMode_t#

Values:

enumerator HIPSPARSE_SIDE_LEFT#
enumerator HIPSPARSE_SIDE_RIGHT#

hipsparseDirection_t#

enum hipsparseDirection_t#

Specify the matrix direction.

The hipsparseDirection_t indicates whether a dense matrix should be parsed by rows or by columns, assuming column-major storage.

Values:

enumerator HIPSPARSE_DIRECTION_ROW#
enumerator HIPSPARSE_DIRECTION_COLUMN#

hipsparseFormat_t#

enum hipsparseFormat_t#

Values:

enumerator HIPSPARSE_FORMAT_CSR#
enumerator HIPSPARSE_FORMAT_CSC#
enumerator HIPSPARSE_FORMAT_COO#
enumerator HIPSPARSE_FORMAT_COO_AOS#
enumerator HIPSPARSE_FORMAT_BLOCKED_ELL#

hipsparseOrder_t#

enum hipsparseOrder_t#

Values:

enumerator HIPSPARSE_ORDER_ROW#
enumerator HIPSPARSE_ORDER_COLUMN#

hipsparseIndextype_t#

enum hipsparseIndexType_t#

Values:

enumerator HIPSPARSE_INDEX_16U#
enumerator HIPSPARSE_INDEX_32I#
enumerator HIPSPARSE_INDEX_64I#

hipsparseSpMVAlg_t#

enum hipsparseSpMVAlg_t#

Values:

enumerator HIPSPARSE_MV_ALG_DEFAULT#
enumerator HIPSPARSE_COOMV_ALG#
enumerator HIPSPARSE_CSRMV_ALG1#
enumerator HIPSPARSE_CSRMV_ALG2#
enumerator HIPSPARSE_SPMV_ALG_DEFAULT#
enumerator HIPSPARSE_SPMV_COO_ALG1#
enumerator HIPSPARSE_SPMV_COO_ALG2#
enumerator HIPSPARSE_SPMV_CSR_ALG1#
enumerator HIPSPARSE_SPMV_CSR_ALG2#

hipsparseSpMMAlg_t#

enum hipsparseSpMMAlg_t#

Values:

enumerator HIPSPARSE_MM_ALG_DEFAULT#
enumerator HIPSPARSE_COOMM_ALG1#
enumerator HIPSPARSE_COOMM_ALG2#
enumerator HIPSPARSE_COOMM_ALG3#
enumerator HIPSPARSE_CSRMM_ALG1#
enumerator HIPSPARSE_SPMM_ALG_DEFAULT#
enumerator HIPSPARSE_SPMM_COO_ALG1#
enumerator HIPSPARSE_SPMM_COO_ALG2#
enumerator HIPSPARSE_SPMM_COO_ALG3#
enumerator HIPSPARSE_SPMM_COO_ALG4#
enumerator HIPSPARSE_SPMM_CSR_ALG1#
enumerator HIPSPARSE_SPMM_CSR_ALG2#
enumerator HIPSPARSE_SPMM_BLOCKED_ELL_ALG1#
enumerator HIPSPARSE_SPMM_CSR_ALG3#

hipsparseSparseToDenseAlg_t#

enum hipsparseSparseToDenseAlg_t#

Values:

enumerator HIPSPARSE_SPARSETODENSE_ALG_DEFAULT#

hipsparseDenseToSparseAlg_t#

enum hipsparseDenseToSparseAlg_t#

Values:

enumerator HIPSPARSE_DENSETOSPARSE_ALG_DEFAULT#

hipsparseSDDMMAlg_t#

enum hipsparseSDDMMAlg_t#

Values:

enumerator HIPSPARSE_SDDMM_ALG_DEFAULT#

hipsparseSpSVAlg_t#

enum hipsparseSpSVAlg_t#

Values:

enumerator HIPSPARSE_SPSV_ALG_DEFAULT#

hipsparseSpSMAlg_t#

enum hipsparseSpSMAlg_t#

Values:

enumerator HIPSPARSE_SPSM_ALG_DEFAULT#

hipsparseSpMatAttribute_t#

enum hipsparseSpMatAttribute_t#

Values:

enumerator HIPSPARSE_SPMAT_FILL_MODE#
enumerator HIPSPARSE_SPMAT_DIAG_TYPE#

hipsparseSpGEMMAlg_t#

enum hipsparseSpGEMMAlg_t#

Values:

enumerator HIPSPARSE_SPGEMM_DEFAULT#
enumerator HIPSPARSE_SPGEMM_CSR_ALG_NONDETERMINISTIC#
enumerator HIPSPARSE_SPGEMM_CSR_ALG_DETERMINISTIC#

Exported Sparse Functions#

Auxiliary Functions#

Function name

hipsparseCreate()

hipsparseDestroy()

hipsparseGetVersion()

hipsparseGetGitRevision()

hipsparseSetStream()

hipsparseGetStream()

hipsparseSetPointerMode()

hipsparseGetPointerMode()

hipsparseCreateMatDescr()

hipsparseDestroyMatDescr()

hipsparseCopyMatDescr()

hipsparseSetMatType()

hipsparseGetMatType()

hipsparseSetMatFillMode()

hipsparseGetMatFillMode()

hipsparseSetMatDiagType()

hipsparseGetMatDiagType()

hipsparseSetMatIndexBase()

hipsparseGetMatIndexBase()

hipsparseCreateHybMat()

hipsparseDestroyHybMat()

hipsparseCreateBsrsv2Info()

hipsparseDestroyBsrsv2Info()

hipsparseCreateBsrsm2Info()

hipsparseDestroyBsrsm2Info()

hipsparseCreateBsrilu02Info()

hipsparseDestroyBsrilu02Info()

hipsparseCreateBsric02Info()

hipsparseDestroyBsric02Info()

hipsparseCreateCsrsv2Info()

hipsparseDestroyCsrsv2Info()

hipsparseCreateCsrsm2Info()

hipsparseDestroyCsrsm2Info()

hipsparseCreateCsrilu02Info()

hipsparseDestroyCsrilu02Info()

hipsparseCreateCsric02Info()

hipsparseDestroyCsric02Info()

hipsparseCreateCsru2csrInfo()

hipsparseDestroyCsru2csrInfo()

hipsparseCreateColorInfo()

hipsparseDestroyColorInfo()

hipsparseCreateCsrgemm2Info()

hipsparseDestroyCsrgemm2Info()

hipsparseCreatePruneInfo()

hipsparseDestroyPruneInfo()

hipsparseCreateSpVec()

hipsparseDestroySpVec()

hipsparseSpVecGet()

hipsparseSpVecGetIndexBase()

hipsparseSpVecGetValues()

hipsparseSpVecSetValues()

hipsparseCreateCoo()

hipsparseCreateCooAoS()

hipsparseCreateCsr()

hipsparseCreateCsc()

hipsparseCreateBlockedEll()

hipsparseDestroySpMat()

hipsparseCooGet()

hipsparseCooAoSGet()

hipsparseCsrGet()

hipsparseBlockedEllGet()

hipsparseCsrSetPointers()

hipsparseCscSetPointers()

hipsparseCooSetPointers()

hipsparseSpMatGetSize()

hipsparseSpMatGetFormat()

hipsparseSpMatGetIndexBase()

hipsparseSpMatGetValues()

hipsparseSpMatSetValues()

hipsparseSpMatGetAttribute()

hipsparseSpMatSetAttribute()

hipsparseCreateDnVec()

hipsparseDestroyDnVec()

hipsparseDnVecGet()

hipsparseDnVecGetValues()

hipsparseDnVecSetValues()

hipsparseCreateDnMat()

hipsparseDestroyDnMat()

hipsparseDnMatGet()

hipsparseDnMatGetValues()

hipsparseDnMatSetValues()

Sparse Level 1 Functions#

Function name

single

double

single complex

double complex

hipsparseXaxpyi()

x

x

x

x

hipsparseXdoti()

x

x

x

x

hipsparseXdotci()

x

x

hipsparseXgthr()

x

x

x

x

hipsparseXgthrz()

x

x

x

x

hipsparseXroti()

x

x

hipsparseXsctr()

x

x

x

x

Sparse Level 2 Functions#

Function name

single

double

single complex

double complex

hipsparseXcsrmv()

x

x

x

x

hipsparseXcsrsv2_zeroPivot()

hipsparseXcsrsv2_bufferSize()

x

x

x

x

hipsparseXcsrsv2_bufferSizeExt()

x

x

x

x

hipsparseXcsrsv2_analysis()

x

x

x

x

hipsparseXcsrsv2_solve()

x

x

x

x

hipsparseXhybmv()

x

x

x

x

hipsparseXbsrmv()

x

x

x

x

hipsparseXbsrxmv()

x

x

x

x

hipsparseXbsrsv2_zeroPivot()

hipsparseXbsrsv2_bufferSize()

x

x

x

x

hipsparseXbsrsv2_bufferSizeExt()

x

x

x

x

hipsparseXbsrsv2_analysis()

x

x

x

x

hipsparseXbsrsv2_solve()

x

x

x

x

hipsparseXgemvi_bufferSize()

x

x

x

x

hipsparseXgemvi()

x

x

x

x

Sparse Level 3 Functions#

Function name

single

double

single complex

double complex

hipsparseXbsrmm()

x

x

x

x

hipsparseXcsrmm()

x

x

x

x

hipsparseXcsrmm2()

x

x

x

x

hipsparseXbsrsm2_zeroPivot()

hipsparseXbsrsm2_bufferSize()

x

x

x

x

hipsparseXbsrsm2_analysis()

x

x

x

x

hipsparseXbsrsm2_solve()

x

x

x

x

hipsparseXcsrsm2_zeroPivot()

hipsparseXcsrsm2_bufferSizeExt()

x

x

x

x

hipsparseXcsrsm2_analysis()

x

x

x

x

hipsparseXcsrsm2_solve()

x

x

x

x

hipsparseXgemmi()

x

x

x

x

Sparse Extra Functions#

Function name

single

double

single complex

double complex

hipsparseXcsrgeamNnz()

hipsparseXcsrgeam()

x

x

x

x

hipsparseXcsrgeam2_bufferSizeExt()

x

x

x

x

hipsparseXcsrgeam2Nnz()

hipsparseXcsrgeam2()

x

x

x

x

hipsparseXcsrgemmNnz()

hipsparseXcsrgemm()

x

x

x

x

hipsparseXcsrgemm2_bufferSizeExt()

x

x

x

x

hipsparseXcsrgemm2Nnz()

hipsparseXcsrgemm2()

x

x

x

x

Preconditioner Functions#

Function name

single

double

single complex

double complex

hipsparseXbsrilu02_zeroPivot()

hipsparseXbsrilu02_numericBoost()

x

x

x

x

hipsparseXbsrilu02_bufferSize()

x

x

x

x

hipsparseXbsrilu02_analysis()

x

x

x

x

hipsparseXbsrilu02()

x

x

x

x

hipsparseXcsrilu02_zeroPivot()

hipsparseXcsrilu02_numericBoost()

x

x

x

x

hipsparseXcsrilu02_bufferSize()

x

x

x

x

hipsparseXcsrilu02_bufferSizeExt()

x

x

x

x

hipsparseXcsrilu02_analysis()

x

x

x

x

hipsparseXcsrilu02()

x

x

x

x

hipsparseXbsric02_zeroPivot()

hipsparseXbsric02_bufferSize()

x

x

x

x

hipsparseXbsric02_analysis()

x

x

x

x

hipsparseXbsric02()

x

x

x

x

hipsparseXcsric02_zeroPivot()

hipsparseXcsric02_bufferSize()

x

x

x

x

hipsparseXcsric02_bufferSizeExt()

x

x

x

x

hipsparseXcsric02_analysis()

x

x

x

x

hipsparseXcsric02()

x

x

x

x

hipsparseXgtsv2_bufferSizeExt()

x

x

x

x

hipsparseXgtsv2()

x

x

x

x

hipsparseXgtsv2_nopivot_bufferSizeExt()

x

x

x

x

hipsparseXgtsv2_nopivot()

x

x

x

x

hipsparseXgtsv2StridedBatch_bufferSizeExt()

x

x

x

x

hipsparseXgtsv2StridedBatch()

x

x

x

x

hipsparseXgtsvInterleavedBatch_bufferSizeExt()

x

x

x

x

hipsparseXgtsvInterleavedBatch()

x

x

x

x

hipsparseXgpsvInterleavedBatch_bufferSizeExt()

x

x

x

x

hipsparseXgpsvInterleavedBatch()

x

x

x

x

Conversion Functions#

Function name

single

double

single complex

double complex

hipsparseXnnz()

x

x

x

x

hipsparseXdense2csr()

x

x

x

x

hipsparseXpruneDense2csr_bufferSize()

x

x

hipsparseXpruneDense2csrNnz()

x

x

hipsparseXpruneDense2csr()

x

x

hipsparseXpruneDense2csrByPercentage_bufferSize()

x

x

hipsparseXpruneDense2csrByPercentage_bufferSizeExt()

x

x

hipsparseXpruneDense2csrNnzByPercentage()

x

x

hipsparseXpruneDense2csrByPercentage()

x

x

hipsparseXdense2csc()

x

x

x

x

hipsparseXcsr2dense()

x

x

x

x

hipsparseXcsc2dense()

x

x

x

x

hipsparseXcsr2bsrNnz()

hipsparseXcsr2bsr()

x

x

x

x

hipsparseXnnz_compress()

x

x

x

x

hipsparseXcsr2coo()

hipsparseXcsr2csc()

x

x

x

x

hipsparseXcsr2hyb()

x

x

x

x

hipsparseXgebsr2gebsc_bufferSize

x

x

x

x

hipsparseXgebsr2gebsc()

x

x

x

x

hipsparseXcsr2gebsr_bufferSize()

x

x

x

x

hipsparseXcsr2gebsrNnz()

hipsparseXcsr2gebsr()

x

x

x

x

hipsparseXbsr2csr()

x

x

x

x

hipsparseXgebsr2csr()

x

x

x

x

hipsparseXcsr2csr_compress()

x

x

x

x

hipsparseXpruneCsr2csr_bufferSize()

x

x

hipsparseXpruneCsr2csr_bufferSizeExt()

x

x

hipsparseXpruneCsr2csrNnz()

x

x

hipsparseXpruneCsr2csr()

x

x

hipsparseXpruneCsr2csrByPercentage_bufferSize()

x

x

hipsparseXpruneCsr2csrByPercentage_bufferSizeExt()

x

x

hipsparseXpruneCsr2csrNnzByPercentage()

x

x

hipsparseXpruneCsr2csrByPercentage()

x

x

hipsparseXhyb2csr()

x

x

x

x

hipsparseXcoo2csr()

hipsparseCreateIdentityPermutation()

hipsparseXcsrsort_bufferSizeExt()

hipsparseXcsrsort()

hipsparseXcscsort_bufferSizeExt()

hipsparseXcscsort()

hipsparseXcoosort_bufferSizeExt()

hipsparseXcoosortByRow()

hipsparseXcoosortByColumn()

hipsparseXgebsr2gebsr_bufferSize()

x

x

x

x

hipsparseXgebsr2gebsrNnz()

hipsparseXgebsr2gebsr()

x

x

x

x

hipsparseXcsru2csr_bufferSizeExt()

x

x

x

x

hipsparseXcsru2csr()

x

x

x

x

hipsparseXcsr2csru()

x

x

x

x

Reordering Functions#

Function name

single

double

single complex

double complex

hipsparseXcsrcolor()

x

x

x

x

Sparse Generic Functions#

Function name

single

double

single complex

double complex

hipsparseAxpby()

x

x

x

x

hipsparseGather()

x

x

x

x

hipsparseScatter()

x

x

x

x

hipsparseRot()

x

x

x

x

hipsparseSparseToDense_bufferSize()

x

x

x

x

hipsparseSparseToDense()

x

x

x

x

hipsparseDenseToSparse_bufferSize()

x

x

x

x

hipsparseDenseToSparse_analysis()

x

x

x

x

hipsparseDenseToSparse_convert()

x

x

x

x

hipsparseSpVV_bufferSize()

x

x

x

x

hipsparseSpVV()

x

x

x

x

hipsparseSpMV_bufferSize()

x

x

x

x

hipsparseSpMV()

x

x

x

x

hipsparseSpMM_bufferSize()

x

x

x

x

hipsparseSpMM_preprocess()

x

x

x

x

hipsparseSpMM()

x

x

x

x

hipsparseSpGEMM_createDescr()

x

x

x

x

hipsparseSpGEMM_destroyDescr()

x

x

x

x

hipsparseSpGEMM_workEstimation()

x

x

x

x

hipsparseSpGEMM_compute()

x

x

x

x

hipsparseSpGEMM_copy()

x

x

x

x

hipsparseSDDMM_bufferSize()

x

x

x

x

hipsparseSDDMM_preprocess()

x

x

x

x

hipsparseSDDMM()

x

x

x

x

hipsparseSpSV_createDescr()

x

x

x

x

hipsparseSpSV_destroyDescr()

x

x

x

x

hipsparseSpSV_bufferSize()

x

x

x

x

hipsparseSpSV_analysis()

x

x

x

x

hipsparseSpSV_solve()

x

x

x

x

hipsparseSpSM_createDescr()

x

x

x

x

hipsparseSpSM_destroyDescr()

x

x

x

x

hipsparseSpSM_bufferSize()

x

x

x

x

hipsparseSpSM_analysis()

x

x

x

x

hipsparseSpSM_solve()

x

x

x

x

Storage schemes and indexing base#

hipSPARSE supports 0 and 1 based indexing. The index base is selected by the hipsparseIndexBase_t type which is either passed as standalone parameter or as part of the hipsparseMatDescr_t type.

Furthermore, dense vectors are represented with a 1D array, stored linearly in memory. Sparse vectors are represented by a 1D data array stored linearly in memory that hold all non-zero elements and a 1D indexing array stored linearly in memory that hold the positions of the corresponding non-zero elements.

Pointer mode#

The auxiliary functions hipsparseSetPointerMode() and hipsparseGetPointerMode() are used to set and get the value of the state variable hipsparsePointerMode_t. If hipsparsePointerMode_t is equal to HIPSPARSE_POINTER_MODE_HOST, then scalar parameters must be allocated on the host. If hipsparsePointerMode_t is equal to HIPSPARSE_POINTER_MODE_DEVICE, then scalar parameters must be allocated on the device.

There are two types of scalar parameter:

  1. Scaling parameters, such as alpha and beta used in e.g. hipsparseScsrmv(), hipsparseSbsrmv(), …

  2. Scalar results from functions such as hipsparseSdoti(), hipsparseCdotci(), …

For scalar parameters such as alpha and beta, memory can be allocated on the host heap or stack, when hipsparsePointerMode_t is equal to HIPSPARSE_POINTER_MODE_HOST. The kernel launch is asynchronous, and if the scalar parameter is on the heap, it can be freed after the return from the kernel launch. When hipsparsePointerMode_t is equal to HIPSPARSE_POINTER_MODE_DEVICE, the scalar parameter must not be changed till the kernel completes.

For scalar results, when hipsparsePointerMode_t is equal to HIPSPARSE_POINTER_MODE_HOST, the function blocks the CPU till the GPU has copied the result back to the host. Using hipsparsePointerMode_t equal to HIPSPARSE_POINTER_MODE_DEVICE, the function will return after the asynchronous launch. Similarly to vector and matrix results, the scalar result is only available when the kernel has completed execution.

Asynchronous API#

Except a functions having memory allocation inside preventing asynchronicity, all hipSPARSE functions are configured to operate in non-blocking fashion with respect to CPU, meaning these library functions return immediately.

Sparse Auxiliary Functions#

This module holds all sparse auxiliary functions.

The functions that are contained in the auxiliary module describe all available helper functions that are required for subsequent library calls.

hipsparseCreate()#

hipsparseStatus_t hipsparseCreate(hipsparseHandle_t *handle)#

Create a hipsparse handle.

hipsparseCreate creates the hipSPARSE library context. It must be initialized before any other hipSPARSE API function is invoked and must be passed to all subsequent library function calls. The handle should be destroyed at the end using hipsparseDestroy().

hipsparseDestroy()#

hipsparseStatus_t hipsparseDestroy(hipsparseHandle_t handle)#

Destroy a hipsparse handle.

hipsparseDestroy destroys the hipSPARSE library context and releases all resources used by the hipSPARSE library.

hipsparseGetVersion()#

hipsparseStatus_t hipsparseGetVersion(hipsparseHandle_t handle, int *version)#

Get hipSPARSE version.

hipsparseGetVersion gets the hipSPARSE library version number.

  • patch = version % 100

  • minor = version / 100 % 1000

  • major = version / 100000

hipsparseGetGitRevision()#

hipsparseStatus_t hipsparseGetGitRevision(hipsparseHandle_t handle, char *rev)#

Get hipSPARSE git revision.

hipsparseGetGitRevision gets the hipSPARSE library git commit revision (SHA-1).

hipsparseSetStream()#

hipsparseStatus_t hipsparseSetStream(hipsparseHandle_t handle, hipStream_t streamId)#

Specify user defined HIP stream.

hipsparseSetStream specifies the stream to be used by the hipSPARSE library context and all subsequent function calls.

hipsparseGetStream()#

hipsparseStatus_t hipsparseGetStream(hipsparseHandle_t handle, hipStream_t *streamId)#

Get current stream from library context.

hipsparseGetStream gets the hipSPARSE library context stream which is currently used for all subsequent function calls.

hipsparseSetPointerMode()#

hipsparseStatus_t hipsparseSetPointerMode(hipsparseHandle_t handle, hipsparsePointerMode_t mode)#

Specify pointer mode.

hipsparseSetPointerMode specifies the pointer mode to be used by the hipSPARSE library context and all subsequent function calls. By default, all values are passed by reference on the host. Valid pointer modes are HIPSPARSE_POINTER_MODE_HOST or HIPSPARSE_POINTER_MODE_DEVICE.

hipsparseGetPointerMode()#

hipsparseStatus_t hipsparseGetPointerMode(hipsparseHandle_t handle, hipsparsePointerMode_t *mode)#

Get current pointer mode from library context.

hipsparseGetPointerMode gets the hipSPARSE library context pointer mode which is currently used for all subsequent function calls.

hipsparseCreateMatDescr()#

hipsparseStatus_t hipsparseCreateMatDescr(hipsparseMatDescr_t *descrA)#

Create a matrix descriptor.

hipsparseCreateMatDescr creates a matrix descriptor. It initializes hipsparseMatrixType_t to HIPSPARSE_MATRIX_TYPE_GENERAL and hipsparseIndexBase_t to HIPSPARSE_INDEX_BASE_ZERO. It should be destroyed at the end using hipsparseDestroyMatDescr().

hipsparseDestroyMatDescr()#

hipsparseStatus_t hipsparseDestroyMatDescr(hipsparseMatDescr_t descrA)#

Destroy a matrix descriptor.

hipsparseDestroyMatDescr destroys a matrix descriptor and releases all resources used by the descriptor.

hipsparseCopyMatDescr()#

hipsparseStatus_t hipsparseCopyMatDescr(hipsparseMatDescr_t dest, const hipsparseMatDescr_t src)#

Copy a matrix descriptor.

hipsparseCopyMatDescr copies a matrix descriptor. Both, source and destination matrix descriptors must be initialized prior to calling hipsparseCopyMatDescr.

hipsparseSetMatType()#

hipsparseStatus_t hipsparseSetMatType(hipsparseMatDescr_t descrA, hipsparseMatrixType_t type)#

Specify the matrix type of a matrix descriptor.

hipsparseSetMatType sets the matrix type of a matrix descriptor. Valid matrix types are HIPSPARSE_MATRIX_TYPE_GENERAL, HIPSPARSE_MATRIX_TYPE_SYMMETRIC, HIPSPARSE_MATRIX_TYPE_HERMITIAN or HIPSPARSE_MATRIX_TYPE_TRIANGULAR.

hipsparseGetMatType()#

hipsparseMatrixType_t hipsparseGetMatType(const hipsparseMatDescr_t descrA)#

Get the matrix type of a matrix descriptor.

hipsparseGetMatType returns the matrix type of a matrix descriptor.

hipsparseSetMatFillMode()#

hipsparseStatus_t hipsparseSetMatFillMode(hipsparseMatDescr_t descrA, hipsparseFillMode_t fillMode)#

Specify the matrix fill mode of a matrix descriptor.

hipsparseSetMatFillMode sets the matrix fill mode of a matrix descriptor. Valid fill modes are HIPSPARSE_FILL_MODE_LOWER or HIPSPARSE_FILL_MODE_UPPER.

hipsparseGetMatFillMode()#

hipsparseFillMode_t hipsparseGetMatFillMode(const hipsparseMatDescr_t descrA)#

Get the matrix fill mode of a matrix descriptor.

hipsparseGetMatFillMode returns the matrix fill mode of a matrix descriptor.

hipsparseSetMatDiagType()#

hipsparseStatus_t hipsparseSetMatDiagType(hipsparseMatDescr_t descrA, hipsparseDiagType_t diagType)#

Specify the matrix diagonal type of a matrix descriptor.

hipsparseSetMatDiagType sets the matrix diagonal type of a matrix descriptor. Valid diagonal types are HIPSPARSE_DIAG_TYPE_UNIT or HIPSPARSE_DIAG_TYPE_NON_UNIT.

hipsparseGetMatDiagType()#

hipsparseDiagType_t hipsparseGetMatDiagType(const hipsparseMatDescr_t descrA)#

Get the matrix diagonal type of a matrix descriptor.

hipsparseGetMatDiagType returns the matrix diagonal type of a matrix descriptor.

hipsparseSetMatIndexBase()#

hipsparseStatus_t hipsparseSetMatIndexBase(hipsparseMatDescr_t descrA, hipsparseIndexBase_t base)#

Specify the index base of a matrix descriptor.

hipsparseSetMatIndexBase sets the index base of a matrix descriptor. Valid options are HIPSPARSE_INDEX_BASE_ZERO or HIPSPARSE_INDEX_BASE_ONE.

hipsparseGetMatIndexBase()#

hipsparseIndexBase_t hipsparseGetMatIndexBase(const hipsparseMatDescr_t descrA)#

Get the index base of a matrix descriptor.

hipsparseGetMatIndexBase returns the index base of a matrix descriptor.

hipsparseCreateHybMat()#

hipsparseStatus_t hipsparseCreateHybMat(hipsparseHybMat_t *hybA)#

Create a HYB matrix structure.

hipsparseCreateHybMat creates a structure that holds the matrix in HYB storage format. It should be destroyed at the end using hipsparseDestroyHybMat().

hipsparseDestroyHybMat()#

hipsparseStatus_t hipsparseDestroyHybMat(hipsparseHybMat_t hybA)#

Destroy a HYB matrix structure.

hipsparseDestroyHybMat destroys a HYB structure.

hipsparseCreateBsrsv2Info()#

hipsparseStatus_t hipsparseCreateBsrsv2Info(bsrsv2Info_t *info)#

Create a bsrsv2 info structure.

hipsparseCreateBsrsv2Info creates a structure that holds the bsrsv2 info data that is gathered during the analysis routines available. It should be destroyed at the end using hipsparseDestroyBsrsv2Info().

hipsparseDestroyBsrsv2Info()#

hipsparseStatus_t hipsparseDestroyBsrsv2Info(bsrsv2Info_t info)#

Destroy a bsrsv2 info structure.

hipsparseDestroyBsrsv2Info destroys a bsrsv2 info structure.

hipsparseCreateBsrsm2Info()#

hipsparseStatus_t hipsparseCreateBsrsm2Info(bsrsm2Info_t *info)#

Create a bsrsm2 info structure.

hipsparseCreateBsrsm2Info creates a structure that holds the bsrsm2 info data that is gathered during the analysis routines available. It should be destroyed at the end using hipsparseDestroyBsrsm2Info().

hipsparseDestroyBsrsm2Info()#

hipsparseStatus_t hipsparseDestroyBsrsm2Info(bsrsm2Info_t info)#

Destroy a bsrsm2 info structure.

hipsparseDestroyBsrsm2Info destroys a bsrsm2 info structure.

hipsparseCreateBsrilu02Info()#

hipsparseStatus_t hipsparseCreateBsrilu02Info(bsrilu02Info_t *info)#

Create a bsrilu02 info structure.

hipsparseCreateBsrilu02Info creates a structure that holds the bsrilu02 info data that is gathered during the analysis routines available. It should be destroyed at the end using hipsparseDestroyBsrilu02Info().

hipsparseDestroyBsrilu02Info()#

hipsparseStatus_t hipsparseDestroyBsrilu02Info(bsrilu02Info_t info)#

Destroy a bsrilu02 info structure.

hipsparseDestroyBsrilu02Info destroys a bsrilu02 info structure.

hipsparseCreateBsric02Info()#

hipsparseStatus_t hipsparseCreateBsric02Info(bsric02Info_t *info)#

Create a bsric02 info structure.

hipsparseCreateBsric02Info creates a structure that holds the bsric02 info data that is gathered during the analysis routines available. It should be destroyed at the end using hipsparseDestroyBsric02Info().

hipsparseDestroyBsric02Info()#

hipsparseStatus_t hipsparseDestroyBsric02Info(bsric02Info_t info)#

Destroy a bsric02 info structure.

hipsparseDestroyBsric02Info destroys a bsric02 info structure.

hipsparseCreateCsrsv2Info()#

hipsparseStatus_t hipsparseCreateCsrsv2Info(csrsv2Info_t *info)#

Create a csrsv2 info structure.

hipsparseCreateCsrsv2Info creates a structure that holds the csrsv2 info data that is gathered during the analysis routines available. It should be destroyed at the end using hipsparseDestroyCsrsv2Info().

hipsparseDestroyCsrsv2Info()#

hipsparseStatus_t hipsparseDestroyCsrsv2Info(csrsv2Info_t info)#

Destroy a csrsv2 info structure.

hipsparseDestroyCsrsv2Info destroys a csrsv2 info structure.

hipsparseCreateCsrsm2Info()#

hipsparseStatus_t hipsparseCreateCsrsm2Info(csrsm2Info_t *info)#

Create a csrsm2 info structure.

hipsparseCreateCsrsm2Info creates a structure that holds the csrsm2 info data that is gathered during the analysis routines available. It should be destroyed at the end using hipsparseDestroyCsrsm2Info().

hipsparseDestroyCsrsm2Info()#

hipsparseStatus_t hipsparseDestroyCsrsm2Info(csrsm2Info_t info)#

Destroy a csrsm2 info structure.

hipsparseDestroyCsrsm2Info destroys a csrsm2 info structure.

hipsparseCreateCsrilu02Info()#

hipsparseStatus_t hipsparseCreateCsrilu02Info(csrilu02Info_t *info)#

Create a csrilu02 info structure.

hipsparseCreateCsrilu02Info creates a structure that holds the csrilu02 info data that is gathered during the analysis routines available. It should be destroyed at the end using hipsparseDestroyCsrilu02Info().

hipsparseDestroyCsrilu02Info()#

hipsparseStatus_t hipsparseDestroyCsrilu02Info(csrilu02Info_t info)#

Destroy a csrilu02 info structure.

hipsparseDestroyCsrilu02Info destroys a csrilu02 info structure.

hipsparseCreateCsric02Info()#

hipsparseStatus_t hipsparseCreateCsric02Info(csric02Info_t *info)#

Create a csric02 info structure.

hipsparseCreateCsric02Info creates a structure that holds the csric02 info data that is gathered during the analysis routines available. It should be destroyed at the end using hipsparseDestroyCsric02Info().

hipsparseDestroyCsric02Info()#

hipsparseStatus_t hipsparseDestroyCsric02Info(csric02Info_t info)#

Destroy a csric02 info structure.

hipsparseDestroyCsric02Info destroys a csric02 info structure.

hipsparseCreateCsru2csrInfo()#

hipsparseStatus_t hipsparseCreateCsru2csrInfo(csru2csrInfo_t *info)#

Create a csru2csr info structure.

hipsparseCreateCsru2csrInfo creates a structure that holds the csru2csr info data that is gathered during the analysis routines available. It should be destroyed at the end using hipsparseDestroyCsru2csrInfo().

hipsparseDestroyCsru2csrInfo()#

hipsparseStatus_t hipsparseDestroyCsru2csrInfo(csru2csrInfo_t info)#

Destroy a csru2csr info structure.

hipsparseDestroyCsru2csrInfo destroys a csru2csr info structure.

hipsparseCreateColorInfo()#

hipsparseStatus_t hipsparseCreateColorInfo(hipsparseColorInfo_t *info)#

Create a color info structure.

hipsparseCreateColorInfo creates a structure that holds the color info data that is gathered during the analysis routines available. It should be destroyed at the end using hipsparseDestroyColorInfo().

hipsparseDestroyColorInfo()#

hipsparseStatus_t hipsparseDestroyColorInfo(hipsparseColorInfo_t info)#

Destroy a color info structure.

hipsparseDestroyColorInfo destroys a color info structure.

hipsparseCreateCsrgemm2Info()#

hipsparseStatus_t hipsparseCreateCsrgemm2Info(csrgemm2Info_t *info)#

Create a csrgemm2 info structure.

hipsparseCreateCsrgemm2Info creates a structure that holds the csrgemm2 info data that is gathered during the analysis routines available. It should be destroyed at the end using hipsparseDestroyCsrgemm2Info().

hipsparseDestroyCsrgemm2Info()#

hipsparseStatus_t hipsparseDestroyCsrgemm2Info(csrgemm2Info_t info)#

Destroy a csrgemm2 info structure.

hipsparseDestroyCsrgemm2Info destroys a csrgemm2 info structure.

hipsparseCreatePruneInfo()#

hipsparseStatus_t hipsparseCreatePruneInfo(pruneInfo_t *info)#

Create a prune info structure.

hipsparseCreatePruneInfo creates a structure that holds the prune info data that is gathered during the analysis routines available. It should be destroyed at the end using hipsparseDestroyPruneInfo().

hipsparseDestroyPruneInfo()#

hipsparseStatus_t hipsparseDestroyPruneInfo(pruneInfo_t info)#

Destroy a prune info structure.

hipsparseDestroyPruneInfo destroys a prune info structure.

hipsparseCreateSpVec()#

hipsparseStatus_t hipsparseCreateSpVec(hipsparseSpVecDescr_t *spVecDescr, int64_t size, int64_t nnz, void *indices, void *values, hipsparseIndexType_t idxType, hipsparseIndexBase_t idxBase, hipDataType valueType)#

hipsparseDestroySpVec()#

hipsparseStatus_t hipsparseDestroySpVec(hipsparseSpVecDescr_t spVecDescr)#

hipsparseSpVecGet()#

hipsparseStatus_t hipsparseSpVecGet(const hipsparseSpVecDescr_t spVecDescr, int64_t *size, int64_t *nnz, void **indices, void **values, hipsparseIndexType_t *idxType, hipsparseIndexBase_t *idxBase, hipDataType *valueType)#

hipsparseSpVecGetIndexBase()#

hipsparseStatus_t hipsparseSpVecGetIndexBase(const hipsparseSpVecDescr_t spVecDescr, hipsparseIndexBase_t *idxBase)#

hipsparseSpVecGetValues()#

hipsparseStatus_t hipsparseSpVecGetValues(const hipsparseSpVecDescr_t spVecDescr, void **values)#

hipsparseSpVecSetValues()#

hipsparseStatus_t hipsparseSpVecSetValues(hipsparseSpVecDescr_t spVecDescr, void *values)#

hipsparseCreateCoo()#

hipsparseStatus_t hipsparseCreateCoo(hipsparseSpMatDescr_t *spMatDescr, int64_t rows, int64_t cols, int64_t nnz, void *cooRowInd, void *cooColInd, void *cooValues, hipsparseIndexType_t cooIdxType, hipsparseIndexBase_t idxBase, hipDataType valueType)#

hipsparseCreateCooAoS()#

hipsparseStatus_t hipsparseCreateCooAoS(hipsparseSpMatDescr_t *spMatDescr, int64_t rows, int64_t cols, int64_t nnz, void *cooInd, void *cooValues, hipsparseIndexType_t cooIdxType, hipsparseIndexBase_t idxBase, hipDataType valueType)#

hipsparseCreateCsr()#

hipsparseStatus_t hipsparseCreateCsr(hipsparseSpMatDescr_t *spMatDescr, int64_t rows, int64_t cols, int64_t nnz, void *csrRowOffsets, void *csrColInd, void *csrValues, hipsparseIndexType_t csrRowOffsetsType, hipsparseIndexType_t csrColIndType, hipsparseIndexBase_t idxBase, hipDataType valueType)#

hipsparseCreateCsc()#

hipsparseStatus_t hipsparseCreateCsc(hipsparseSpMatDescr_t *spMatDescr, int64_t rows, int64_t cols, int64_t nnz, void *cscColOffsets, void *cscRowInd, void *cscValues, hipsparseIndexType_t cscColOffsetsType, hipsparseIndexType_t cscRowIndType, hipsparseIndexBase_t idxBase, hipDataType valueType)#

hipsparseCreateBlockedEll()#

hipsparseStatus_t hipsparseCreateBlockedEll(hipsparseSpMatDescr_t *spMatDescr, int64_t rows, int64_t cols, int64_t ellBlockSize, int64_t ellCols, void *ellColInd, void *ellValue, hipsparseIndexType_t ellIdxType, hipsparseIndexBase_t idxBase, hipDataType valueType)#

hipsparseDestroySpMat()#

hipsparseStatus_t hipsparseDestroySpMat(hipsparseSpMatDescr_t spMatDescr)#

hipsparseCooGet()#

hipsparseStatus_t hipsparseCooGet(const hipsparseSpMatDescr_t spMatDescr, int64_t *rows, int64_t *cols, int64_t *nnz, void **cooRowInd, void **cooColInd, void **cooValues, hipsparseIndexType_t *idxType, hipsparseIndexBase_t *idxBase, hipDataType *valueType)#

hipsparseCooAoSGet()#

hipsparseStatus_t hipsparseCooAoSGet(const hipsparseSpMatDescr_t spMatDescr, int64_t *rows, int64_t *cols, int64_t *nnz, void **cooInd, void **cooValues, hipsparseIndexType_t *idxType, hipsparseIndexBase_t *idxBase, hipDataType *valueType)#

hipsparseCsrGet()#

hipsparseStatus_t hipsparseCsrGet(const hipsparseSpMatDescr_t spMatDescr, int64_t *rows, int64_t *cols, int64_t *nnz, void **csrRowOffsets, void **csrColInd, void **csrValues, hipsparseIndexType_t *csrRowOffsetsType, hipsparseIndexType_t *csrColIndType, hipsparseIndexBase_t *idxBase, hipDataType *valueType)#

hipsparseBlockedEllGet()#

hipsparseStatus_t hipsparseBlockedEllGet(const hipsparseSpMatDescr_t spMatDescr, int64_t *rows, int64_t *cols, int64_t *ellBlockSize, int64_t *ellCols, void **ellColInd, void **ellValue, hipsparseIndexType_t *ellIdxType, hipsparseIndexBase_t *idxBase, hipDataType *valueType)#

hipsparseCsrSetPointers()#

hipsparseStatus_t hipsparseCsrSetPointers(hipsparseSpMatDescr_t spMatDescr, void *csrRowOffsets, void *csrColInd, void *csrValues)#

hipsparseCscSetPointers()#

hipsparseStatus_t hipsparseCscSetPointers(hipsparseSpMatDescr_t spMatDescr, void *cscColOffsets, void *cscRowInd, void *cscValues)#

hipsparseCooSetPointers()#

hipsparseStatus_t hipsparseCooSetPointers(hipsparseSpMatDescr_t spMatDescr, void *cooRowInd, void *cooColInd, void *cooValues)#

hipsparseSpMatGetSize()#

hipsparseStatus_t hipsparseSpMatGetSize(hipsparseSpMatDescr_t spMatDescr, int64_t *rows, int64_t *cols, int64_t *nnz)#

hipsparseSpMatGetFormat()#

hipsparseStatus_t hipsparseSpMatGetFormat(const hipsparseSpMatDescr_t spMatDescr, hipsparseFormat_t *format)#

hipsparseSpMatGetIndexBase()#

hipsparseStatus_t hipsparseSpMatGetIndexBase(const hipsparseSpMatDescr_t spMatDescr, hipsparseIndexBase_t *idxBase)#

hipsparseSpMatGetValues()#

hipsparseStatus_t hipsparseSpMatGetValues(hipsparseSpMatDescr_t spMatDescr, void **values)#

hipsparseSpMatSetValues()#

hipsparseStatus_t hipsparseSpMatSetValues(hipsparseSpMatDescr_t spMatDescr, void *values)#

hipsparseSpMatGetAttribute()#

hipsparseStatus_t hipsparseSpMatGetAttribute(hipsparseSpMatDescr_t spMatDescr, hipsparseSpMatAttribute_t attribute, void *data, size_t dataSize)#

hipsparseSpMatSetAttribute()#

hipsparseStatus_t hipsparseSpMatSetAttribute(hipsparseSpMatDescr_t spMatDescr, hipsparseSpMatAttribute_t attribute, const void *data, size_t dataSize)#

hipsparseCreateDnVec()#

hipsparseStatus_t hipsparseCreateDnVec(hipsparseDnVecDescr_t *dnVecDescr, int64_t size, void *values, hipDataType valueType)#

hipsparseDestroyDnVec()#

hipsparseStatus_t hipsparseDestroyDnVec(hipsparseDnVecDescr_t dnVecDescr)#

hipsparseDnVecGet()#

hipsparseStatus_t hipsparseDnVecGet(const hipsparseDnVecDescr_t dnVecDescr, int64_t *size, void **values, hipDataType *valueType)#

hipsparseDnVecGetValues()#

hipsparseStatus_t hipsparseDnVecGetValues(const hipsparseDnVecDescr_t dnVecDescr, void **values)#

hipsparseDnVecSetValues()#

hipsparseStatus_t hipsparseDnVecSetValues(hipsparseDnVecDescr_t dnVecDescr, void *values)#

hipsparseCreateDnMat()#

hipsparseStatus_t hipsparseCreateDnMat(hipsparseDnMatDescr_t *dnMatDescr, int64_t rows, int64_t cols, int64_t ld, void *values, hipDataType valueType, hipsparseOrder_t order)#

hipsparseDestroyDnMat()#

hipsparseStatus_t hipsparseDestroyDnMat(hipsparseDnMatDescr_t dnMatDescr)#

hipsparseDnMatGet()#

hipsparseStatus_t hipsparseDnMatGet(const hipsparseDnMatDescr_t dnMatDescr, int64_t *rows, int64_t *cols, int64_t *ld, void **values, hipDataType *valueType, hipsparseOrder_t *order)#

hipsparseDnMatGetValues()#

hipsparseStatus_t hipsparseDnMatGetValues(const hipsparseDnMatDescr_t dnMatDescr, void **values)#

hipsparseDnMatSetValues()#

hipsparseStatus_t hipsparseDnMatSetValues(hipsparseDnMatDescr_t dnMatDescr, void *values)#

Sparse Level 1 Functions#

The sparse level 1 routines describe operations between a vector in sparse format and a vector in dense format. This section describes all hipSPARSE level 1 sparse linear algebra functions.

hipsparseXaxpyi()#

hipsparseStatus_t hipsparseSaxpyi(hipsparseHandle_t handle, int nnz, const float *alpha, const float *xVal, const int *xInd, float *y, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseDaxpyi(hipsparseHandle_t handle, int nnz, const double *alpha, const double *xVal, const int *xInd, double *y, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseCaxpyi(hipsparseHandle_t handle, int nnz, const hipComplex *alpha, const hipComplex *xVal, const int *xInd, hipComplex *y, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseZaxpyi(hipsparseHandle_t handle, int nnz, const hipDoubleComplex *alpha, const hipDoubleComplex *xVal, const int *xInd, hipDoubleComplex *y, hipsparseIndexBase_t idxBase)#

Scale a sparse vector and add it to a dense vector.

hipsparseXaxpyi multiplies the sparse vector \(x\) with scalar \(\alpha\) and adds the result to the dense vector \(y\), such that

\[ y := y + \alpha \cdot x \]

for(i = 0; i < nnz; ++i)
{
    y[x_ind[i]] = y[x_ind[i]] + alpha * x_val[i];
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXdoti()#

hipsparseStatus_t hipsparseSdoti(hipsparseHandle_t handle, int nnz, const float *xVal, const int *xInd, const float *y, float *result, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseDdoti(hipsparseHandle_t handle, int nnz, const double *xVal, const int *xInd, const double *y, double *result, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseCdoti(hipsparseHandle_t handle, int nnz, const hipComplex *xVal, const int *xInd, const hipComplex *y, hipComplex *result, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseZdoti(hipsparseHandle_t handle, int nnz, const hipDoubleComplex *xVal, const int *xInd, const hipDoubleComplex *y, hipDoubleComplex *result, hipsparseIndexBase_t idxBase)#

Compute the dot product of a sparse vector with a dense vector.

hipsparseXdoti computes the dot product of the sparse vector \(x\) with the dense vector \(y\), such that

\[ \text{result} := y^T x \]

for(i = 0; i < nnz; ++i)
{
    result += x_val[i] * y[x_ind[i]];
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXdotci()#

hipsparseStatus_t hipsparseCdotci(hipsparseHandle_t handle, int nnz, const hipComplex *xVal, const int *xInd, const hipComplex *y, hipComplex *result, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseZdotci(hipsparseHandle_t handle, int nnz, const hipDoubleComplex *xVal, const int *xInd, const hipDoubleComplex *y, hipDoubleComplex *result, hipsparseIndexBase_t idxBase)#

Compute the dot product of a complex conjugate sparse vector with a dense vector.

hipsparseXdotci computes the dot product of the complex conjugate sparse vector \(x\) with the dense vector \(y\), such that

\[ \text{result} := \bar{x}^H y \]

for(i = 0; i < nnz; ++i)
{
    result += conj(x_val[i]) * y[x_ind[i]];
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXgthr()#

hipsparseStatus_t hipsparseSgthr(hipsparseHandle_t handle, int nnz, const float *y, float *xVal, const int *xInd, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseDgthr(hipsparseHandle_t handle, int nnz, const double *y, double *xVal, const int *xInd, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseCgthr(hipsparseHandle_t handle, int nnz, const hipComplex *y, hipComplex *xVal, const int *xInd, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseZgthr(hipsparseHandle_t handle, int nnz, const hipDoubleComplex *y, hipDoubleComplex *xVal, const int *xInd, hipsparseIndexBase_t idxBase)#

Gather elements from a dense vector and store them into a sparse vector.

hipsparseXgthr gathers the elements that are listed in x_ind from the dense vector \(y\) and stores them in the sparse vector \(x\).

for(i = 0; i < nnz; ++i)
{
    x_val[i] = y[x_ind[i]];
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXgthrz()#

hipsparseStatus_t hipsparseSgthrz(hipsparseHandle_t handle, int nnz, float *y, float *xVal, const int *xInd, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseDgthrz(hipsparseHandle_t handle, int nnz, double *y, double *xVal, const int *xInd, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseCgthrz(hipsparseHandle_t handle, int nnz, hipComplex *y, hipComplex *xVal, const int *xInd, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseZgthrz(hipsparseHandle_t handle, int nnz, hipDoubleComplex *y, hipDoubleComplex *xVal, const int *xInd, hipsparseIndexBase_t idxBase)#

Gather and zero out elements from a dense vector and store them into a sparse vector.

hipsparseXgthrz gathers the elements that are listed in x_ind from the dense vector \(y\) and stores them in the sparse vector \(x\). The gathered elements in \(y\) are replaced by zero.

for(i = 0; i < nnz; ++i)
{
    x_val[i]    = y[x_ind[i]];
    y[x_ind[i]] = 0;
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXroti()#

hipsparseStatus_t hipsparseSroti(hipsparseHandle_t handle, int nnz, float *xVal, const int *xInd, float *y, const float *c, const float *s, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseDroti(hipsparseHandle_t handle, int nnz, double *xVal, const int *xInd, double *y, const double *c, const double *s, hipsparseIndexBase_t idxBase)#

Apply Givens rotation to a dense and a sparse vector.

hipsparseXroti applies the Givens rotation matrix \(G\) to the sparse vector \(x\) and the dense vector \(y\), where

\[\begin{split} G = \begin{pmatrix} c & s \\ -s & c \end{pmatrix} \end{split}\]

for(i = 0; i < nnz; ++i)
{
    x_tmp = x_val[i];
    y_tmp = y[x_ind[i]];

    x_val[i]    = c * x_tmp + s * y_tmp;
    y[x_ind[i]] = c * y_tmp - s * x_tmp;
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXsctr()#

hipsparseStatus_t hipsparseSsctr(hipsparseHandle_t handle, int nnz, const float *xVal, const int *xInd, float *y, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseDsctr(hipsparseHandle_t handle, int nnz, const double *xVal, const int *xInd, double *y, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseCsctr(hipsparseHandle_t handle, int nnz, const hipComplex *xVal, const int *xInd, hipComplex *y, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseZsctr(hipsparseHandle_t handle, int nnz, const hipDoubleComplex *xVal, const int *xInd, hipDoubleComplex *y, hipsparseIndexBase_t idxBase)#

Scatter elements from a dense vector across a sparse vector.

hipsparseXsctr scatters the elements that are listed in x_ind from the sparse vector \(x\) into the dense vector \(y\). Indices of \(y\) that are not listed in x_ind remain unchanged.

for(i = 0; i < nnz; ++i)
{
    y[x_ind[i]] = x_val[i];
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Sparse Level 2 Functions#

This module holds all sparse level 2 routines.

The sparse level 2 routines describe operations between a matrix in sparse format and a vector in dense format.

hipsparseXcsrmv()#

hipsparseStatus_t hipsparseScsrmv(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, int nnz, const float *alpha, const hipsparseMatDescr_t descrA, const float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const float *x, const float *beta, float *y)#
hipsparseStatus_t hipsparseDcsrmv(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, int nnz, const double *alpha, const hipsparseMatDescr_t descrA, const double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const double *x, const double *beta, double *y)#
hipsparseStatus_t hipsparseCcsrmv(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, int nnz, const hipComplex *alpha, const hipsparseMatDescr_t descrA, const hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const hipComplex *x, const hipComplex *beta, hipComplex *y)#
hipsparseStatus_t hipsparseZcsrmv(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, int nnz, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, const hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const hipDoubleComplex *x, const hipDoubleComplex *beta, hipDoubleComplex *y)#

Sparse matrix vector multiplication using CSR storage format.

hipsparseXcsrmv multiplies the scalar \(\alpha\) with a sparse \(m \times n\) matrix, defined in CSR storage format, and the dense vector \(x\) and adds the result to the dense vector \(y\) that is multiplied by the scalar \(\beta\), such that

\[ y := \alpha \cdot op(A) \cdot x + \beta \cdot y, \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

for(i = 0; i < m; ++i)
{
    y[i] = beta * y[i];

    for(j = csr_row_ptr[i]; j < csr_row_ptr[i + 1]; ++j)
    {
        y[i] = y[i] + alpha * csr_val[j] * x[csr_col_ind[j]];
    }
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Currently, only trans == HIPSPARSE_OPERATION_NON_TRANSPOSE is supported.

hipsparseXcsrsv2_zeroPivot()#

hipsparseStatus_t hipsparseXcsrsv2_zeroPivot(hipsparseHandle_t handle, csrsv2Info_t info, int *position)#

Sparse triangular solve using CSR storage format.

hipsparseXcsrsv2_zeroPivot returns HIPSPARSE_STATUS_ZERO_PIVOT, if either a structural or numerical zero has been found during hipsparseScsrsv2_solve(), hipsparseDcsrsv2_solve(), hipsparseCcsrsv2_solve() or hipsparseZcsrsv2_solve() computation. The first zero pivot \(j\) at \(A_{j,j}\) is stored in position, using same index base as the CSR matrix.

position can be in host or device memory. If no zero pivot has been found, position is set to -1 and HIPSPARSE_STATUS_SUCCESS is returned instead.

Note

hipsparseXcsrsv2_zeroPivot is a blocking function. It might influence performance negatively.

hipsparseXcsrsv2_bufferSize()#

hipsparseStatus_t hipsparseScsrsv2_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipsparseMatDescr_t descrA, float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDcsrsv2_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipsparseMatDescr_t descrA, double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCcsrsv2_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipsparseMatDescr_t descrA, hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZcsrsv2_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipsparseMatDescr_t descrA, hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, int *pBufferSizeInBytes)#

Sparse triangular solve using CSR storage format.

hipsparseXcsrsv2_bufferSize returns the size of the temporary storage buffer that is required by hipsparseScsrsv2_analysis(), hipsparseDcsrsv2_analysis(), hipsparseCcsrsv2_analysis(), hipsparseZcsrsv2_analysis(), hipsparseScsrsv2_solve(), hipsparseDcsrsv2_solve(), hipsparseCcsrsv2_solve() and hipsparseZcsrsv2_solve(). The temporary storage buffer must be allocated by the user.

hipsparseXcsrsv2_bufferSizeExt()#

hipsparseStatus_t hipsparseScsrsv2_bufferSizeExt(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipsparseMatDescr_t descrA, float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, size_t *pBufferSize)#
hipsparseStatus_t hipsparseDcsrsv2_bufferSizeExt(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipsparseMatDescr_t descrA, double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, size_t *pBufferSize)#
hipsparseStatus_t hipsparseCcsrsv2_bufferSizeExt(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipsparseMatDescr_t descrA, hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, size_t *pBufferSize)#
hipsparseStatus_t hipsparseZcsrsv2_bufferSizeExt(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipsparseMatDescr_t descrA, hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, size_t *pBufferSize)#

Sparse triangular solve using CSR storage format.

hipsparseXcsrsv2_bufferSizeExt returns the size of the temporary storage buffer that is required by hipsparseScsrsv2_analysis(), hipsparseDcsrsv2_analysis(), hipsparseCcsrsv2_analysis(), hipsparseZcsrsv2_analysis(), hipsparseScsrsv2_solve(), hipsparseDcsrsv2_solve(), hipsparseCcsrsv2_solve() and hipsparseZcsrsv2_solve(). The temporary storage buffer must be allocated by the user.

hipsparseXcsrsv2_analysis()#

hipsparseStatus_t hipsparseScsrsv2_analysis(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipsparseMatDescr_t descrA, const float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseDcsrsv2_analysis(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipsparseMatDescr_t descrA, const double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseCcsrsv2_analysis(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipsparseMatDescr_t descrA, const hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseZcsrsv2_analysis(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipsparseMatDescr_t descrA, const hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#

Sparse triangular solve using CSR storage format.

hipsparseXcsrsv2_analysis performs the analysis step for hipsparseScsrsv2_solve(), hipsparseDcsrsv2_solve(), hipsparseCcsrsv2_solve() and hipsparseZcsrsv2_solve().

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcsrsv2_solve()#

hipsparseStatus_t hipsparseScsrsv2_solve(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const float *alpha, const hipsparseMatDescr_t descrA, const float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, const float *f, float *x, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseDcsrsv2_solve(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const double *alpha, const hipsparseMatDescr_t descrA, const double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, const double *f, double *x, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseCcsrsv2_solve(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipComplex *alpha, const hipsparseMatDescr_t descrA, const hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, const hipComplex *f, hipComplex *x, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseZcsrsv2_solve(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int nnz, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, const hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrsv2Info_t info, const hipDoubleComplex *f, hipDoubleComplex *x, hipsparseSolvePolicy_t policy, void *pBuffer)#

Sparse triangular solve using CSR storage format.

hipsparseXcsrsv2_solve solves a sparse triangular linear system of a sparse \(m \times m\) matrix, defined in CSR storage format, a dense solution vector \(y\) and the right-hand side \(x\) that is multiplied by \(\alpha\), such that

\[ op(A) \cdot y = \alpha \cdot x, \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

hipsparseXcsrsv2_solve requires a user allocated temporary buffer. Its size is returned by hipsparseXcsrsv2_bufferSize() or hipsparseXcsrsv2_bufferSizeExt(). Furthermore, analysis meta data is required. It can be obtained by hipsparseXcsrsv2_analysis(). hipsparseXcsrsv2_solve reports the first zero pivot (either numerical or structural zero). The zero pivot status can be checked calling hipsparseXcsrsv2_zeroPivot(). If hipsparseDiagType_t == HIPSPARSE_DIAG_TYPE_UNIT, no zero pivot will be reported, even if \(A_{j,j} = 0\) for some \(j\).

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 may return before the actual computation has finished.

Note

Currently, only trans == HIPSPARSE_OPERATION_NON_TRANSPOSE and trans == HIPSPARSE_OPERATION_TRANSPOSE is supported.

hipsparseXhybmv()#

hipsparseStatus_t hipsparseShybmv(hipsparseHandle_t handle, hipsparseOperation_t transA, const float *alpha, const hipsparseMatDescr_t descrA, const hipsparseHybMat_t hybA, const float *x, const float *beta, float *y)#
hipsparseStatus_t hipsparseDhybmv(hipsparseHandle_t handle, hipsparseOperation_t transA, const double *alpha, const hipsparseMatDescr_t descrA, const hipsparseHybMat_t hybA, const double *x, const double *beta, double *y)#
hipsparseStatus_t hipsparseChybmv(hipsparseHandle_t handle, hipsparseOperation_t transA, const hipComplex *alpha, const hipsparseMatDescr_t descrA, const hipsparseHybMat_t hybA, const hipComplex *x, const hipComplex *beta, hipComplex *y)#
hipsparseStatus_t hipsparseZhybmv(hipsparseHandle_t handle, hipsparseOperation_t transA, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, const hipsparseHybMat_t hybA, const hipDoubleComplex *x, const hipDoubleComplex *beta, hipDoubleComplex *y)#

Sparse matrix vector multiplication using HYB storage format.

hipsparseXhybmv multiplies the scalar \(\alpha\) with a sparse \(m \times n\) matrix, defined in HYB storage format, and the dense vector \(x\) and adds the result to the dense vector \(y\) that is multiplied by the scalar \(\beta\), such that

\[ y := \alpha \cdot op(A) \cdot x + \beta \cdot y, \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Currently, only trans == HIPSPARSE_OPERATION_NON_TRANSPOSE is supported.

hipsparseXbsrmv()#

hipsparseStatus_t hipsparseSbsrmv(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nb, int nnzb, const float *alpha, const hipsparseMatDescr_t descrA, const float *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, const float *x, const float *beta, float *y)#
hipsparseStatus_t hipsparseDbsrmv(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nb, int nnzb, const double *alpha, const hipsparseMatDescr_t descrA, const double *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, const double *x, const double *beta, double *y)#
hipsparseStatus_t hipsparseCbsrmv(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nb, int nnzb, const hipComplex *alpha, const hipsparseMatDescr_t descrA, const hipComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, const hipComplex *x, const hipComplex *beta, hipComplex *y)#
hipsparseStatus_t hipsparseZbsrmv(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nb, int nnzb, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, const hipDoubleComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, const hipDoubleComplex *x, const hipDoubleComplex *beta, hipDoubleComplex *y)#

Sparse matrix vector multiplication using BSR storage format.

hipsparseXbsrmv multiplies the scalar \(\alpha\) with a sparse \((mb \cdot \text{block_dim}) \times (nb \cdot \text{block_dim})\) matrix, defined in BSR storage format, and the dense vector \(x\) and adds the result to the dense vector \(y\) that is multiplied by the scalar \(\beta\), such that

\[ y := \alpha \cdot op(A) \cdot x + \beta \cdot y, \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Currently, only trans == HIPSPARSE_OPERATION_NON_TRANSPOSE is supported.

hipsparseXbsrxmv()#

hipsparseStatus_t hipsparseSbsrxmv(hipsparseHandle_t handle, hipsparseDirection_t dir, hipsparseOperation_t trans, int sizeOfMask, int mb, int nb, int nnzb, const float *alpha, const hipsparseMatDescr_t descr, const float *bsrVal, const int *bsrMaskPtr, const int *bsrRowPtr, const int *bsrEndPtr, const int *bsrColInd, int blockDim, const float *x, const float *beta, float *y)#
hipsparseStatus_t hipsparseDbsrxmv(hipsparseHandle_t handle, hipsparseDirection_t dir, hipsparseOperation_t trans, int sizeOfMask, int mb, int nb, int nnzb, const double *alpha, const hipsparseMatDescr_t descr, const double *bsrVal, const int *bsrMaskPtr, const int *bsrRowPtr, const int *bsrEndPtr, const int *bsrColInd, int blockDim, const double *x, const double *beta, double *y)#
hipsparseStatus_t hipsparseCbsrxmv(hipsparseHandle_t handle, hipsparseDirection_t dir, hipsparseOperation_t trans, int sizeOfMask, int mb, int nb, int nnzb, const hipComplex *alpha, const hipsparseMatDescr_t descr, const hipComplex *bsrVal, const int *bsrMaskPtr, const int *bsrRowPtr, const int *bsrEndPtr, const int *bsrColInd, int blockDim, const hipComplex *x, const hipComplex *beta, hipComplex *y)#
hipsparseStatus_t hipsparseZbsrxmv(hipsparseHandle_t handle, hipsparseDirection_t dir, hipsparseOperation_t trans, int sizeOfMask, int mb, int nb, int nnzb, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descr, const hipDoubleComplex *bsrVal, const int *bsrMaskPtr, const int *bsrRowPtr, const int *bsrEndPtr, const int *bsrColInd, int blockDim, const hipDoubleComplex *x, const hipDoubleComplex *beta, hipDoubleComplex *y)#

Sparse matrix vector multiplication with mask operation using BSR storage format.

hipsparseXbsrxmv multiplies the scalar \(\alpha\) with a sparse \((mb \cdot \text{block_dim}) \times (nb \cdot \text{block_dim})\) modified matrix, defined in BSR storage format, and the dense vector \(x\) and adds the result to the dense vector \(y\) that is multiplied by the scalar \(\beta\), such that

\[ y := \left( \alpha \cdot op(A) \cdot x + \beta \cdot y \right)\left( \text{mask} \right), \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

The \(\text{mask}\) is defined as an array of block row indices. The input sparse matrix is defined with a modified BSR storage format where the beginning and the end of each row is defined with two arrays, bsr_row_ptr and bsr_end_ptr (both of size mb), rather the usual bsr_row_ptr of size mb + 1.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Currently, only trans == HIPSPARSE_OPERATION_NON_TRANSPOSE is supported. Currently, block_dim == 1 is not supported.

hipsparseXbsrsv2_zeroPivot()#

hipsparseStatus_t hipsparseXbsrsv2_zeroPivot(hipsparseHandle_t handle, bsrsv2Info_t info, int *position)#

Sparse triangular solve using BSR storage format.

hipsparseXbsrsv2_zeroPivot returns HIPSPARSE_STATUS_ZERO_PIVOT, if either a structural or numerical zero has been found during hipsparseXbsrsv2_analysis() or hipsparseXbsrsv2_solve() computation. The first zero pivot \(j\) at \(A_{j,j}\) is stored in position, using same index base as the BSR matrix.

position can be in host or device memory. If no zero pivot has been found, position is set to -1 and HIPSPARSE_STATUS_SUCCESS is returned instead.

Note

hipsparseXbsrsv2_zeroPivot is a blocking function. It might influence performance negatively.

hipsparseXbsrsv2_bufferSize()#

hipsparseStatus_t hipsparseSbsrsv2_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipsparseMatDescr_t descrA, float *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDbsrsv2_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipsparseMatDescr_t descrA, double *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCbsrsv2_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZbsrsv2_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipDoubleComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, int *pBufferSizeInBytes)#

Sparse triangular solve using BSR storage format.

hipsparseXbsrsv2_bufferSize returns the size of the temporary storage buffer that is required by hipsparseXbsrsv2_analysis() and hipsparseXbsrsv2_solve(). The temporary storage buffer must be allocated by the user.

hipsparseXbsrsv2_bufferSizeExt()#

hipsparseStatus_t hipsparseSbsrsv2_bufferSizeExt(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipsparseMatDescr_t descrA, float *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, size_t *pBufferSize)#
hipsparseStatus_t hipsparseDbsrsv2_bufferSizeExt(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipsparseMatDescr_t descrA, double *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, size_t *pBufferSize)#
hipsparseStatus_t hipsparseCbsrsv2_bufferSizeExt(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, size_t *pBufferSize)#
hipsparseStatus_t hipsparseZbsrsv2_bufferSizeExt(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipDoubleComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, size_t *pBufferSize)#

Sparse triangular solve using BSR storage format.

hipsparseXbsrsv2_bufferSizeExt returns the size of the temporary storage buffer that is required by hipsparseXbsrsv2_analysis() and hipsparseXbsrsv2_solve(). The temporary storage buffer must be allocated by the user.

hipsparseXbsrsv2_analysis()#

hipsparseStatus_t hipsparseSbsrsv2_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipsparseMatDescr_t descrA, const float *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseDbsrsv2_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipsparseMatDescr_t descrA, const double *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseCbsrsv2_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipsparseMatDescr_t descrA, const hipComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseZbsrsv2_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipsparseMatDescr_t descrA, const hipDoubleComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#

Sparse triangular solve using BSR storage format.

hipsparseXbsrsv2_analysis performs the analysis step for hipsparseXbsrsv2_solve().

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 may return before the actual computation has finished.

hipsparseXbsrsv2_solve()#

hipsparseStatus_t hipsparseSbsrsv2_solve(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const float *alpha, const hipsparseMatDescr_t descrA, const float *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, const float *f, float *x, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseDbsrsv2_solve(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const double *alpha, const hipsparseMatDescr_t descrA, const double *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, const double *f, double *x, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseCbsrsv2_solve(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipComplex *alpha, const hipsparseMatDescr_t descrA, const hipComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, const hipComplex *f, hipComplex *x, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseZbsrsv2_solve(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, int mb, int nnzb, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, const hipDoubleComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsv2Info_t info, const hipDoubleComplex *f, hipDoubleComplex *x, hipsparseSolvePolicy_t policy, void *pBuffer)#

Sparse triangular solve using BSR storage format.

hipsparseXbsrsv2_solve solves a sparse triangular linear system of a sparse \(m \times m\) matrix, defined in BSR storage format, a dense solution vector \(y\) and the right-hand side \(x\) that is multiplied by \(\alpha\), such that

\[ op(A) \cdot y = \alpha \cdot x, \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

hipsparseXbsrsv2_solve requires a user allocated temporary buffer. Its size is returned by hipsparseXbsrsv2_bufferSize() or hipsparseXbsrsv2_bufferSizeExt(). Furthermore, analysis meta data is required. It can be obtained by hipsparseXbsrsv2_analysis(). hipsparseXbsrsv2_solve reports the first zero pivot (either numerical or structural zero). The zero pivot status can be checked calling hipsparseXbsrsv2_zeroPivot(). If hipsparseDiagType_t == HIPSPARSE_DIAG_TYPE_UNIT, no zero pivot will be reported, even if \(A_{j,j} = 0\) for some \(j\).

Note

The sparse BSR matrix has to be sorted.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Currently, only trans == HIPSPARSE_OPERATION_NON_TRANSPOSE and trans == HIPSPARSE_OPERATION_TRANSPOSE is supported.

hipsparseXgemvi_bufferSize()#

hipsparseStatus_t hipsparseSgemvi_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, int nnz, int *pBufferSize)#
hipsparseStatus_t hipsparseDgemvi_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, int nnz, int *pBufferSize)#
hipsparseStatus_t hipsparseCgemvi_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, int nnz, int *pBufferSize)#
hipsparseStatus_t hipsparseZgemvi_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, int nnz, int *pBufferSize)#

Dense matrix sparse vector multiplication.

hipsparseXgemvi_bufferSize returns the size of the temporary storage buffer required by hipsparseXgemvi(). The temporary storage buffer must be allocated by the user.

hipsparseXgemvi()#

hipsparseStatus_t hipsparseSgemvi(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, const float *alpha, const float *A, int lda, int nnz, const float *x, const int *xInd, const float *beta, float *y, hipsparseIndexBase_t idxBase, void *pBuffer)#
hipsparseStatus_t hipsparseDgemvi(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, const double *alpha, const double *A, int lda, int nnz, const double *x, const int *xInd, const double *beta, double *y, hipsparseIndexBase_t idxBase, void *pBuffer)#
hipsparseStatus_t hipsparseCgemvi(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, const hipComplex *alpha, const hipComplex *A, int lda, int nnz, const hipComplex *x, const int *xInd, const hipComplex *beta, hipComplex *y, hipsparseIndexBase_t idxBase, void *pBuffer)#
hipsparseStatus_t hipsparseZgemvi(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, const hipDoubleComplex *alpha, const hipDoubleComplex *A, int lda, int nnz, const hipDoubleComplex *x, const int *xInd, const hipDoubleComplex *beta, hipDoubleComplex *y, hipsparseIndexBase_t idxBase, void *pBuffer)#

Dense matrix sparse vector multiplication.

hipsparseXgemvi multiplies the scalar \(\alpha\) with a dense \(m \times n\) matrix \(A\) and the sparse vector \(x\) and adds the result to the dense vector \(y\) that is multiplied by the scalar \(\beta\), such that

\[ y := \alpha \cdot op(A) \cdot x + \beta \cdot y, \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

hipsparseXgemvi requires a user allocated temporary buffer. Its size is returned by hipsparseXgemvi_bufferSize().

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Currently, only trans == HIPSPARSE_OPERATION_NON_TRANSPOSE is supported.

Sparse Level 3 Functions#

This module holds all sparse level 3 routines.

The sparse level 3 routines describe operations between a matrix in sparse format and multiple vectors in dense format that can also be seen as a dense matrix.

hipsparseXbsrmm()#

hipsparseStatus_t hipsparseSbsrmm(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, hipsparseOperation_t transB, int mb, int n, int kb, int nnzb, const float *alpha, const hipsparseMatDescr_t descrA, const float *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, const float *B, int ldb, const float *beta, float *C, int ldc)#
hipsparseStatus_t hipsparseDbsrmm(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, hipsparseOperation_t transB, int mb, int n, int kb, int nnzb, const double *alpha, const hipsparseMatDescr_t descrA, const double *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, const double *B, int ldb, const double *beta, double *C, int ldc)#
hipsparseStatus_t hipsparseCbsrmm(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, hipsparseOperation_t transB, int mb, int n, int kb, int nnzb, const hipComplex *alpha, const hipsparseMatDescr_t descrA, const hipComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, const hipComplex *B, int ldb, const hipComplex *beta, hipComplex *C, int ldc)#
hipsparseStatus_t hipsparseZbsrmm(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, hipsparseOperation_t transB, int mb, int n, int kb, int nnzb, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, const hipDoubleComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, const hipDoubleComplex *B, int ldb, const hipDoubleComplex *beta, hipDoubleComplex *C, int ldc)#

Sparse matrix dense matrix multiplication using BSR storage format.

hipsparseXbsrmm multiplies the scalar \(\alpha\) with a sparse \(mb \times kb\) matrix \(A\), defined in BSR storage format, and the dense \(k \times n\) matrix \(B\) (where \(k = block\_dim \times kb\)) and adds the result to the dense \(m \times n\) matrix \(C\) (where \(m = block\_dim \times mb\)) that is multiplied by the scalar \(\beta\), such that

\[ C := \alpha \cdot op(A) \cdot op(B) + \beta \cdot C, \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans_A == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ \end{array} \right. \end{split}\]
and
\[\begin{split} op(B) = \left\{ \begin{array}{ll} B, & \text{if trans_B == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ B^T, & \text{if trans_B == HIPSPARSE_OPERATION_TRANSPOSE} \\ \end{array} \right. \end{split}\]

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Currently, only trans_A == HIPSPARSE_OPERATION_NON_TRANSPOSE is supported.

hipsparseXcsrmm()#

hipsparseStatus_t hipsparseScsrmm(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, int k, int nnz, const float *alpha, const hipsparseMatDescr_t descrA, const float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const float *B, int ldb, const float *beta, float *C, int ldc)#
hipsparseStatus_t hipsparseDcsrmm(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, int k, int nnz, const double *alpha, const hipsparseMatDescr_t descrA, const double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const double *B, int ldb, const double *beta, double *C, int ldc)#
hipsparseStatus_t hipsparseCcsrmm(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, int k, int nnz, const hipComplex *alpha, const hipsparseMatDescr_t descrA, const hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const hipComplex *B, int ldb, const hipComplex *beta, hipComplex *C, int ldc)#
hipsparseStatus_t hipsparseZcsrmm(hipsparseHandle_t handle, hipsparseOperation_t transA, int m, int n, int k, int nnz, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, const hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const hipDoubleComplex *B, int ldb, const hipDoubleComplex *beta, hipDoubleComplex *C, int ldc)#

Sparse matrix dense matrix multiplication using CSR storage format.

hipsparseXcsrmm multiplies the scalar \(\alpha\) with a sparse \(m \times k\) matrix \(A\), defined in CSR storage format, and the dense \(k \times n\) matrix \(B\) and adds the result to the dense \(m \times n\) matrix \(C\) that is multiplied by the scalar \(\beta\), such that

\[ C := \alpha \cdot op(A) \cdot B + \beta \cdot C, \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans_A == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans_A == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans_A == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

for(i = 0; i < ldc; ++i)
{
    for(j = 0; j < n; ++j)
    {
        C[i][j] = beta * C[i][j];

        for(k = csr_row_ptr[i]; k < csr_row_ptr[i + 1]; ++k)
        {
            C[i][j] += alpha * csr_val[k] * B[csr_col_ind[k]][j];
        }
    }
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcsrmm2()#

hipsparseStatus_t hipsparseScsrmm2(hipsparseHandle_t handle, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int n, int k, int nnz, const float *alpha, const hipsparseMatDescr_t descrA, const float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const float *B, int ldb, const float *beta, float *C, int ldc)#
hipsparseStatus_t hipsparseDcsrmm2(hipsparseHandle_t handle, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int n, int k, int nnz, const double *alpha, const hipsparseMatDescr_t descrA, const double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const double *B, int ldb, const double *beta, double *C, int ldc)#
hipsparseStatus_t hipsparseCcsrmm2(hipsparseHandle_t handle, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int n, int k, int nnz, const hipComplex *alpha, const hipsparseMatDescr_t descrA, const hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const hipComplex *B, int ldb, const hipComplex *beta, hipComplex *C, int ldc)#
hipsparseStatus_t hipsparseZcsrmm2(hipsparseHandle_t handle, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int n, int k, int nnz, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, const hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const hipDoubleComplex *B, int ldb, const hipDoubleComplex *beta, hipDoubleComplex *C, int ldc)#

Sparse matrix dense matrix multiplication using CSR storage format.

hipsparseXcsrmm2 multiplies the scalar \(\alpha\) with a sparse \(m \times k\) matrix \(A\), defined in CSR storage format, and the dense \(k \times n\) matrix \(B\) and adds the result to the dense \(m \times n\) matrix \(C\) that is multiplied by the scalar \(\beta\), such that

\[ C := \alpha \cdot op(A) \cdot op(B) + \beta \cdot C, \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans_A == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans_A == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans_A == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]
and
\[\begin{split} op(B) = \left\{ \begin{array}{ll} B, & \text{if trans_B == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ B^T, & \text{if trans_B == HIPSPARSE_OPERATION_TRANSPOSE} \\ B^H, & \text{if trans_B == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

for(i = 0; i < ldc; ++i)
{
    for(j = 0; j < n; ++j)
    {
        C[i][j] = beta * C[i][j];

        for(k = csr_row_ptr[i]; k < csr_row_ptr[i + 1]; ++k)
        {
            C[i][j] += alpha * csr_val[k] * B[csr_col_ind[k]][j];
        }
    }
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXbsrsm2_zeroPivot()#

hipsparseStatus_t hipsparseXbsrsm2_zeroPivot(hipsparseHandle_t handle, bsrsm2Info_t info, int *position)#

Sparse triangular system solve using BSR storage format.

hipsparseXbsrsm2_zeroPivot returns HIPSPARSE_STATUS_ZERO_PIVOT, if either a structural or numerical zero has been found during hipsparseXbsrsm2_analysis() or hipsparseXbsrsm2_solve() computation. The first zero pivot \(j\) at \(A_{j,j}\) is stored in position, using same index base as the BSR matrix.

position can be in host or device memory. If no zero pivot has been found, position is set to -1 and HIPSPARSE_STATUS_SUCCESS is returned instead.

Note

hipsparseXbsrsm2_zeroPivot is a blocking function. It might influence performance negatively.

hipsparseXbsrsm2_bufferSize()#

hipsparseStatus_t hipsparseSbsrsm2_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, hipsparseOperation_t transX, int mb, int nrhs, int nnzb, const hipsparseMatDescr_t descrA, float *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsm2Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDbsrsm2_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, hipsparseOperation_t transX, int mb, int nrhs, int nnzb, const hipsparseMatDescr_t descrA, double *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsm2Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCbsrsm2_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, hipsparseOperation_t transX, int mb, int nrhs, int nnzb, const hipsparseMatDescr_t descrA, hipComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsm2Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZbsrsm2_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, hipsparseOperation_t transX, int mb, int nrhs, int nnzb, const hipsparseMatDescr_t descrA, hipDoubleComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsm2Info_t info, int *pBufferSizeInBytes)#

Sparse triangular system solve using BSR storage format.

hipsparseXbsrsm2_buffer_size returns the size of the temporary storage buffer that is required by hipsparseXbsrsm2_analysis() and hipsparseXbsrsm2_solve(). The temporary storage buffer must be allocated by the user.

hipsparseXbsrsm2_analysis()#

hipsparseStatus_t hipsparseSbsrsm2_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, hipsparseOperation_t transX, int mb, int nrhs, int nnzb, const hipsparseMatDescr_t descrA, const float *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsm2Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseDbsrsm2_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, hipsparseOperation_t transX, int mb, int nrhs, int nnzb, const hipsparseMatDescr_t descrA, const double *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsm2Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseCbsrsm2_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, hipsparseOperation_t transX, int mb, int nrhs, int nnzb, const hipsparseMatDescr_t descrA, const hipComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsm2Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseZbsrsm2_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, hipsparseOperation_t transA, hipsparseOperation_t transX, int mb, int nrhs, int nnzb, const hipsparseMatDescr_t descrA, const hipDoubleComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrsm2Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#

Sparse triangular system solve using BSR storage format.

hipsparseXbsrsm2_analysis performs the analysis step for hipsparseXbsrsm2_solve().

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 may return before the actual computation has finished.

hipsparseXbsrsm2_solve()#

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)#
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)#
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)#
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)#

Sparse triangular system solve using BSR storage format.

hipsparseXbsrsm2_solve solves a sparse triangular linear system of a sparse \(m \times m\) matrix, defined in BSR storage format, a dense solution matrix \(X\) and the right-hand side matrix \(B\) that is multiplied by \(\alpha\), such that

\[ op(A) \cdot op(X) = \alpha \cdot op(B), \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans_A == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans_A == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans_A == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]
,
\[\begin{split} op(X) = \left\{ \begin{array}{ll} X, & \text{if trans_X == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ X^T, & \text{if trans_X == HIPSPARSE_OPERATION_TRANSPOSE} \\ X^H, & \text{if trans_X == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

hipsparseXbsrsm2_solve requires a user allocated temporary buffer. Its size is returned by hipsparseXbsrsm2_bufferSize(). Furthermore, analysis meta data is required. It can be obtained by hipsparseXbsrsm2_analysis(). hipsparseXbsrsm2_solve reports the first zero pivot (either numerical or structural zero). The zero pivot status can be checked calling hipsparseXbsrsm2_zeroPivot(). If hipsparseDiagType_t == HIPSPARSE_DIAG_TYPE_UNIT, no zero pivot will be reported, even if \(A_{j,j} = 0\) for some \(j\).

Note

The sparse BSR matrix has to be sorted.

Note

Operation type of B and X must match, if \(op(B)=B, op(X)=X\).

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Currently, only trans_A != HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE and trans_X != HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE is supported.

hipsparseXcsrsm2_zeroPivot()#

hipsparseStatus_t hipsparseXcsrsm2_zeroPivot(hipsparseHandle_t handle, csrsm2Info_t info, int *position)#

Sparse triangular system solve using CSR storage format.

hipsparseXcsrsm2_zeroPivot returns HIPSPARSE_STATUS_ZERO_PIVOT, if either a structural or numerical zero has been found during hipsparseXcsrsm2_analysis() or hipsparseXcsrsm2_solve() computation. The first zero pivot \(j\) at \(A_{j,j}\) is stored in position, using same index base as the CSR matrix.

position can be in host or device memory. If no zero pivot has been found, position is set to -1 and HIPSPARSE_STATUS_SUCCESS is returned instead.

Note

hipsparseXcsrsm2_zeroPivot is a blocking function. It might influence performance negatively.

hipsparseXcsrsm2_bufferSizeExt()#

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 *pBufferSize)#
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 *pBufferSize)#
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 *pBufferSize)#
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 *pBufferSize)#

Sparse triangular system solve using BSR storage format.

hipsparseXbsrsm2_solve solves a sparse triangular linear system of a sparse \(m \times m\) matrix, defined in BSR storage format, a dense solution matrix \(X\) and the right-hand side matrix \(B\) that is multiplied by \(\alpha\), such that

\[ op(A) \cdot op(X) = \alpha \cdot op(B), \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans_A == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans_A == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans_A == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]
,
\[\begin{split} op(X) = \left\{ \begin{array}{ll} X, & \text{if trans_X == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ X^T, & \text{if trans_X == HIPSPARSE_OPERATION_TRANSPOSE} \\ X^H, & \text{if trans_X == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

hipsparseXbsrsm2_solve requires a user allocated temporary buffer. Its size is returned by hipsparseXbsrsm2_bufferSize(). Furthermore, analysis meta data is required. It can be obtained by hipsparseXbsrsm2_analysis(). hipsparseXbsrsm2_solve reports the first zero pivot (either numerical or structural zero). The zero pivot status can be checked calling hipsparseXbsrsm2_zeroPivot(). If hipsparseDiagType_t == HIPSPARSE_DIAG_TYPE_UNIT, no zero pivot will be reported, even if \(A_{j,j} = 0\) for some \(j\).

Note

The sparse BSR matrix has to be sorted.

Note

Operation type of B and X must match, if \(op(B)=B, op(X)=X\).

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Currently, only trans_A != HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE and trans_X != HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE is supported.

hipsparseXcsrsm2_analysis()#

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)#
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)#
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)#
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)#

Sparse triangular system solve using CSR storage format.

hipsparseXcsrsm2_analysis performs the analysis step for hipsparseXcsrsm2_solve().

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 may return before the actual computation has finished.

hipsparseXcsrsm2_solve()#

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)#
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)#
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)#
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)#

Sparse triangular system solve using CSR storage format.

hipsparseXcsrsm2_solve solves a sparse triangular linear system of a sparse \(m \times m\) matrix, defined in CSR storage format, a dense solution matrix \(X\) and the right-hand side matrix \(B\) that is multiplied by \(\alpha\), such that

\[ op(A) \cdot op(X) = \alpha \cdot op(B), \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans_A == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans_A == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans_A == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]
,
\[\begin{split} op(B) = \left\{ \begin{array}{ll} B, & \text{if trans_B == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ B^T, & \text{if trans_B == HIPSPARSE_OPERATION_TRANSPOSE} \\ B^H, & \text{if trans_B == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]
and
\[\begin{split} op(X) = \left\{ \begin{array}{ll} X, & \text{if trans_B == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ X^T, & \text{if trans_B == HIPSPARSE_OPERATION_TRANSPOSE} \\ X^H, & \text{if trans_B == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

hipsparseXcsrsm2_solve requires a user allocated temporary buffer. Its size is returned by hipsparseXcsrsm2_bufferSizeExt(). Furthermore, analysis meta data is required. It can be obtained by hipsparseXcsrsm2_analysis(). hipsparseXcsrsm2_solve reports the first zero pivot (either numerical or structural zero). The zero pivot status can be checked calling hipsparseXcsrsm2_zeroPivot(). If hipsparseDiagType_t == HIPSPARSE_DIAG_TYPE_UNIT, no zero pivot will be reported, even if \(A_{j,j} = 0\) for some \(j\).

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 may return before the actual computation has finished.

Note

Currently, only trans_A != HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE and trans_B != HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE is supported.

hipsparseXgemmi()#

hipsparseStatus_t hipsparseSgemmi(hipsparseHandle_t handle, int m, int n, int k, int nnz, const float *alpha, const float *A, int lda, const float *cscValB, const int *cscColPtrB, const int *cscRowIndB, const float *beta, float *C, int ldc)#
hipsparseStatus_t hipsparseDgemmi(hipsparseHandle_t handle, int m, int n, int k, int nnz, const double *alpha, const double *A, int lda, const double *cscValB, const int *cscColPtrB, const int *cscRowIndB, const double *beta, double *C, int ldc)#
hipsparseStatus_t hipsparseCgemmi(hipsparseHandle_t handle, int m, int n, int k, int nnz, const hipComplex *alpha, const hipComplex *A, int lda, const hipComplex *cscValB, const int *cscColPtrB, const int *cscRowIndB, const hipComplex *beta, hipComplex *C, int ldc)#
hipsparseStatus_t hipsparseZgemmi(hipsparseHandle_t handle, int m, int n, int k, int nnz, const hipDoubleComplex *alpha, const hipDoubleComplex *A, int lda, const hipDoubleComplex *cscValB, const int *cscColPtrB, const int *cscRowIndB, const hipDoubleComplex *beta, hipDoubleComplex *C, int ldc)#

Dense matrix sparse matrix multiplication using CSR storage format.

hipsparseXgemmi multiplies the scalar \(\alpha\) with a dense \(m \times k\) matrix \(A\) and the sparse \(k \times n\) matrix \(B\), defined in CSR storage format and adds the result to the dense \(m \times n\) matrix \(C\) that is multiplied by the scalar \(\beta\), such that

\[ C := \alpha \cdot op(A) \cdot op(B) + \beta \cdot C \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans_A == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans_A == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans_A == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]
and
\[\begin{split} op(B) = \left\{ \begin{array}{ll} B, & \text{if trans_B == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ B^T, & \text{if trans_B == HIPSPARSE_OPERATION_TRANSPOSE} \\ B^H, & \text{if trans_B == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Sparse Extra Functions#

This module holds all sparse extra routines.

The sparse extra routines describe operations that manipulate sparse matrices.

hipsparseXcsrgeamNnz()#

hipsparseStatus_t hipsparseXcsrgeamNnz(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descrA, int nnzA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const int *csrRowPtrB, const int *csrColIndB, const hipsparseMatDescr_t descrC, int *csrRowPtrC, int *nnzTotalDevHostPtr)#

Sparse matrix sparse matrix addition using CSR storage format.

hipsparseXcsrgeamNnz computes the total CSR non-zero elements and the CSR row offsets, that point to the start of every row of the sparse CSR matrix, of the resulting matrix C. It is assumed that csr_row_ptr_C has been allocated with size m + 1.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Currently, only HIPSPARSE_MATRIX_TYPE_GENERAL is supported.

hipsparseXcsrgeam()#

hipsparseStatus_t hipsparseScsrgeam(hipsparseHandle_t handle, int m, int n, const float *alpha, const hipsparseMatDescr_t descrA, int nnzA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, const float *beta, const hipsparseMatDescr_t descrB, int nnzB, const float *csrValB, const int *csrRowPtrB, const int *csrColIndB, const hipsparseMatDescr_t descrC, float *csrValC, int *csrRowPtrC, int *csrColIndC)#
hipsparseStatus_t hipsparseDcsrgeam(hipsparseHandle_t handle, int m, int n, const double *alpha, const hipsparseMatDescr_t descrA, int nnzA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, const double *beta, const hipsparseMatDescr_t descrB, int nnzB, const double *csrValB, const int *csrRowPtrB, const int *csrColIndB, const hipsparseMatDescr_t descrC, double *csrValC, int *csrRowPtrC, int *csrColIndC)#
hipsparseStatus_t hipsparseCcsrgeam(hipsparseHandle_t handle, int m, int n, const hipComplex *alpha, const hipsparseMatDescr_t descrA, int nnzA, const hipComplex *csrValA, const int *csrRowPtrA, const int *csrColIndA, const hipComplex *beta, const hipsparseMatDescr_t descrB, int nnzB, const hipComplex *csrValB, const int *csrRowPtrB, const int *csrColIndB, const hipsparseMatDescr_t descrC, hipComplex *csrValC, int *csrRowPtrC, int *csrColIndC)#
hipsparseStatus_t hipsparseZcsrgeam(hipsparseHandle_t handle, int m, int n, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, int nnzA, const hipDoubleComplex *csrValA, const int *csrRowPtrA, const int *csrColIndA, const hipDoubleComplex *beta, const hipsparseMatDescr_t descrB, int nnzB, const hipDoubleComplex *csrValB, const int *csrRowPtrB, const int *csrColIndB, const hipsparseMatDescr_t descrC, hipDoubleComplex *csrValC, int *csrRowPtrC, int *csrColIndC)#

Sparse matrix sparse matrix addition using CSR storage format.

hipsparseXcsrgeam multiplies the scalar \(\alpha\) with the sparse \(m \times n\) matrix \(A\), defined in CSR storage format, multiplies the scalar \(\beta\) with the sparse \(m \times n\) matrix \(B\), defined in CSR storage format, and adds both resulting matrices to obtain the sparse \(m \times n\) matrix \(C\), defined in CSR storage format, such that

\[ C := \alpha \cdot A + \beta \cdot B. \]

It is assumed that csr_row_ptr_C has already been filled and that csr_val_C and csr_col_ind_C are allocated by the user. csr_row_ptr_C and allocation size of csr_col_ind_C and csr_val_C is defined by the number of non-zero elements of the sparse CSR matrix C. Both can be obtained by hipsparseXcsrgeamNnz().

Note

Both scalars \(\alpha\) and \(beta\) have to be valid.

Note

Currently, only HIPSPARSE_MATRIX_TYPE_GENERAL is supported.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcsrgeam2_bufferSizeExt()#

hipsparseStatus_t hipsparseScsrgeam2_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const float *alpha, const hipsparseMatDescr_t descrA, int nnzA, const float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const float *beta, const hipsparseMatDescr_t descrB, int nnzB, const float *csrSortedValB, const int *csrSortedRowPtrB, const int *csrSortedColIndB, const hipsparseMatDescr_t descrC, const float *csrSortedValC, const int *csrSortedRowPtrC, const int *csrSortedColIndC, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDcsrgeam2_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const double *alpha, const hipsparseMatDescr_t descrA, int nnzA, const double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const double *beta, const hipsparseMatDescr_t descrB, int nnzB, const double *csrSortedValB, const int *csrSortedRowPtrB, const int *csrSortedColIndB, const hipsparseMatDescr_t descrC, const double *csrSortedValC, const int *csrSortedRowPtrC, const int *csrSortedColIndC, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCcsrgeam2_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const hipComplex *alpha, const hipsparseMatDescr_t descrA, int nnzA, const hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const hipComplex *beta, const hipsparseMatDescr_t descrB, int nnzB, const hipComplex *csrSortedValB, const int *csrSortedRowPtrB, const int *csrSortedColIndB, const hipsparseMatDescr_t descrC, const hipComplex *csrSortedValC, const int *csrSortedRowPtrC, const int *csrSortedColIndC, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZcsrgeam2_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, int nnzA, const hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const hipDoubleComplex *beta, const hipsparseMatDescr_t descrB, int nnzB, const hipDoubleComplex *csrSortedValB, const int *csrSortedRowPtrB, const int *csrSortedColIndB, const hipsparseMatDescr_t descrC, const hipDoubleComplex *csrSortedValC, const int *csrSortedRowPtrC, const int *csrSortedColIndC, size_t *pBufferSizeInBytes)#

Sparse matrix sparse matrix multiplication using CSR storage format.

hipsparseXcsrgeam2_bufferSizeExt returns the size of the temporary storage buffer that is required by hipsparseXcsrgeam2Nnz() and hipsparseXcsrgeam2(). The temporary storage buffer must be allocated by the user.

Note

Currently, only HIPSPARSE_MATRIX_TYPE_GENERAL is supported.

hipsparseXcsrgeam2Nnz()#

hipsparseStatus_t hipsparseXcsrgeam2Nnz(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descrA, int nnzA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const hipsparseMatDescr_t descrB, int nnzB, const int *csrSortedRowPtrB, const int *csrSortedColIndB, const hipsparseMatDescr_t descrC, int *csrSortedRowPtrC, int *nnzTotalDevHostPtr, void *workspace)#

Sparse matrix sparse matrix addition using CSR storage format.

hipsparseXcsrgeam2Nnz computes the total CSR non-zero elements and the CSR row offsets, that point to the start of every row of the sparse CSR matrix, of the resulting matrix C. It is assumed that csr_row_ptr_C has been allocated with size m + 1.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Currently, only HIPSPARSE_MATRIX_TYPE_GENERAL is supported.

hipsparseXcsrgeam2()#

hipsparseStatus_t hipsparseScsrgeam2(hipsparseHandle_t handle, int m, int n, const float *alpha, const hipsparseMatDescr_t descrA, int nnzA, const float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const float *beta, const hipsparseMatDescr_t descrB, int nnzB, const float *csrSortedValB, const int *csrSortedRowPtrB, const int *csrSortedColIndB, const hipsparseMatDescr_t descrC, float *csrSortedValC, int *csrSortedRowPtrC, int *csrSortedColIndC, void *pBuffer)#
hipsparseStatus_t hipsparseDcsrgeam2(hipsparseHandle_t handle, int m, int n, const double *alpha, const hipsparseMatDescr_t descrA, int nnzA, const double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const double *beta, const hipsparseMatDescr_t descrB, int nnzB, const double *csrSortedValB, const int *csrSortedRowPtrB, const int *csrSortedColIndB, const hipsparseMatDescr_t descrC, double *csrSortedValC, int *csrSortedRowPtrC, int *csrSortedColIndC, void *pBuffer)#
hipsparseStatus_t hipsparseCcsrgeam2(hipsparseHandle_t handle, int m, int n, const hipComplex *alpha, const hipsparseMatDescr_t descrA, int nnzA, const hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const hipComplex *beta, const hipsparseMatDescr_t descrB, int nnzB, const hipComplex *csrSortedValB, const int *csrSortedRowPtrB, const int *csrSortedColIndB, const hipsparseMatDescr_t descrC, hipComplex *csrSortedValC, int *csrSortedRowPtrC, int *csrSortedColIndC, void *pBuffer)#
hipsparseStatus_t hipsparseZcsrgeam2(hipsparseHandle_t handle, int m, int n, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, int nnzA, const hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, const hipDoubleComplex *beta, const hipsparseMatDescr_t descrB, int nnzB, const hipDoubleComplex *csrSortedValB, const int *csrSortedRowPtrB, const int *csrSortedColIndB, const hipsparseMatDescr_t descrC, hipDoubleComplex *csrSortedValC, int *csrSortedRowPtrC, int *csrSortedColIndC, void *pBuffer)#

Sparse matrix sparse matrix addition using CSR storage format.

hipsparseXcsrgeam2 multiplies the scalar \(\alpha\) with the sparse \(m \times n\) matrix \(A\), defined in CSR storage format, multiplies the scalar \(\beta\) with the sparse \(m \times n\) matrix \(B\), defined in CSR storage format, and adds both resulting matrices to obtain the sparse \(m \times n\) matrix \(C\), defined in CSR storage format, such that

\[ C := \alpha \cdot A + \beta \cdot B. \]

It is assumed that csr_row_ptr_C has already been filled and that csr_val_C and csr_col_ind_C are allocated by the user. csr_row_ptr_C and allocation size of csr_col_ind_C and csr_val_C is defined by the number of non-zero elements of the sparse CSR matrix C. Both can be obtained by hipsparseXcsrgeam2Nnz().

Note

Both scalars \(\alpha\) and \(beta\) have to be valid.

Note

Currently, only HIPSPARSE_MATRIX_TYPE_GENERAL is supported.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcsrgemmNnz()#

hipsparseStatus_t hipsparseXcsrgemmNnz(hipsparseHandle_t handle, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int n, int k, const hipsparseMatDescr_t descrA, int nnzA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const int *csrRowPtrB, const int *csrColIndB, const hipsparseMatDescr_t descrC, int *csrRowPtrC, int *nnzTotalDevHostPtr)#

Sparse matrix sparse matrix multiplication using CSR storage format.

hipsparseXcsrgemmNnz computes the total CSR non-zero elements and the CSR row offsets, that point to the start of every row of the sparse CSR matrix, of the resulting multiplied matrix C. It is assumed that csr_row_ptr_C has been allocated with size m + 1.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Please note, that for matrix products with more than 8192 intermediate products per row, additional temporary storage buffer is allocated by the algorithm.

Note

Currently, only trans_A == trans_B == HIPSPARSE_OPERATION_NONE is supported.

Note

Currently, only HIPSPARSE_MATRIX_TYPE_GENERAL is supported.

hipsparseXcsrgemm()#

hipsparseStatus_t hipsparseScsrgemm(hipsparseHandle_t handle, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int n, int k, const hipsparseMatDescr_t descrA, int nnzA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const float *csrValB, const int *csrRowPtrB, const int *csrColIndB, const hipsparseMatDescr_t descrC, float *csrValC, const int *csrRowPtrC, int *csrColIndC)#
hipsparseStatus_t hipsparseDcsrgemm(hipsparseHandle_t handle, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int n, int k, const hipsparseMatDescr_t descrA, int nnzA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const double *csrValB, const int *csrRowPtrB, const int *csrColIndB, const hipsparseMatDescr_t descrC, double *csrValC, const int *csrRowPtrC, int *csrColIndC)#
hipsparseStatus_t hipsparseCcsrgemm(hipsparseHandle_t handle, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int n, int k, const hipsparseMatDescr_t descrA, int nnzA, const hipComplex *csrValA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const hipComplex *csrValB, const int *csrRowPtrB, const int *csrColIndB, const hipsparseMatDescr_t descrC, hipComplex *csrValC, const int *csrRowPtrC, int *csrColIndC)#
hipsparseStatus_t hipsparseZcsrgemm(hipsparseHandle_t handle, hipsparseOperation_t transA, hipsparseOperation_t transB, int m, int n, int k, const hipsparseMatDescr_t descrA, int nnzA, const hipDoubleComplex *csrValA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const hipDoubleComplex *csrValB, const int *csrRowPtrB, const int *csrColIndB, const hipsparseMatDescr_t descrC, hipDoubleComplex *csrValC, const int *csrRowPtrC, int *csrColIndC)#

Sparse matrix sparse matrix multiplication using CSR storage format.

hipsparseXcsrgemm multiplies the sparse \(m \times k\) matrix \(A\), defined in CSR storage format with the sparse \(k \times n\) matrix \(B\), defined in CSR storage format, and stores the result in the sparse \(m \times n\) matrix \(C\), defined in CSR storage format, such that

\[ C := op(A) \cdot op(B), \]
with
\[\begin{split} op(A) = \left\{ \begin{array}{ll} A, & \text{if trans_A == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ A^T, & \text{if trans_A == HIPSPARSE_OPERATION_TRANSPOSE} \\ A^H, & \text{if trans_A == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]
and
\[\begin{split} op(B) = \left\{ \begin{array}{ll} B, & \text{if trans_B == HIPSPARSE_OPERATION_NON_TRANSPOSE} \\ B^T, & \text{if trans_B == HIPSPARSE_OPERATION_TRANSPOSE} \\ B^H, & \text{if trans_B == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE} \end{array} \right. \end{split}\]

It is assumed that csr_row_ptr_C has already been filled and that csr_val_C and csr_col_ind_C are allocated by the user. csr_row_ptr_C and allocation size of csr_col_ind_C and csr_val_C is defined by the number of non-zero elements of the sparse CSR matrix C. Both can be obtained by hipsparseXcsrgemmNnz().

Note

Currently, only trans_A == HIPSPARSE_OPERATION_NON_TRANSPOSE is supported.

Note

Currently, only trans_B == HIPSPARSE_OPERATION_NON_TRANSPOSE is supported.

Note

Currently, only HIPSPARSE_MATRIX_TYPE_GENERAL is supported.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Please note, that for matrix products with more than 4096 non-zero entries per row, additional temporary storage buffer is allocated by the algorithm.

hipsparseXcsrgemm2_bufferSizeExt()#

hipsparseStatus_t hipsparseScsrgemm2_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int k, const float *alpha, const hipsparseMatDescr_t descrA, int nnzA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const int *csrRowPtrB, const int *csrColIndB, const float *beta, const hipsparseMatDescr_t descrD, int nnzD, const int *csrRowPtrD, const int *csrColIndD, csrgemm2Info_t info, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDcsrgemm2_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int k, const double *alpha, const hipsparseMatDescr_t descrA, int nnzA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const int *csrRowPtrB, const int *csrColIndB, const double *beta, const hipsparseMatDescr_t descrD, int nnzD, const int *csrRowPtrD, const int *csrColIndD, csrgemm2Info_t info, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCcsrgemm2_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int k, const hipComplex *alpha, const hipsparseMatDescr_t descrA, int nnzA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const int *csrRowPtrB, const int *csrColIndB, const hipComplex *beta, const hipsparseMatDescr_t descrD, int nnzD, const int *csrRowPtrD, const int *csrColIndD, csrgemm2Info_t info, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZcsrgemm2_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int k, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, int nnzA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const int *csrRowPtrB, const int *csrColIndB, const hipDoubleComplex *beta, const hipsparseMatDescr_t descrD, int nnzD, const int *csrRowPtrD, const int *csrColIndD, csrgemm2Info_t info, size_t *pBufferSizeInBytes)#

Sparse matrix sparse matrix multiplication using CSR storage format.

hipsparseXcsrgemm2_bufferSizeExt returns the size of the temporary storage buffer that is required by hipsparseXcsrgemm2Nnz() and hipsparseXcsrgemm2(). The temporary storage buffer must be allocated by the user.

Note

Please note, that for matrix products with more than 4096 non-zero entries per row, additional temporary storage buffer is allocated by the algorithm.

Note

Please note, that for matrix products with more than 8192 intermediate products per row, additional temporary storage buffer is allocated by the algorithm.

Note

Currently, only HIPSPARSE_MATRIX_TYPE_GENERAL is supported.

hipsparseXcsrgemm2Nnz()#

hipsparseStatus_t hipsparseXcsrgemm2Nnz(hipsparseHandle_t handle, int m, int n, int k, const hipsparseMatDescr_t descrA, int nnzA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const int *csrRowPtrB, const int *csrColIndB, const hipsparseMatDescr_t descrD, int nnzD, const int *csrRowPtrD, const int *csrColIndD, const hipsparseMatDescr_t descrC, int *csrRowPtrC, int *nnzTotalDevHostPtr, const csrgemm2Info_t info, void *pBuffer)#

Sparse matrix sparse matrix multiplication using CSR storage format.

hipsparseXcsrgemm2Nnz computes the total CSR non-zero elements and the CSR row offsets, that point to the start of every row of the sparse CSR matrix, of the resulting multiplied matrix C. It is assumed that csr_row_ptr_C has been allocated with size m + 1. The required buffer size can be obtained by hipsparseXcsrgemm2_bufferSizeExt().

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Please note, that for matrix products with more than 8192 intermediate products per row, additional temporary storage buffer is allocated by the algorithm.

Note

Currently, only HIPSPARSE_MATRIX_TYPE_GENERAL is supported.

hipsparseXcsrgemm2()#

hipsparseStatus_t hipsparseScsrgemm2(hipsparseHandle_t handle, int m, int n, int k, const float *alpha, const hipsparseMatDescr_t descrA, int nnzA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const float *csrValB, const int *csrRowPtrB, const int *csrColIndB, const float *beta, const hipsparseMatDescr_t descrD, int nnzD, const float *csrValD, const int *csrRowPtrD, const int *csrColIndD, const hipsparseMatDescr_t descrC, float *csrValC, const int *csrRowPtrC, int *csrColIndC, const csrgemm2Info_t info, void *pBuffer)#
hipsparseStatus_t hipsparseDcsrgemm2(hipsparseHandle_t handle, int m, int n, int k, const double *alpha, const hipsparseMatDescr_t descrA, int nnzA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const double *csrValB, const int *csrRowPtrB, const int *csrColIndB, const double *beta, const hipsparseMatDescr_t descrD, int nnzD, const double *csrValD, const int *csrRowPtrD, const int *csrColIndD, const hipsparseMatDescr_t descrC, double *csrValC, const int *csrRowPtrC, int *csrColIndC, const csrgemm2Info_t info, void *pBuffer)#
hipsparseStatus_t hipsparseCcsrgemm2(hipsparseHandle_t handle, int m, int n, int k, const hipComplex *alpha, const hipsparseMatDescr_t descrA, int nnzA, const hipComplex *csrValA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const hipComplex *csrValB, const int *csrRowPtrB, const int *csrColIndB, const hipComplex *beta, const hipsparseMatDescr_t descrD, int nnzD, const hipComplex *csrValD, const int *csrRowPtrD, const int *csrColIndD, const hipsparseMatDescr_t descrC, hipComplex *csrValC, const int *csrRowPtrC, int *csrColIndC, const csrgemm2Info_t info, void *pBuffer)#
hipsparseStatus_t hipsparseZcsrgemm2(hipsparseHandle_t handle, int m, int n, int k, const hipDoubleComplex *alpha, const hipsparseMatDescr_t descrA, int nnzA, const hipDoubleComplex *csrValA, const int *csrRowPtrA, const int *csrColIndA, const hipsparseMatDescr_t descrB, int nnzB, const hipDoubleComplex *csrValB, const int *csrRowPtrB, const int *csrColIndB, const hipDoubleComplex *beta, const hipsparseMatDescr_t descrD, int nnzD, const hipDoubleComplex *csrValD, const int *csrRowPtrD, const int *csrColIndD, const hipsparseMatDescr_t descrC, hipDoubleComplex *csrValC, const int *csrRowPtrC, int *csrColIndC, const csrgemm2Info_t info, void *pBuffer)#

Sparse matrix sparse matrix multiplication using CSR storage format.

hipsparseXcsrgemm2 multiplies the scalar \(\alpha\) with the sparse \(m \times k\) matrix \(A\), defined in CSR storage format, and the sparse \(k \times n\) matrix \(B\), defined in CSR storage format, and adds the result to the sparse \(m \times n\) matrix \(D\) that is multiplied by \(\beta\). The final result is stored in the sparse \(m \times n\) matrix \(C\), defined in CSR storage format, such that

\[ C := \alpha \cdot A \cdot B + \beta \cdot D \]

It is assumed that csr_row_ptr_C has already been filled and that csr_val_C and csr_col_ind_C are allocated by the user. csr_row_ptr_C and allocation size of csr_col_ind_C and csr_val_C is defined by the number of non-zero elements of the sparse CSR matrix C. Both can be obtained by hipsparseXcsrgemm2Nnz(). The required buffer size for the computation can be obtained by hipsparseXcsrgemm2_bufferSizeExt().

Note

If \(\alpha == 0\), then \(C = \beta \cdot D\) will be computed.

Note

If \(\beta == 0\), then \(C = \alpha \cdot A \cdot B\) will be computed.

Note

\(\alpha == beta == 0\) is invalid.

Note

Currently, only HIPSPARSE_MATRIX_TYPE_GENERAL is supported.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Note

Please note, that for matrix products with more than 4096 non-zero entries per row, additional temporary storage buffer is allocated by the algorithm.

Preconditioner Functions#

This module holds all sparse preconditioners.

The sparse preconditioners describe manipulations on a matrix in sparse format to obtain a sparse preconditioner matrix.

hipsparseXbsrilu02_zeroPivot()#

hipsparseStatus_t hipsparseXbsrilu02_zeroPivot(hipsparseHandle_t handle, bsrilu02Info_t info, int *position)#

Incomplete LU factorization with 0 fill-ins and no pivoting using BSR storage format.

hipsparseXbsrilu02_zeroPivot returns HIPSPARSE_STATUS_ZERO_PIVOT, if either a structural or numerical zero has been found during hipsparseXbsrilu02_analysis() or hipsparseXbsrilu02() computation. The first zero pivot \(j\) at \(A_{j,j}\) is stored in position, using same index base as the BSR matrix.

position can be in host or device memory. If no zero pivot has been found, position is set to -1 and HIPSPARSE_STATUS_SUCCESS is returned instead.

Note

If a zero pivot is found, position \(=j\) means that either the diagonal block \(A_{j,j}\) is missing (structural zero) or the diagonal block \(A_{j,j}\) is not invertible (numerical zero).

Note

hipsparseXbsrilu02_zeroPivot is a blocking function. It might influence performance negatively.

hipsparseXbsrilu02_numericBoost()#

hipsparseStatus_t hipsparseSbsrilu02_numericBoost(hipsparseHandle_t handle, bsrilu02Info_t info, int enable_boost, double *tol, float *boost_val)#
hipsparseStatus_t hipsparseDbsrilu02_numericBoost(hipsparseHandle_t handle, bsrilu02Info_t info, int enable_boost, double *tol, double *boost_val)#
hipsparseStatus_t hipsparseCbsrilu02_numericBoost(hipsparseHandle_t handle, bsrilu02Info_t info, int enable_boost, double *tol, hipComplex *boost_val)#
hipsparseStatus_t hipsparseZbsrilu02_numericBoost(hipsparseHandle_t handle, bsrilu02Info_t info, int enable_boost, double *tol, hipDoubleComplex *boost_val)#

Incomplete LU factorization with 0 fill-ins and no pivoting using BSR storage format.

hipsparseXbsrilu02_numericBoost enables the user to replace a numerical value in an incomplete LU factorization. tol is used to determine whether a numerical value is replaced by boost_val, such that \(A_{j,j} = \text{boost_val}\) if \(\text{tol} \ge \left|A_{j,j}\right|\).

Note

The boost value is enabled by setting enable_boost to 1 or disabled by setting enable_boost to 0.

Note

tol and boost_val can be in host or device memory.

hipsparseXbsrilu02_bufferSize()#

hipsparseStatus_t hipsparseSbsrilu02_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, float *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrilu02Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDbsrilu02_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, double *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrilu02Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCbsrilu02_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrilu02Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZbsrilu02_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipDoubleComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrilu02Info_t info, int *pBufferSizeInBytes)#

Incomplete LU factorization with 0 fill-ins and no pivoting using BSR storage format.

hipsparseXbsrilu02_bufferSize returns the size of the temporary storage buffer that is required by hipsparseXbsrilu02_analysis() and hipsparseXbsrilu02_solve(). The temporary storage buffer must be allocated by the user.

hipsparseXbsrilu02_analysis()#

hipsparseStatus_t hipsparseSbsrilu02_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, float *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrilu02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseDbsrilu02_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, double *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrilu02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseCbsrilu02_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrilu02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseZbsrilu02_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipDoubleComplex *bsrSortedValA, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrilu02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#

Incomplete LU factorization with 0 fill-ins and no pivoting using BSR storage format.

hipsparseXbsrilu02_analysis performs the analysis step for hipsparseXbsrilu02().

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 may return before the actual computation has finished.

hipsparseXbsrilu02()#

hipsparseStatus_t hipsparseSbsrilu02(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, float *bsrSortedValA_valM, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrilu02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseDbsrilu02(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, double *bsrSortedValA_valM, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrilu02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseCbsrilu02(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipComplex *bsrSortedValA_valM, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrilu02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseZbsrilu02(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipDoubleComplex *bsrSortedValA_valM, const int *bsrSortedRowPtrA, const int *bsrSortedColIndA, int blockDim, bsrilu02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#

Incomplete LU factorization with 0 fill-ins and no pivoting using BSR storage format.

hipsparseXbsrilu02 computes the incomplete LU factorization with 0 fill-ins and no pivoting of a sparse \(mb \times mb\) BSR matrix \(A\), such that

\[ A \approx LU \]

hipsparseXbsrilu02 requires a user allocated temporary buffer. Its size is returned by hipsparseXbsrilu02_bufferSize(). Furthermore, analysis meta data is required. It can be obtained by hipsparseXbsrilu02_analysis(). hipsparseXbsrilu02 reports the first zero pivot (either numerical or structural zero). The zero pivot status can be obtained by calling hipsparseXbsrilu02_zeroPivot().

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcsrilu02_zeroPivot()#

hipsparseStatus_t hipsparseXcsrilu02_zeroPivot(hipsparseHandle_t handle, csrilu02Info_t info, int *position)#

Incomplete LU factorization with 0 fill-ins and no pivoting using CSR storage format.

hipsparseXcsrilu02_zeroPivot returns HIPSPARSE_STATUS_ZERO_PIVOT, if either a structural or numerical zero has been found during hipsparseXcsrilu02() computation. The first zero pivot \(j\) at \(A_{j,j}\) is stored in position, using same index base as the CSR matrix.

position can be in host or device memory. If no zero pivot has been found, position is set to -1 and HIPSPARSE_STATUS_SUCCESS is returned instead.

Note

hipsparseXcsrilu02_zeroPivot is a blocking function. It might influence performance negatively.

hipsparseXcsrilu02_numericBoost()#

hipsparseStatus_t hipsparseScsrilu02_numericBoost(hipsparseHandle_t handle, csrilu02Info_t info, int enable_boost, double *tol, float *boost_val)#
hipsparseStatus_t hipsparseDcsrilu02_numericBoost(hipsparseHandle_t handle, csrilu02Info_t info, int enable_boost, double *tol, double *boost_val)#
hipsparseStatus_t hipsparseCcsrilu02_numericBoost(hipsparseHandle_t handle, csrilu02Info_t info, int enable_boost, double *tol, hipComplex *boost_val)#
hipsparseStatus_t hipsparseZcsrilu02_numericBoost(hipsparseHandle_t handle, csrilu02Info_t info, int enable_boost, double *tol, hipDoubleComplex *boost_val)#

Incomplete LU factorization with 0 fill-ins and no pivoting using CSR storage format.

hipsparseXcsrilu02_numericBoost enables the user to replace a numerical value in an incomplete LU factorization. tol is used to determine whether a numerical value is replaced by boost_val, such that \(A_{j,j} = \text{boost_val}\) if \(\text{tol} \ge \left|A_{j,j}\right|\).

Note

The boost value is enabled by setting enable_boost to 1 or disabled by setting enable_boost to 0.

Note

tol and boost_val can be in host or device memory.

hipsparseXcsrilu02_bufferSize()#

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)#
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)#
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)#
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)#

Incomplete LU factorization with 0 fill-ins and no pivoting using CSR storage format.

hipsparseXcsrilu02_bufferSize returns the size of the temporary storage buffer that is required by hipsparseXcsrilu02_analysis() and hipsparseXcsrilu02_solve(). the temporary storage buffer must be allocated by the user.

hipsparseXcsrilu02_bufferSizeExt()#

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 *pBufferSize)#
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 *pBufferSize)#
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 *pBufferSize)#
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 *pBufferSize)#

Incomplete LU factorization with 0 fill-ins and no pivoting using CSR storage format.

hipsparseXcsrilu02_bufferSizeExt returns the size of the temporary storage buffer that is required by hipsparseXcsrilu02_analysis() and hipsparseXcsrilu02_solve(). the temporary storage buffer must be allocated by the user.

hipsparseXcsrilu02_analysis()#

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)#
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)#
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)#
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)#

Incomplete LU factorization with 0 fill-ins and no pivoting using CSR storage format.

hipsparseXcsrilu02_analysis performs the analysis step for hipsparseXcsrilu02().

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 may return before the actual computation has finished.

hipsparseXcsrilu02()#

hipsparseStatus_t hipsparseScsrilu02(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, float *csrSortedValA_valM, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrilu02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseDcsrilu02(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, double *csrSortedValA_valM, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrilu02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseCcsrilu02(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, hipComplex *csrSortedValA_valM, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrilu02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseZcsrilu02(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, hipDoubleComplex *csrSortedValA_valM, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csrilu02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#

Incomplete LU factorization with 0 fill-ins and no pivoting using CSR storage format.

hipsparseXcsrilu02 computes the incomplete LU factorization with 0 fill-ins and no pivoting of a sparse \(m \times m\) CSR matrix \(A\), such that

\[ A \approx LU \]

hipsparseXcsrilu02 requires a user allocated temporary buffer. Its size is returned by hipsparseXcsrilu02_bufferSize() or hipsparseXcsrilu02_bufferSizeExt(). Furthermore, analysis meta data is required. It can be obtained by hipsparseXcsrilu02_analysis(). hipsparseXcsrilu02 reports the first zero pivot (either numerical or structural zero). The zero pivot status can be obtained by calling hipsparseXcsrilu02_zeroPivot().

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 may return before the actual computation has finished.

hipsparseXbsric02_zeroPivot()#

hipsparseStatus_t hipsparseXbsric02_zeroPivot(hipsparseHandle_t handle, bsric02Info_t info, int *position)#

Incomplete Cholesky factorization with 0 fill-ins and no pivoting using BSR storage format.

hipsparseXbsric02_zeroPivot returns HIPSPARSE_STATUS_ZERO_PIVOT, if either a structural or numerical zero has been found during hipsparseXbsric02_analysis() or hipsparseXbsric02() computation. The first zero pivot \(j\) at \(A_{j,j}\) is stored in position, using same index base as the BSR matrix.

position can be in host or device memory. If no zero pivot has been found, position is set to -1 and HIPSPARSE_STATUS_SUCCESS is returned instead.

Note

If a zero pivot is found, position=j means that either the diagonal block A(j,j) is missing (structural zero) or the diagonal block A(j,j) is not positive definite (numerical zero).

Note

hipsparseXbsric02_zeroPivot is a blocking function. It might influence performance negatively.

hipsparseXbsric02_bufferSize()#

hipsparseStatus_t hipsparseSbsric02_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, float *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, bsric02Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDbsric02_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, double *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, bsric02Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCbsric02_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, bsric02Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZbsric02_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipDoubleComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, bsric02Info_t info, int *pBufferSizeInBytes)#

Incomplete Cholesky factorization with 0 fill-ins and no pivoting using BSR storage format.

hipsparseXbsric02_bufferSize returns the size of the temporary storage buffer that is required by hipsparseXbsric02_analysis() and hipsparseXbsric02(). The temporary storage buffer must be allocated by the user.

hipsparseXbsric02_analysis()#

hipsparseStatus_t hipsparseSbsric02_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, const float *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, bsric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseDbsric02_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, const double *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, bsric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseCbsric02_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, const hipComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, bsric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseZbsric02_analysis(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, const hipDoubleComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, bsric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#

Incomplete Cholesky factorization with 0 fill-ins and no pivoting using BSR storage format.

hipsparseXbsric02_analysis performs the analysis step for hipsparseXbsric02().

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 may return before the actual computation has finished.

hipsparseXbsric02()#

hipsparseStatus_t hipsparseSbsric02(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, float *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, bsric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseDbsric02(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, double *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, bsric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseCbsric02(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, bsric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseZbsric02(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nnzb, const hipsparseMatDescr_t descrA, hipDoubleComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, bsric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#

Incomplete Cholesky factorization with 0 fill-ins and no pivoting using BSR storage format.

hipsparseXbsric02 computes the incomplete Cholesky factorization with 0 fill-ins and no pivoting of a sparse \(mb \times mb\) BSR matrix \(A\), such that

\[ A \approx LL^T \]

hipsparseXbsric02 requires a user allocated temporary buffer. Its size is returned by hipsparseXbsric02_bufferSize(). Furthermore, analysis meta data is required. It can be obtained by hipsparseXbsric02_analysis(). hipsparseXbsric02 reports the first zero pivot (either numerical or structural zero). The zero pivot status can be obtained by calling hipsparseXbsric02_zeroPivot().

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcsric02_zeroPivot()#

hipsparseStatus_t hipsparseXcsric02_zeroPivot(hipsparseHandle_t handle, csric02Info_t info, int *position)#

Incomplete Cholesky factorization with 0 fill-ins and no pivoting using CSR storage format.

hipsparseXcsric02_zeroPivot returns HIPSPARSE_STATUS_ZERO_PIVOT, if either a structural or numerical zero has been found during hipsparseXcsric02_analysis() or hipsparseXcsric02() computation. The first zero pivot \(j\) at \(A_{j,j}\) is stored in position, using same index base as the CSR matrix.

position can be in host or device memory. If no zero pivot has been found, position is set to -1 and HIPSPARSE_STATUS_SUCCESS is returned instead.

Note

hipsparseXcsric02_zeroPivot is a blocking function. It might influence performance negatively.

hipsparseXcsric02_bufferSize()#

hipsparseStatus_t hipsparseScsric02_bufferSize(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDcsric02_bufferSize(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCcsric02_bufferSize(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, int *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZcsric02_bufferSize(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, int *pBufferSizeInBytes)#

Incomplete Cholesky factorization with 0 fill-ins and no pivoting using CSR storage format.

hipsparseXcsric02_bufferSize returns the size of the temporary storage buffer that is required by hipsparseXcsric02_analysis() and hipsparseXcsric02().

hipsparseXcsric02_bufferSizeExt()#

hipsparseStatus_t hipsparseScsric02_bufferSizeExt(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, size_t *pBufferSize)#
hipsparseStatus_t hipsparseDcsric02_bufferSizeExt(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, size_t *pBufferSize)#
hipsparseStatus_t hipsparseCcsric02_bufferSizeExt(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, size_t *pBufferSize)#
hipsparseStatus_t hipsparseZcsric02_bufferSizeExt(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, size_t *pBufferSize)#

Incomplete Cholesky factorization with 0 fill-ins and no pivoting using CSR storage format.

hipsparseXcsric02_bufferSizeExt returns the size of the temporary storage buffer that is required by hipsparseXcsric02_analysis() and hipsparseXcsric02().

hipsparseXcsric02_analysis()#

hipsparseStatus_t hipsparseScsric02_analysis(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, const float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseDcsric02_analysis(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, const double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseCcsric02_analysis(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, const hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseZcsric02_analysis(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, const hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#

Incomplete Cholesky factorization with 0 fill-ins and no pivoting using CSR storage format.

hipsparseXcsric02_analysis performs the analysis step for hipsparseXcsric02().

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 may return before the actual computation has finished.

hipsparseXcsric02()#

hipsparseStatus_t hipsparseScsric02(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, float *csrSortedValA_valM, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseDcsric02(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, double *csrSortedValA_valM, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseCcsric02(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, hipComplex *csrSortedValA_valM, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#
hipsparseStatus_t hipsparseZcsric02(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, hipDoubleComplex *csrSortedValA_valM, const int *csrSortedRowPtrA, const int *csrSortedColIndA, csric02Info_t info, hipsparseSolvePolicy_t policy, void *pBuffer)#

Incomplete Cholesky factorization with 0 fill-ins and no pivoting using CSR storage format.

hipsparseXcsric02 computes the incomplete Cholesky factorization with 0 fill-ins and no pivoting of a sparse \(m \times m\) CSR matrix \(A\), such that

\[ A \approx LL^T \]

hipsparseXcsric02 requires a user allocated temporary buffer. Its size is returned by hipsparseXcsric02_bufferSize() or hipsparseXcsric02_bufferSizeExt(). Furthermore, analysis meta data is required. It can be obtained by hipsparseXcsric02_analysis(). hipsparseXcsric02 reports the first zero pivot (either numerical or structural zero). The zero pivot status can be obtained by calling hipsparseXcsric02_zeroPivot().

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 may return before the actual computation has finished.

hipsparseXgtsv2_bufferSizeExt()#

hipsparseStatus_t hipsparseSgtsv2_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const float *dl, const float *d, const float *du, const float *B, int ldb, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDgtsv2_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const double *dl, const double *d, const double *du, const double *B, int db, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCgtsv2_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const hipComplex *dl, const hipComplex *d, const hipComplex *du, const hipComplex *B, int ldb, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZgtsv2_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const hipDoubleComplex *dl, const hipDoubleComplex *d, const hipDoubleComplex *du, const hipDoubleComplex *B, int ldb, size_t *pBufferSizeInBytes)#

Tridiagonal solver with pivoting.

hipsparseXgtsv2_bufferSize returns the size of the temporary storage buffer that is required by hipsparseXgtsv2(). The temporary storage buffer must be allocated by the user.

hipsparseXgtsv2()#

hipsparseStatus_t hipsparseSgtsv2(hipsparseHandle_t handle, int m, int n, const float *dl, const float *d, const float *du, float *B, int ldb, void *pBuffer)#
hipsparseStatus_t hipsparseDgtsv2(hipsparseHandle_t handle, int m, int n, const double *dl, const double *d, const double *du, double *B, int ldb, void *pBuffer)#
hipsparseStatus_t hipsparseCgtsv2(hipsparseHandle_t handle, int m, int n, const hipComplex *dl, const hipComplex *d, const hipComplex *du, hipComplex *B, int ldb, void *pBuffer)#
hipsparseStatus_t hipsparseZgtsv2(hipsparseHandle_t handle, int m, int n, const hipDoubleComplex *dl, const hipDoubleComplex *d, const hipDoubleComplex *du, hipDoubleComplex *B, int ldb, void *pBuffer)#

Tridiagonal solver with pivoting.

hipsparseXgtsv2 solves a tridiagonal system for multiple right hand sides using pivoting.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXgtsv2_nopivot_bufferSizeExt()#

hipsparseStatus_t hipsparseSgtsv2_nopivot_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const float *dl, const float *d, const float *du, const float *B, int ldb, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDgtsv2_nopivot_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const double *dl, const double *d, const double *du, const double *B, int db, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCgtsv2_nopivot_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const hipComplex *dl, const hipComplex *d, const hipComplex *du, const hipComplex *B, int ldb, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZgtsv2_nopivot_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const hipDoubleComplex *dl, const hipDoubleComplex *d, const hipDoubleComplex *du, const hipDoubleComplex *B, int ldb, size_t *pBufferSizeInBytes)#

Tridiagonal solver (no pivoting)

hipsparseXgtsv2_nopivot_bufferSizeExt returns the size of the temporary storage buffer that is required by hipsparseXgtsv2_nopivot(). The temporary storage buffer must be allocated by the user.

hipsparseXgtsv2_nopivot()#

hipsparseStatus_t hipsparseSgtsv2_nopivot(hipsparseHandle_t handle, int m, int n, const float *dl, const float *d, const float *du, float *B, int ldb, void *pBuffer)#
hipsparseStatus_t hipsparseDgtsv2_nopivot(hipsparseHandle_t handle, int m, int n, const double *dl, const double *d, const double *du, double *B, int ldb, void *pBuffer)#
hipsparseStatus_t hipsparseCgtsv2_nopivot(hipsparseHandle_t handle, int m, int n, const hipComplex *dl, const hipComplex *d, const hipComplex *du, hipComplex *B, int ldb, void *pBuffer)#
hipsparseStatus_t hipsparseZgtsv2_nopivot(hipsparseHandle_t handle, int m, int n, const hipDoubleComplex *dl, const hipDoubleComplex *d, const hipDoubleComplex *du, hipDoubleComplex *B, int ldb, void *pBuffer)#

Tridiagonal solver (no pivoting)

hipsparseXgtsv2_nopivot solves a tridiagonal linear system for multiple right-hand sides

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXgtsv2StridedBatch_bufferSizeExt()#

hipsparseStatus_t hipsparseSgtsv2StridedBatch_bufferSizeExt(hipsparseHandle_t handle, int m, const float *dl, const float *d, const float *du, const float *x, int batchCount, int batchStride, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDgtsv2StridedBatch_bufferSizeExt(hipsparseHandle_t handle, int m, const double *dl, const double *d, const double *du, const double *x, int batchCount, int batchStride, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCgtsv2StridedBatch_bufferSizeExt(hipsparseHandle_t handle, int m, const hipComplex *dl, const hipComplex *d, const hipComplex *du, const hipComplex *x, int batchCount, int batchStride, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZgtsv2StridedBatch_bufferSizeExt(hipsparseHandle_t handle, int m, const hipDoubleComplex *dl, const hipDoubleComplex *d, const hipDoubleComplex *du, const hipDoubleComplex *x, int batchCount, int batchStride, size_t *pBufferSizeInBytes)#

Strided Batch tridiagonal solver (no pivoting)

hipsparseXgtsv2StridedBatch_bufferSizeExt returns the size of the temporary storage buffer that is required by hipsparseXgtsv2StridedBatch(). The temporary storage buffer must be allocated by the user.

hipsparseXgtsv2StridedBatch()#

hipsparseStatus_t hipsparseSgtsv2StridedBatch(hipsparseHandle_t handle, int m, const float *dl, const float *d, const float *du, float *x, int batchCount, int batchStride, void *pBuffer)#
hipsparseStatus_t hipsparseDgtsv2StridedBatch(hipsparseHandle_t handle, int m, const double *dl, const double *d, const double *du, double *x, int batchCount, int batchStride, void *pBuffer)#
hipsparseStatus_t hipsparseCgtsv2StridedBatch(hipsparseHandle_t handle, int m, const hipComplex *dl, const hipComplex *d, const hipComplex *du, hipComplex *x, int batchCount, int batchStride, void *pBuffer)#
hipsparseStatus_t hipsparseZgtsv2StridedBatch(hipsparseHandle_t handle, int m, const hipDoubleComplex *dl, const hipDoubleComplex *d, const hipDoubleComplex *du, hipDoubleComplex *x, int batchCount, int batchStride, void *pBuffer)#

Strided Batch tridiagonal solver (no pivoting)

hipsparseXgtsv2StridedBatch solves a batched tridiagonal linear system

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXgtsvInterleavedBatch_bufferSizeExt()#

hipsparseStatus_t hipsparseSgtsvInterleavedBatch_bufferSizeExt(hipsparseHandle_t handle, int algo, int m, const float *dl, const float *d, const float *du, const float *x, int batchCount, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDgtsvInterleavedBatch_bufferSizeExt(hipsparseHandle_t handle, int algo, int m, const double *dl, const double *d, const double *du, const double *x, int batchCount, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCgtsvInterleavedBatch_bufferSizeExt(hipsparseHandle_t handle, int algo, int m, const hipComplex *dl, const hipComplex *d, const hipComplex *du, const hipComplex *x, int batchCount, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZgtsvInterleavedBatch_bufferSizeExt(hipsparseHandle_t handle, int algo, int m, const hipDoubleComplex *dl, const hipDoubleComplex *d, const hipDoubleComplex *du, const hipDoubleComplex *x, int batchCount, size_t *pBufferSizeInBytes)#

Interleaved Batch tridiagonal solver.

hipsparseXgtsvInterleavedBatch_bufferSizeExt returns the size of the temporary storage buffer that is required by hipsparseXgtsvInterleavedBatch(). The temporary storage buffer must be allocated by the user.

hipsparseXgtsvInterleavedBatch()#

hipsparseStatus_t hipsparseSgtsvInterleavedBatch(hipsparseHandle_t handle, int algo, int m, float *dl, float *d, float *du, float *x, int batchCount, void *pBuffer)#
hipsparseStatus_t hipsparseDgtsvInterleavedBatch(hipsparseHandle_t handle, int algo, int m, double *dl, double *d, double *du, double *x, int batchCount, void *pBuffer)#
hipsparseStatus_t hipsparseCgtsvInterleavedBatch(hipsparseHandle_t handle, int algo, int m, hipComplex *dl, hipComplex *d, hipComplex *du, hipComplex *x, int batchCount, void *pBuffer)#
hipsparseStatus_t hipsparseZgtsvInterleavedBatch(hipsparseHandle_t handle, int algo, int m, hipDoubleComplex *dl, hipDoubleComplex *d, hipDoubleComplex *du, hipDoubleComplex *x, int batchCount, void *pBuffer)#

Interleaved Batch tridiagonal solver.

hipsparseXgtsvInterleavedBatch solves a batched tridiagonal linear system

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXgpsvInterleavedBatch_bufferSizeExt()#

hipsparseStatus_t hipsparseSgpsvInterleavedBatch_bufferSizeExt(hipsparseHandle_t handle, int algo, int m, const float *ds, const float *dl, const float *d, const float *du, const float *dw, const float *x, int batchCount, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDgpsvInterleavedBatch_bufferSizeExt(hipsparseHandle_t handle, int algo, int m, const double *ds, const double *dl, const double *d, const double *du, const double *dw, const double *x, int batchCount, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCgpsvInterleavedBatch_bufferSizeExt(hipsparseHandle_t handle, int algo, int m, const hipComplex *ds, const hipComplex *dl, const hipComplex *d, const hipComplex *du, const hipComplex *dw, const hipComplex *x, int batchCount, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZgpsvInterleavedBatch_bufferSizeExt(hipsparseHandle_t handle, int algo, int m, const hipDoubleComplex *ds, const hipDoubleComplex *dl, const hipDoubleComplex *d, const hipDoubleComplex *du, const hipDoubleComplex *dw, const hipDoubleComplex *x, int batchCount, size_t *pBufferSizeInBytes)#

Interleaved Batch pentadiagonal solver.

hipsparseXgpsvInterleavedBatch_bufferSizeExt returns the size of the temporary storage buffer that is required by hipsparseXgpsvInterleavedBatch(). The temporary storage buffer must be allocated by the user.

hipsparseXgpsvInterleavedBatch()#

hipsparseStatus_t hipsparseSgpsvInterleavedBatch(hipsparseHandle_t handle, int algo, int m, float *ds, float *dl, float *d, float *du, float *dw, float *x, int batchCount, void *pBuffer)#
hipsparseStatus_t hipsparseDgpsvInterleavedBatch(hipsparseHandle_t handle, int algo, int m, double *ds, double *dl, double *d, double *du, double *dw, double *x, int batchCount, void *pBuffer)#
hipsparseStatus_t hipsparseCgpsvInterleavedBatch(hipsparseHandle_t handle, int algo, int m, hipComplex *ds, hipComplex *dl, hipComplex *d, hipComplex *du, hipComplex *dw, hipComplex *x, int batchCount, void *pBuffer)#
hipsparseStatus_t hipsparseZgpsvInterleavedBatch(hipsparseHandle_t handle, int algo, int m, hipDoubleComplex *ds, hipDoubleComplex *dl, hipDoubleComplex *d, hipDoubleComplex *du, hipDoubleComplex *dw, hipDoubleComplex *x, int batchCount, void *pBuffer)#

Interleaved Batch pentadiagonal solver.

hipsparseXgpsvInterleavedBatch solves a batched pentadiagonal linear system

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Sparse Conversion Functions#

This module holds all sparse conversion routines.

The sparse conversion routines describe operations on a matrix in sparse format to obtain a matrix in a different sparse format.

hipsparseXnnz()#

hipsparseStatus_t hipsparseSnnz(hipsparseHandle_t handle, hipsparseDirection_t dirA, int m, int n, const hipsparseMatDescr_t descrA, const float *A, int lda, int *nnzPerRowColumn, int *nnzTotalDevHostPtr)#
hipsparseStatus_t hipsparseDnnz(hipsparseHandle_t handle, hipsparseDirection_t dirA, int m, int n, const hipsparseMatDescr_t descrA, const double *A, int lda, int *nnzPerRowColumn, int *nnzTotalDevHostPtr)#
hipsparseStatus_t hipsparseCnnz(hipsparseHandle_t handle, hipsparseDirection_t dirA, int m, int n, const hipsparseMatDescr_t descrA, const hipComplex *A, int lda, int *nnzPerRowColumn, int *nnzTotalDevHostPtr)#
hipsparseStatus_t hipsparseZnnz(hipsparseHandle_t handle, hipsparseDirection_t dirA, int m, int n, const hipsparseMatDescr_t descrA, const hipDoubleComplex *A, int lda, int *nnzPerRowColumn, int *nnzTotalDevHostPtr)#

This function computes the number of nonzero elements per row or column and the total number of nonzero elements in a dense matrix.

The routine does support asynchronous execution if the pointer mode is set to device.

hipsparseXdense2csr()#

hipsparseStatus_t hipsparseSdense2csr(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const float *A, int ld, const int *nnz_per_rows, float *csr_val, int *csr_row_ptr, int *csr_col_ind)#
hipsparseStatus_t hipsparseDdense2csr(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const double *A, int ld, const int *nnz_per_rows, double *csr_val, int *csr_row_ptr, int *csr_col_ind)#
hipsparseStatus_t hipsparseCdense2csr(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const hipComplex *A, int ld, const int *nnz_per_rows, hipComplex *csr_val, int *csr_row_ptr, int *csr_col_ind)#
hipsparseStatus_t hipsparseZdense2csr(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const hipDoubleComplex *A, int ld, const int *nnz_per_rows, hipDoubleComplex *csr_val, int *csr_row_ptr, int *csr_col_ind)#

This function converts the matrix A in dense format into a sparse matrix in CSR format. All the parameters are assumed to have been pre-allocated by the user and the arrays are filled in based on nnz_per_row, which can be pre-computed with hipsparseXnnz(). It is executed asynchronously with respect to the host and may return control to the application on the host before the entire result is ready.

hipsparseXpruneDense2csr_bufferSize()#

hipsparseStatus_t hipsparseSpruneDense2csr_bufferSize(hipsparseHandle_t handle, int m, int n, const float *A, int lda, const float *threshold, const hipsparseMatDescr_t descr, const float *csrVal, const int *csrRowPtr, const int *csrColInd, size_t *bufferSize)#
hipsparseStatus_t hipsparseDpruneDense2csr_bufferSize(hipsparseHandle_t handle, int m, int n, const double *A, int lda, const double *threshold, const hipsparseMatDescr_t descr, const double *csrVal, const int *csrRowPtr, const int *csrColInd, size_t *bufferSize)#

This function computes the the size of the user allocated temporary storage buffer used when converting and pruning a dense matrix to a CSR matrix.

hipsparseXpruneDense2csr_bufferSizeExt returns the size of the temporary storage buffer that is required by hipsparseXpruneDense2csrNnz() and hipsparseXpruneDense2csr(). The temporary storage buffer must be allocated by the user.

hipsparseXpruneDense2csrNnz()#

hipsparseStatus_t hipsparseSpruneDense2csrNnz(hipsparseHandle_t handle, int m, int n, const float *A, int lda, const float *threshold, const hipsparseMatDescr_t descr, int *csrRowPtr, int *nnzTotalDevHostPtr, void *buffer)#
hipsparseStatus_t hipsparseDpruneDense2csrNnz(hipsparseHandle_t handle, int m, int n, const double *A, int lda, const double *threshold, const hipsparseMatDescr_t descr, int *csrRowPtr, int *nnzTotalDevHostPtr, void *buffer)#

This function computes the number of nonzero elements per row and the total number of nonzero elements in a dense matrix once elements less than the threshold are pruned from the matrix.

The routine does support asynchronous execution if the pointer mode is set to device.

hipsparseXpruneDense2csr()#

hipsparseStatus_t hipsparseSpruneDense2csr(hipsparseHandle_t handle, int m, int n, const float *A, int lda, const float *threshold, const hipsparseMatDescr_t descr, float *csrVal, const int *csrRowPtr, int *csrColInd, void *buffer)#
hipsparseStatus_t hipsparseDpruneDense2csr(hipsparseHandle_t handle, int m, int n, const double *A, int lda, const double *threshold, const hipsparseMatDescr_t descr, double *csrVal, const int *csrRowPtr, int *csrColInd, void *buffer)#

This function converts the matrix A in dense format into a sparse matrix in CSR format while pruning values that are less than the threshold. All the parameters are assumed to have been pre-allocated by the user.

The user first allocates csrRowPtr to have m+1 elements and then calls hipsparseXpruneDense2csrNnz() which fills in the csrRowPtr array and stores the number of elements that are larger than the pruning threshold in nnzTotalDevHostPtr. The user then allocates csrColInd and csrVal to have size nnzTotalDevHostPtr and completes the conversion by calling hipsparseXpruneDense2csr(). A temporary storage buffer is used by both hipsparseXpruneDense2csrNnz() and hipsparseXpruneDense2csr() and must be allocated by the user and whose size is determined by hipsparseXpruneDense2csr_bufferSizeExt(). The routine hipsparseXpruneDense2csr() is executed asynchronously with respect to the host and may return control to the application on the host before the entire result is ready.

hipsparseXpruneDense2csrByPercentage_bufferSize()#

hipsparseStatus_t hipsparseSpruneDense2csrByPercentage_bufferSize(hipsparseHandle_t handle, int m, int n, const float *A, int lda, float percentage, const hipsparseMatDescr_t descr, const float *csrVal, const int *csrRowPtr, const int *csrColInd, pruneInfo_t info, size_t *bufferSize)#
hipsparseStatus_t hipsparseDpruneDense2csrByPercentage_bufferSize(hipsparseHandle_t handle, int m, int n, const double *A, int lda, double percentage, const hipsparseMatDescr_t descr, const double *csrVal, const int *csrRowPtr, const int *csrColInd, pruneInfo_t info, size_t *bufferSize)#

This function computes the size of the user allocated temporary storage buffer used when converting and pruning by percentage a dense matrix to a CSR matrix.

When converting and pruning a dense matrix A to a CSR matrix by percentage the following steps are performed. First the user calls hipsparseXpruneDense2csrByPercentage_bufferSize which determines the size of the temporary storage buffer. Once determined, this buffer must be allocated by the user. Next the user allocates the csr_row_ptr array to have m+1 elements and calls hipsparseXpruneDense2csrNnzByPercentage. Finally the user finishes the conversion by allocating the csr_col_ind and csr_val arrays (whos size is determined by the value at nnz_total_dev_host_ptr) and calling hipsparseXpruneDense2csrByPercentage.

The pruning by percentage works by first sorting the absolute values of the dense matrix A. We then determine a position in this sorted array by

\[ pos = ceil(m*n*(percentage/100)) - 1 pos = min(pos, m*n-1) pos = max(pos, 0) threshold = sorted_A[pos] \]
Once we have this threshold we prune values in the dense matrix A as in hipsparseXpruneDense2csr. It is executed asynchronously with respect to the host and may return control to the application on the host before the entire result is ready.

hipsparseXpruneDense2csrByPercentage_bufferSizeExt()#

hipsparseStatus_t hipsparseSpruneDense2csrByPercentage_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const float *A, int lda, float percentage, const hipsparseMatDescr_t descr, const float *csrVal, const int *csrRowPtr, const int *csrColInd, pruneInfo_t info, size_t *bufferSize)#
hipsparseStatus_t hipsparseDpruneDense2csrByPercentage_bufferSizeExt(hipsparseHandle_t handle, int m, int n, const double *A, int lda, double percentage, const hipsparseMatDescr_t descr, const double *csrVal, const int *csrRowPtr, const int *csrColInd, pruneInfo_t info, size_t *bufferSize)#

This function computes the size of the user allocated temporary storage buffer used when converting and pruning by percentage a dense matrix to a CSR matrix.

When converting and pruning a dense matrix A to a CSR matrix by percentage the following steps are performed. First the user calls hipsparseXpruneDense2csrByPercentage_bufferSizeExt which determines the size of the temporary storage buffer. Once determined, this buffer must be allocated by the user. Next the user allocates the csr_row_ptr array to have m+1 elements and calls hipsparseXpruneDense2csrNnzByPercentage. Finally the user finishes the conversion by allocating the csr_col_ind and csr_val arrays (whos size is determined by the value at nnz_total_dev_host_ptr) and calling hipsparseXpruneDense2csrByPercentage.

The pruning by percentage works by first sorting the absolute values of the dense matrix A. We then determine a position in this sorted array by

\[ pos = ceil(m*n*(percentage/100)) - 1 pos = min(pos, m*n-1) pos = max(pos, 0) threshold = sorted_A[pos] \]
Once we have this threshold we prune values in the dense matrix A as in hipsparseXpruneDense2csr. It is executed asynchronously with respect to the host and may return control to the application on the host before the entire result is ready.

hipsparseXpruneDense2csrNnzByPercentage()#

hipsparseStatus_t hipsparseSpruneDense2csrNnzByPercentage(hipsparseHandle_t handle, int m, int n, const float *A, int lda, float percentage, const hipsparseMatDescr_t descr, int *csrRowPtr, int *nnzTotalDevHostPtr, pruneInfo_t info, void *buffer)#
hipsparseStatus_t hipsparseDpruneDense2csrNnzByPercentage(hipsparseHandle_t handle, int m, int n, const double *A, int lda, double percentage, const hipsparseMatDescr_t descr, int *csrRowPtr, int *nnzTotalDevHostPtr, pruneInfo_t info, void *buffer)#

This function computes the number of nonzero elements per row and the total number of nonzero elements in a dense matrix when converting and pruning by percentage a dense matrix to a CSR matrix.

When converting and pruning a dense matrix A to a CSR matrix by percentage the following steps are performed. First the user calls hipsparseXpruneDense2csrByPercentage_bufferSize which determines the size of the temporary storage buffer. Once determined, this buffer must be allocated by the user. Next the user allocates the csr_row_ptr array to have m+1 elements and calls hipsparseXpruneDense2csrNnzByPercentage. Finally the user finishes the conversion by allocating the csr_col_ind and csr_val arrays (whos size is determined by the value at nnz_total_dev_host_ptr) and calling hipsparseXpruneDense2csrByPercentage.

The pruning by percentage works by first sorting the absolute values of the dense matrix A. We then determine a position in this sorted array by

\[ pos = ceil(m*n*(percentage/100)) - 1 pos = min(pos, m*n-1) pos = max(pos, 0) threshold = sorted_A[pos] \]
Once we have this threshold we prune values in the dense matrix A as in hipsparseXpruneDense2csr. The routine does support asynchronous execution if the pointer mode is set to device.

hipsparseXpruneDense2csrByPercentage()#

hipsparseStatus_t hipsparseSpruneDense2csrByPercentage(hipsparseHandle_t handle, int m, int n, const float *A, int lda, float percentage, const hipsparseMatDescr_t descr, float *csrVal, const int *csrRowPtr, int *csrColInd, pruneInfo_t info, void *buffer)#
hipsparseStatus_t hipsparseDpruneDense2csrByPercentage(hipsparseHandle_t handle, int m, int n, const double *A, int lda, double percentage, const hipsparseMatDescr_t descr, double *csrVal, const int *csrRowPtr, int *csrColInd, pruneInfo_t info, void *buffer)#

This function computes the number of nonzero elements per row and the total number of nonzero elements in a dense matrix when converting and pruning by percentage a dense matrix to a CSR matrix.

When converting and pruning a dense matrix A to a CSR matrix by percentage the following steps are performed. First the user calls hipsparseXpruneDense2csrByPercentage_bufferSize which determines the size of the temporary storage buffer. Once determined, this buffer must be allocated by the user. Next the user allocates the csr_row_ptr array to have m+1 elements and calls hipsparseXpruneDense2csrNnzByPercentage. Finally the user finishes the conversion by allocating the csr_col_ind and csr_val arrays (whos size is determined by the value at nnz_total_dev_host_ptr) and calling hipsparseXpruneDense2csrByPercentage.

The pruning by percentage works by first sorting the absolute values of the dense matrix A. We then determine a position in this sorted array by

\[ pos = ceil(m*n*(percentage/100)) - 1 pos = min(pos, m*n-1) pos = max(pos, 0) threshold = sorted_A[pos] \]
Once we have this threshold we prune values in the dense matrix A as in hipsparseXpruneDense2csr. The routine does support asynchronous execution if the pointer mode is set to device.

hipsparseXdense2csc()#

hipsparseStatus_t hipsparseSdense2csc(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const float *A, int ld, const int *nnz_per_columns, float *csc_val, int *csc_row_ind, int *csc_col_ptr)#
hipsparseStatus_t hipsparseDdense2csc(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const double *A, int ld, const int *nnz_per_columns, double *csc_val, int *csc_row_ind, int *csc_col_ptr)#
hipsparseStatus_t hipsparseCdense2csc(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const hipComplex *A, int ld, const int *nnz_per_columns, hipComplex *csc_val, int *csc_row_ind, int *csc_col_ptr)#
hipsparseStatus_t hipsparseZdense2csc(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const hipDoubleComplex *A, int ld, const int *nnz_per_columns, hipDoubleComplex *csc_val, int *csc_row_ind, int *csc_col_ptr)#

This function converts the matrix A in dense format into a sparse matrix in CSC format. All the parameters are assumed to have been pre-allocated by the user and the arrays are filled in based on nnz_per_columns, which can be pre-computed with hipsparseXnnz(). It is executed asynchronously with respect to the host and may return control to the application on the host before the entire result is ready.

hipsparseXcsr2dense()#

hipsparseStatus_t hipsparseScsr2dense(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const float *csr_val, const int *csr_row_ptr, const int *csr_col_ind, float *A, int ld)#
hipsparseStatus_t hipsparseDcsr2dense(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const double *csr_val, const int *csr_row_ptr, const int *csr_col_ind, double *A, int ld)#
hipsparseStatus_t hipsparseCcsr2dense(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const hipComplex *csr_val, const int *csr_row_ptr, const int *csr_col_ind, hipComplex *A, int ld)#
hipsparseStatus_t hipsparseZcsr2dense(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const hipDoubleComplex *csr_val, const int *csr_row_ptr, const int *csr_col_ind, hipDoubleComplex *A, int ld)#

This function converts the sparse matrix in CSR format into a dense matrix. It is executed asynchronously with respect to the host and may return control to the application on the host before the entire result is ready.

hipsparseXcsc2dense()#

hipsparseStatus_t hipsparseScsc2dense(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const float *csc_val, const int *csc_row_ind, const int *csc_col_ptr, float *A, int ld)#
hipsparseStatus_t hipsparseDcsc2dense(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const double *csc_val, const int *csc_row_ind, const int *csc_col_ptr, double *A, int ld)#
hipsparseStatus_t hipsparseCcsc2dense(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const hipComplex *csc_val, const int *csc_row_ind, const int *csc_col_ptr, hipComplex *A, int ld)#
hipsparseStatus_t hipsparseZcsc2dense(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descr, const hipDoubleComplex *csc_val, const int *csc_row_ind, const int *csc_col_ptr, hipDoubleComplex *A, int ld)#

This function converts the sparse matrix in CSC format into a dense matrix. It is executed asynchronously with respect to the host and may return control to the application on the host before the entire result is ready.

hipsparseXcsr2bsrNnz()#

hipsparseStatus_t hipsparseXcsr2bsrNnz(hipsparseHandle_t handle, hipsparseDirection_t dirA, int m, int n, const hipsparseMatDescr_t descrA, const int *csrRowPtrA, const int *csrColIndA, int blockDim, const hipsparseMatDescr_t descrC, int *bsrRowPtrC, int *bsrNnzb)#

This function computes the number of nonzero block columns per row and the total number of nonzero blocks in a sparse BSR matrix given a sparse CSR matrix as input.

The routine does support asynchronous execution if the pointer mode is set to device.

hipsparseXcsr2bsr()#

hipsparseStatus_t hipsparseScsr2bsr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int m, int n, const hipsparseMatDescr_t descrA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, int blockDim, const hipsparseMatDescr_t descrC, float *bsrValC, int *bsrRowPtrC, int *bsrColIndC)#
hipsparseStatus_t hipsparseDcsr2bsr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int m, int n, const hipsparseMatDescr_t descrA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, int blockDim, const hipsparseMatDescr_t descrC, double *bsrValC, int *bsrRowPtrC, int *bsrColIndC)#
hipsparseStatus_t hipsparseCcsr2bsr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int m, int n, const hipsparseMatDescr_t descrA, const hipComplex *csrValA, const int *csrRowPtrA, const int *csrColIndA, int blockDim, const hipsparseMatDescr_t descrC, hipComplex *bsrValC, int *bsrRowPtrC, int *bsrColIndC)#
hipsparseStatus_t hipsparseZcsr2bsr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int m, int n, const hipsparseMatDescr_t descrA, const hipDoubleComplex *csrValA, const int *csrRowPtrA, const int *csrColIndA, int blockDim, const hipsparseMatDescr_t descrC, hipDoubleComplex *bsrValC, int *bsrRowPtrC, int *bsrColIndC)#

Convert a sparse CSR matrix into a sparse BSR matrix.

hipsparseXcsr2bsr converts a CSR matrix into a BSR matrix. It is assumed, that bsr_val, bsr_col_ind and bsr_row_ptr are allocated. Allocation size for bsr_row_ptr is computed as mb+1 where mb is the number of block rows in the BSR matrix. Allocation size for bsr_val and bsr_col_ind is computed using csr2bsr_nnz() which also fills in bsr_row_ptr.

hipsparseXcsr2bsr requires extra temporary storage that is allocated internally if block_dim>16

hipsparseXnnz_compress()#

hipsparseStatus_t hipsparseSnnz_compress(hipsparseHandle_t handle, int m, const hipsparseMatDescr_t descrA, const float *csrValA, const int *csrRowPtrA, int *nnzPerRow, int *nnzC, float tol)#
hipsparseStatus_t hipsparseDnnz_compress(hipsparseHandle_t handle, int m, const hipsparseMatDescr_t descrA, const double *csrValA, const int *csrRowPtrA, int *nnzPerRow, int *nnzC, double tol)#
hipsparseStatus_t hipsparseCnnz_compress(hipsparseHandle_t handle, int m, const hipsparseMatDescr_t descrA, const hipComplex *csrValA, const int *csrRowPtrA, int *nnzPerRow, int *nnzC, hipComplex tol)#
hipsparseStatus_t hipsparseZnnz_compress(hipsparseHandle_t handle, int m, const hipsparseMatDescr_t descrA, const hipDoubleComplex *csrValA, const int *csrRowPtrA, int *nnzPerRow, int *nnzC, hipDoubleComplex tol)#

Given a sparse CSR matrix and a non-negative tolerance, this function computes how many entries would be left in each row of the matrix if elements less than the tolerance were removed. It also computes the total number of remaining elements in the matrix.

hipsparseXcsr2coo()#

hipsparseStatus_t hipsparseXcsr2coo(hipsparseHandle_t handle, const int *csrRowPtr, int nnz, int m, int *cooRowInd, hipsparseIndexBase_t idxBase)#

Convert a sparse CSR matrix into a sparse COO matrix.

hipsparseXcsr2coo converts the CSR array containing the row offsets, that point to the start of every row, into a COO array of row indices.

Note

It can also be used to convert a CSC array containing the column offsets into a COO array of column indices.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcsr2csc()#

hipsparseStatus_t hipsparseScsr2csc(hipsparseHandle_t handle, int m, int n, int nnz, const float *csrSortedVal, const int *csrSortedRowPtr, const int *csrSortedColInd, float *cscSortedVal, int *cscSortedRowInd, int *cscSortedColPtr, hipsparseAction_t copyValues, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseDcsr2csc(hipsparseHandle_t handle, int m, int n, int nnz, const double *csrSortedVal, const int *csrSortedRowPtr, const int *csrSortedColInd, double *cscSortedVal, int *cscSortedRowInd, int *cscSortedColPtr, hipsparseAction_t copyValues, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseCcsr2csc(hipsparseHandle_t handle, int m, int n, int nnz, const hipComplex *csrSortedVal, const int *csrSortedRowPtr, const int *csrSortedColInd, hipComplex *cscSortedVal, int *cscSortedRowInd, int *cscSortedColPtr, hipsparseAction_t copyValues, hipsparseIndexBase_t idxBase)#
hipsparseStatus_t hipsparseZcsr2csc(hipsparseHandle_t handle, int m, int n, int nnz, const hipDoubleComplex *csrSortedVal, const int *csrSortedRowPtr, const int *csrSortedColInd, hipDoubleComplex *cscSortedVal, int *cscSortedRowInd, int *cscSortedColPtr, hipsparseAction_t copyValues, hipsparseIndexBase_t idxBase)#

Convert a sparse CSR matrix into a sparse CSC matrix.

hipsparseXcsr2csc converts a CSR matrix into a CSC matrix. hipsparseXcsr2csc can also be used to convert a CSC matrix into a CSR matrix. copy_values decides whether csc_val is being filled during conversion (HIPSPARSE_ACTION_NUMERIC) or not (HIPSPARSE_ACTION_SYMBOLIC).

Note

The resulting matrix can also be seen as the transpose of the input matrix.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcsr2hyb()#

hipsparseStatus_t hipsparseScsr2hyb(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descrA, const float *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, hipsparseHybMat_t hybA, int userEllWidth, hipsparseHybPartition_t partitionType)#
hipsparseStatus_t hipsparseDcsr2hyb(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descrA, const double *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, hipsparseHybMat_t hybA, int userEllWidth, hipsparseHybPartition_t partitionType)#
hipsparseStatus_t hipsparseCcsr2hyb(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descrA, const hipComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, hipsparseHybMat_t hybA, int userEllWidth, hipsparseHybPartition_t partitionType)#
hipsparseStatus_t hipsparseZcsr2hyb(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descrA, const hipDoubleComplex *csrSortedValA, const int *csrSortedRowPtrA, const int *csrSortedColIndA, hipsparseHybMat_t hybA, int userEllWidth, hipsparseHybPartition_t partitionType)#

Convert a sparse CSR matrix into a sparse HYB matrix.

hipsparseXcsr2hyb converts a CSR matrix into a HYB matrix. It is assumed that hyb has been initialized with hipsparseCreateHybMat().

Note

This function requires a significant amount of storage for the HYB matrix, depending on the matrix structure.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXgebsr2gebsc_bufferSize()#

hipsparseStatus_t hipsparseSgebsr2gebsc_bufferSize(hipsparseHandle_t handle, int mb, int nb, int nnzb, const float *bsr_val, const int *bsr_row_ptr, const int *bsr_col_ind, int row_block_dim, int col_block_dim, size_t *p_buffer_size)#
hipsparseStatus_t hipsparseDgebsr2gebsc_bufferSize(hipsparseHandle_t handle, int mb, int nb, int nnzb, const double *bsr_val, const int *bsr_row_ptr, const int *bsr_col_ind, int row_block_dim, int col_block_dim, size_t *p_buffer_size)#
hipsparseStatus_t hipsparseCgebsr2gebsc_bufferSize(hipsparseHandle_t handle, int mb, int nb, int nnzb, const hipComplex *bsr_val, const int *bsr_row_ptr, const int *bsr_col_ind, int row_block_dim, int col_block_dim, size_t *p_buffer_size)#
hipsparseStatus_t hipsparseZgebsr2gebsc_bufferSize(hipsparseHandle_t handle, int mb, int nb, int nnzb, const hipDoubleComplex *bsr_val, const int *bsr_row_ptr, const int *bsr_col_ind, int row_block_dim, int col_block_dim, size_t *p_buffer_size)#

Convert a sparse GEneral BSR matrix into a sparse GEneral BSC matrix.

hipsparseXgebsr2gebsc_bufferSize returns the size of the temporary storage buffer required by hipsparseXgebsr2gebsc(). The temporary storage buffer must be allocated by the user.

hipsparseXgebsr2gebsc()#

hipsparseStatus_t hipsparseSgebsr2gebsc(hipsparseHandle_t handle, int mb, int nb, int nnzb, const float *bsr_val, const int *bsr_row_ptr, const int *bsr_col_ind, int row_block_dim, int col_block_dim, float *bsc_val, int *bsc_row_ind, int *bsc_col_ptr, hipsparseAction_t copy_values, hipsparseIndexBase_t idx_base, void *temp_buffer)#
hipsparseStatus_t hipsparseDgebsr2gebsc(hipsparseHandle_t handle, int mb, int nb, int nnzb, const double *bsr_val, const int *bsr_row_ptr, const int *bsr_col_ind, int row_block_dim, int col_block_dim, double *bsc_val, int *bsc_row_ind, int *bsc_col_ptr, hipsparseAction_t copy_values, hipsparseIndexBase_t idx_base, void *temp_buffer)#
hipsparseStatus_t hipsparseCgebsr2gebsc(hipsparseHandle_t handle, int mb, int nb, int nnzb, const hipComplex *bsr_val, const int *bsr_row_ptr, const int *bsr_col_ind, int row_block_dim, int col_block_dim, hipComplex *bsc_val, int *bsc_row_ind, int *bsc_col_ptr, hipsparseAction_t copy_values, hipsparseIndexBase_t idx_base, void *temp_buffer)#
hipsparseStatus_t hipsparseZgebsr2gebsc(hipsparseHandle_t handle, int mb, int nb, int nnzb, const hipDoubleComplex *bsr_val, const int *bsr_row_ptr, const int *bsr_col_ind, int row_block_dim, int col_block_dim, hipDoubleComplex *bsc_val, int *bsc_row_ind, int *bsc_col_ptr, hipsparseAction_t copy_values, hipsparseIndexBase_t idx_base, void *temp_buffer)#

Convert a sparse GEneral BSR matrix into a sparse GEneral BSC matrix.

hipsparseXgebsr2gebsc converts a GEneral BSR matrix into a GEneral BSC matrix. hipsparseXgebsr2gebsc can also be used to convert a GEneral BSC matrix into a GEneral BSR matrix. copy_values decides whether bsc_val is being filled during conversion (HIPSPARSE_ACTION_NUMERIC) or not (HIPSPARSE_ACTION_SYMBOLIC).

hipsparseXgebsr2gebsc requires extra temporary storage buffer that has to be allocated by the user. Storage buffer size can be determined by hipsparseXgebsr2gebsc_bufferSize().

Note

The resulting matrix can also be seen as the transpose of the input matrix.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcsr2gebsr_bufferSize()#

hipsparseStatus_t hipsparseScsr2gebsr_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dir, int m, int n, const hipsparseMatDescr_t csr_descr, const float *csr_val, const int *csr_row_ptr, const int *csr_col_ind, int row_block_dim, int col_block_dim, size_t *p_buffer_size)#
hipsparseStatus_t hipsparseDcsr2gebsr_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dir, int m, int n, const hipsparseMatDescr_t csr_descr, const double *csr_val, const int *csr_row_ptr, const int *csr_col_ind, int row_block_dim, int col_block_dim, size_t *p_buffer_size)#
hipsparseStatus_t hipsparseCcsr2gebsr_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dir, int m, int n, const hipsparseMatDescr_t csr_descr, const hipComplex *csr_val, const int *csr_row_ptr, const int *csr_col_ind, int row_block_dim, int col_block_dim, size_t *p_buffer_size)#
hipsparseStatus_t hipsparseZcsr2gebsr_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dir, int m, int n, const hipsparseMatDescr_t csr_descr, const hipDoubleComplex *csr_val, const int *csr_row_ptr, const int *csr_col_ind, int row_block_dim, int col_block_dim, size_t *p_buffer_size)#

hipsparseXcsr2gebsr_bufferSize returns the size of the temporary buffer that is required by hipsparseXcsr2gebcsrNnz and hipsparseXcsr2gebcsr. The temporary storage buffer must be allocated by the user.

This function computes the number of nonzero block columns per row and the total number of nonzero blocks in a sparse GEneral BSR matrix given a sparse CSR matrix as input.

The routine does support asynchronous execution if the pointer mode is set to device.

hipsparseXcsr2gebsrNnz()#

hipsparseStatus_t hipsparseXcsr2gebsrNnz(hipsparseHandle_t handle, hipsparseDirection_t dir, int m, int n, const hipsparseMatDescr_t csr_descr, const int *csr_row_ptr, const int *csr_col_ind, const hipsparseMatDescr_t bsr_descr, int *bsr_row_ptr, int row_block_dim, int col_block_dim, int *bsr_nnz_devhost, void *p_buffer)#

This function computes the number of nonzero block columns per row and the total number of nonzero blocks in a sparse GEneral BSR matrix given a sparse CSR matrix as input.

hipsparseXcsr2gebsr()#

hipsparseStatus_t hipsparseScsr2gebsr(hipsparseHandle_t handle, hipsparseDirection_t dir, int m, int n, const hipsparseMatDescr_t csr_descr, const float *csr_val, const int *csr_row_ptr, const int *csr_col_ind, const hipsparseMatDescr_t bsr_descr, float *bsr_val, int *bsr_row_ptr, int *bsr_col_ind, int row_block_dim, int col_block_dim, void *p_buffer)#
hipsparseStatus_t hipsparseDcsr2gebsr(hipsparseHandle_t handle, hipsparseDirection_t dir, int m, int n, const hipsparseMatDescr_t csr_descr, const double *csr_val, const int *csr_row_ptr, const int *csr_col_ind, const hipsparseMatDescr_t bsr_descr, double *bsr_val, int *bsr_row_ptr, int *bsr_col_ind, int row_block_dim, int col_block_dim, void *p_buffer)#
hipsparseStatus_t hipsparseCcsr2gebsr(hipsparseHandle_t handle, hipsparseDirection_t dir, int m, int n, const hipsparseMatDescr_t csr_descr, const hipComplex *csr_val, const int *csr_row_ptr, const int *csr_col_ind, const hipsparseMatDescr_t bsr_descr, hipComplex *bsr_val, int *bsr_row_ptr, int *bsr_col_ind, int row_block_dim, int col_block_dim, void *p_buffer)#
hipsparseStatus_t hipsparseZcsr2gebsr(hipsparseHandle_t handle, hipsparseDirection_t dir, int m, int n, const hipsparseMatDescr_t csr_descr, const hipDoubleComplex *csr_val, const int *csr_row_ptr, const int *csr_col_ind, const hipsparseMatDescr_t bsr_descr, hipDoubleComplex *bsr_val, int *bsr_row_ptr, int *bsr_col_ind, int row_block_dim, int col_block_dim, void *p_buffer)#

Convert a sparse CSR matrix into a sparse GEneral BSR matrix.

hipsparseXcsr2gebsr converts a CSR matrix into a GEneral BSR matrix. It is assumed, that bsr_val, bsr_col_ind and bsr_row_ptr are allocated. Allocation size for bsr_row_ptr is computed as mb+1 where mb is the number of block rows in the GEneral BSR matrix. Allocation size for bsr_val and bsr_col_ind is computed using csr2gebsr_nnz() which also fills in bsr_row_ptr.

hipsparseXbsr2csr()#

hipsparseStatus_t hipsparseSbsr2csr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, const hipsparseMatDescr_t descrA, const float *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, const hipsparseMatDescr_t descrC, float *csrValC, int *csrRowPtrC, int *csrColIndC)#
hipsparseStatus_t hipsparseDbsr2csr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, const hipsparseMatDescr_t descrA, const double *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, const hipsparseMatDescr_t descrC, double *csrValC, int *csrRowPtrC, int *csrColIndC)#
hipsparseStatus_t hipsparseCbsr2csr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, const hipsparseMatDescr_t descrA, const hipComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, const hipsparseMatDescr_t descrC, hipComplex *csrValC, int *csrRowPtrC, int *csrColIndC)#
hipsparseStatus_t hipsparseZbsr2csr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, const hipsparseMatDescr_t descrA, const hipDoubleComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int blockDim, const hipsparseMatDescr_t descrC, hipDoubleComplex *csrValC, int *csrRowPtrC, int *csrColIndC)#

Convert a sparse BSR matrix into a sparse CSR matrix.

hipsparseXbsr2csr converts a BSR matrix into a CSR matrix. It is assumed, that csr_val, csr_col_ind and csr_row_ptr are allocated. Allocation size for csr_row_ptr is computed by the number of block rows multiplied by the block dimension plus one. Allocation for csr_val and csr_col_ind is computed by the the number of blocks in the BSR matrix multiplied by the block dimension squared.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXgebsr2csr()#

hipsparseStatus_t hipsparseSgebsr2csr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, const hipsparseMatDescr_t descrA, const float *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDim, int colBlockDim, const hipsparseMatDescr_t descrC, float *csrValC, int *csrRowPtrC, int *csrColIndC)#
hipsparseStatus_t hipsparseDgebsr2csr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, const hipsparseMatDescr_t descrA, const double *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDim, int colBlockDim, const hipsparseMatDescr_t descrC, double *csrValC, int *csrRowPtrC, int *csrColIndC)#
hipsparseStatus_t hipsparseCgebsr2csr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, const hipsparseMatDescr_t descrA, const hipComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDim, int colBlockDim, const hipsparseMatDescr_t descrC, hipComplex *csrValC, int *csrRowPtrC, int *csrColIndC)#
hipsparseStatus_t hipsparseZgebsr2csr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, const hipsparseMatDescr_t descrA, const hipDoubleComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDim, int colBlockDim, const hipsparseMatDescr_t descrC, hipDoubleComplex *csrValC, int *csrRowPtrC, int *csrColIndC)#

Convert a sparse general BSR matrix into a sparse CSR matrix.

hipsparseXgebsr2csr converts a BSR matrix into a CSR matrix. It is assumed, that csr_val, csr_col_ind and csr_row_ptr are allocated. Allocation size for csr_row_ptr is computed by the number of block rows multiplied by the block dimension plus one. Allocation for csr_val and csr_col_ind is computed by the the number of blocks in the BSR matrix multiplied by the product of the block dimensions.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcsr2csr_compress()#

hipsparseStatus_t hipsparseScsr2csr_compress(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descrA, const float *csrValA, const int *csrColIndA, const int *csrRowPtrA, int nnzA, const int *nnzPerRow, float *csrValC, int *csrColIndC, int *csrRowPtrC, float tol)#
hipsparseStatus_t hipsparseDcsr2csr_compress(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descrA, const double *csrValA, const int *csrColIndA, const int *csrRowPtrA, int nnzA, const int *nnzPerRow, double *csrValC, int *csrColIndC, int *csrRowPtrC, double tol)#
hipsparseStatus_t hipsparseCcsr2csr_compress(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descrA, const hipComplex *csrValA, const int *csrColIndA, const int *csrRowPtrA, int nnzA, const int *nnzPerRow, hipComplex *csrValC, int *csrColIndC, int *csrRowPtrC, hipComplex tol)#
hipsparseStatus_t hipsparseZcsr2csr_compress(hipsparseHandle_t handle, int m, int n, const hipsparseMatDescr_t descrA, const hipDoubleComplex *csrValA, const int *csrColIndA, const int *csrRowPtrA, int nnzA, const int *nnzPerRow, hipDoubleComplex *csrValC, int *csrColIndC, int *csrRowPtrC, hipDoubleComplex tol)#

Convert a sparse CSR matrix into a compressed sparse CSR matrix.

hipsparseXcsr2csr_compress converts a CSR matrix into a compressed CSR matrix by removing entries in the input CSR matrix that are below a non-negative threshold tol

Note

In the case of complex matrices only the magnitude of the real part of tol is used.

hipsparseXpruneCsr2csr_bufferSize()#

hipsparseStatus_t hipsparseSpruneCsr2csr_bufferSize(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, const float *threshold, const hipsparseMatDescr_t descrC, const float *csrValC, const int *csrRowPtrC, const int *csrColIndC, size_t *bufferSize)#
hipsparseStatus_t hipsparseDpruneCsr2csr_bufferSize(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, const double *threshold, const hipsparseMatDescr_t descrC, const double *csrValC, const int *csrRowPtrC, const int *csrColIndC, size_t *bufferSize)#

Convert and prune sparse CSR matrix into a sparse CSR matrix.

hipsparseXpruneCsr2csr_bufferSize returns the size of the temporary buffer that is required by hipsparseXpruneCsr2csrNnz and hipsparseXpruneCsr2csr. The temporary storage buffer must be allocated by the user.

hipsparseXpruneCsr2csr_bufferSizeExt()#

hipsparseStatus_t hipsparseSpruneCsr2csr_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, const float *threshold, const hipsparseMatDescr_t descrC, const float *csrValC, const int *csrRowPtrC, const int *csrColIndC, size_t *bufferSize)#
hipsparseStatus_t hipsparseDpruneCsr2csr_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, const double *threshold, const hipsparseMatDescr_t descrC, const double *csrValC, const int *csrRowPtrC, const int *csrColIndC, size_t *bufferSize)#

Convert and prune sparse CSR matrix into a sparse CSR matrix.

hipsparseXpruneCsr2csr_bufferSizeExt returns the size of the temporary buffer that is required by hipsparseXpruneCsr2csrNnz and hipsparseXpruneCsr2csr. The temporary storage buffer must be allocated by the user.

hipsparseXpruneCsr2csrNnz()#

hipsparseStatus_t hipsparseSpruneCsr2csrNnz(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, const float *threshold, const hipsparseMatDescr_t descrC, int *csrRowPtrC, int *nnzTotalDevHostPtr, void *buffer)#
hipsparseStatus_t hipsparseDpruneCsr2csrNnz(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, const double *threshold, const hipsparseMatDescr_t descrC, int *csrRowPtrC, int *nnzTotalDevHostPtr, void *buffer)#

Convert and prune sparse CSR matrix into a sparse CSR matrix.

hipsparseXpruneCsr2csrNnz computes the number of nonzero elements per row and the total number of nonzero elements in a sparse CSR matrix once elements less than the threshold are pruned from the matrix.

Note

The routine does support asynchronous execution if the pointer mode is set to device.

hipsparseXpruneCsr2csr()#

hipsparseStatus_t hipsparseSpruneCsr2csr(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, const float *threshold, const hipsparseMatDescr_t descrC, float *csrValC, const int *csrRowPtrC, int *csrColIndC, void *buffer)#
hipsparseStatus_t hipsparseDpruneCsr2csr(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, const double *threshold, const hipsparseMatDescr_t descrC, double *csrValC, const int *csrRowPtrC, int *csrColIndC, void *buffer)#

Convert and prune sparse CSR matrix into a sparse CSR matrix.

This function converts the sparse CSR matrix A into a sparse CSR matrix C by pruning values in A that are less than the threshold. All the parameters are assumed to have been pre-allocated by the user. The user first calls hipsparseXpruneCsr2csr_bufferSize() to determine the size of the buffer used by hipsparseXpruneCsr2csrNnz() and hipsparseXpruneCsr2csr() which the user then allocates. The user then allocates csr_row_ptr_C to have m+1 elements and then calls hipsparseXpruneCsr2csrNnz() which fills in the csr_row_ptr_C array stores then number of elements that are larger than the pruning threshold in nnz_total_dev_host_ptr. The user then calls hipsparseXpruneCsr2csr() to complete the conversion. It is executed asynchronously with respect to the host and may return control to the application on the host before the entire result is ready.

hipsparseXpruneCsr2csrByPercentage_bufferSize()#

hipsparseStatus_t hipsparseSpruneCsr2csrByPercentage_bufferSize(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, float percentage, const hipsparseMatDescr_t descrC, const float *csrValC, const int *csrRowPtrC, const int *csrColIndC, pruneInfo_t info, size_t *bufferSize)#
hipsparseStatus_t hipsparseDpruneCsr2csrByPercentage_bufferSize(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, double percentage, const hipsparseMatDescr_t descrC, const double *csrValC, const int *csrRowPtrC, const int *csrColIndC, pruneInfo_t info, size_t *bufferSize)#

Convert and prune by percentage a sparse CSR matrix into a sparse CSR matrix.

hipsparseXpruneCsr2csrByPercentage_bufferSize returns the size of the temporary buffer that is required by hipsparseXpruneCsr2csrNnzByPercentage. The temporary storage buffer must be allocated by the user.

hipsparseXpruneCsr2csrByPercentage_bufferSizeExt()#

hipsparseStatus_t hipsparseSpruneCsr2csrByPercentage_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, float percentage, const hipsparseMatDescr_t descrC, const float *csrValC, const int *csrRowPtrC, const int *csrColIndC, pruneInfo_t info, size_t *bufferSize)#
hipsparseStatus_t hipsparseDpruneCsr2csrByPercentage_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, double percentage, const hipsparseMatDescr_t descrC, const double *csrValC, const int *csrRowPtrC, const int *csrColIndC, pruneInfo_t info, size_t *bufferSize)#

Convert and prune by percentage a sparse CSR matrix into a sparse CSR matrix.

hipsparseXpruneCsr2csrByPercentage_bufferSizeExt returns the size of the temporary buffer that is required by hipsparseXpruneCsr2csrNnzByPercentage. The temporary storage buffer must be allocated by the user.

hipsparseXpruneCsr2csrNnzByPercentage()#

hipsparseStatus_t hipsparseSpruneCsr2csrNnzByPercentage(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, float percentage, const hipsparseMatDescr_t descrC, int *csrRowPtrC, int *nnzTotalDevHostPtr, pruneInfo_t info, void *buffer)#
hipsparseStatus_t hipsparseDpruneCsr2csrNnzByPercentage(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, double percentage, const hipsparseMatDescr_t descrC, int *csrRowPtrC, int *nnzTotalDevHostPtr, pruneInfo_t info, void *buffer)#

Convert and prune by percentage a sparse CSR matrix into a sparse CSR matrix.

hipsparseXpruneCsr2csrNnzByPercentage computes the number of nonzero elements per row and the total number of nonzero elements in a sparse CSR matrix once elements less than the threshold are pruned from the matrix.

Note

The routine does support asynchronous execution if the pointer mode is set to device.

hipsparseXpruneCsr2csrByPercentage()#

hipsparseStatus_t hipsparseSpruneCsr2csrByPercentage(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, float percentage, const hipsparseMatDescr_t descrC, float *csrValC, const int *csrRowPtrC, int *csrColIndC, pruneInfo_t info, void *buffer)#
hipsparseStatus_t hipsparseDpruneCsr2csrByPercentage(hipsparseHandle_t handle, int m, int n, int nnzA, const hipsparseMatDescr_t descrA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, double percentage, const hipsparseMatDescr_t descrC, double *csrValC, const int *csrRowPtrC, int *csrColIndC, pruneInfo_t info, void *buffer)#

Convert and prune by percentage a sparse CSR matrix into a sparse CSR matrix.

This function converts the sparse CSR matrix A into a sparse CSR matrix C by pruning values in A that are less than the threshold. All the parameters are assumed to have been pre-allocated by the user. The user first calls hipsparseXpruneCsr2csr_bufferSize() to determine the size of the buffer used by hipsparseXpruneCsr2csrNnz() and hipsparseXpruneCsr2csr() which the user then allocates. The user then allocates csr_row_ptr_C to have m+1 elements and then calls hipsparseXpruneCsr2csrNnz() which fills in the csr_row_ptr_C array stores then number of elements that are larger than the pruning threshold in nnz_total_dev_host_ptr. The user then calls hipsparseXpruneCsr2csr() to complete the conversion. It is executed asynchronously with respect to the host and may return control to the application on the host before the entire result is ready.

hipsparseXhyb2csr()#

hipsparseStatus_t hipsparseShyb2csr(hipsparseHandle_t handle, const hipsparseMatDescr_t descrA, const hipsparseHybMat_t hybA, float *csrSortedValA, int *csrSortedRowPtrA, int *csrSortedColIndA)#
hipsparseStatus_t hipsparseDhyb2csr(hipsparseHandle_t handle, const hipsparseMatDescr_t descrA, const hipsparseHybMat_t hybA, double *csrSortedValA, int *csrSortedRowPtrA, int *csrSortedColIndA)#
hipsparseStatus_t hipsparseChyb2csr(hipsparseHandle_t handle, const hipsparseMatDescr_t descrA, const hipsparseHybMat_t hybA, hipComplex *csrSortedValA, int *csrSortedRowPtrA, int *csrSortedColIndA)#
hipsparseStatus_t hipsparseZhyb2csr(hipsparseHandle_t handle, const hipsparseMatDescr_t descrA, const hipsparseHybMat_t hybA, hipDoubleComplex *csrSortedValA, int *csrSortedRowPtrA, int *csrSortedColIndA)#

Convert a sparse HYB matrix into a sparse CSR matrix.

hipsparseXhyb2csr converts a HYB matrix into a CSR matrix.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcoo2csr()#

hipsparseStatus_t hipsparseXcoo2csr(hipsparseHandle_t handle, const int *cooRowInd, int nnz, int m, int *csrRowPtr, hipsparseIndexBase_t idxBase)#

Convert a sparse COO matrix into a sparse CSR matrix.

hipsparseXcoo2csr converts the COO array containing the row indices into a CSR array of row offsets, that point to the start of every row. It is assumed that the COO row index array is sorted.

Note

It can also be used, to convert a COO array containing the column indices into a CSC array of column offsets, that point to the start of every column. Then, it is assumed that the COO column index array is sorted, instead.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseCreateIdentityPermutation()#

hipsparseStatus_t hipsparseCreateIdentityPermutation(hipsparseHandle_t handle, int n, int *p)#

Create the identity map.

hipsparseCreateIdentityPermutation stores the identity map in p, such that \(p = 0:1:(n-1)\).

for(i = 0; i < n; ++i)
{
    p[i] = i;
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcsrsort_bufferSizeExt()#

hipsparseStatus_t hipsparseXcsrsort_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int nnz, const int *csrRowPtr, const int *csrColInd, size_t *pBufferSizeInBytes)#

Sort a sparse CSR matrix.

hipsparseXcsrsort_bufferSizeExt returns the size of the temporary storage buffer required by hipsparseXcsrsort(). The temporary storage buffer must be allocated by the user.

hipsparseXcsrsort()#

hipsparseStatus_t hipsparseXcsrsort(hipsparseHandle_t handle, int m, int n, int nnz, const hipsparseMatDescr_t descrA, const int *csrRowPtr, int *csrColInd, int *P, void *pBuffer)#

Sort a sparse CSR matrix.

hipsparseXcsrsort sorts a matrix in CSR format. The sorted permutation vector perm can be used to obtain sorted csr_val array. In this case, perm must be initialized as the identity permutation, see hipsparseCreateIdentityPermutation().

hipsparseXcsrsort requires extra temporary storage buffer that has to be allocated by the user. Storage buffer size can be determined by hipsparseXcsrsort_bufferSizeExt().

Note

perm can be NULL if a sorted permutation vector is not required.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcscsort_bufferSizeExt()#

hipsparseStatus_t hipsparseXcscsort_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int nnz, const int *cscColPtr, const int *cscRowInd, size_t *pBufferSizeInBytes)#

Sort a sparse CSC matrix.

hipsparseXcscsort_bufferSizeExt returns the size of the temporary storage buffer required by hipsparseXcscsort(). The temporary storage buffer must be allocated by the user.

hipsparseXcscsort()#

hipsparseStatus_t hipsparseXcscsort(hipsparseHandle_t handle, int m, int n, int nnz, const hipsparseMatDescr_t descrA, const int *cscColPtr, int *cscRowInd, int *P, void *pBuffer)#

Sort a sparse CSC matrix.

hipsparseXcscsort sorts a matrix in CSC format. The sorted permutation vector perm can be used to obtain sorted csc_val array. In this case, perm must be initialized as the identity permutation, see hipsparseCreateIdentityPermutation().

hipsparseXcscsort requires extra temporary storage buffer that has to be allocated by the user. Storage buffer size can be determined by hipsparseXcscsort_bufferSizeExt().

Note

perm can be NULL if a sorted permutation vector is not required.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcoosort_bufferSizeExt()#

hipsparseStatus_t hipsparseXcoosort_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int nnz, const int *cooRows, const int *cooCols, size_t *pBufferSizeInBytes)#

Sort a sparse COO matrix.

hipsparseXcoosort_bufferSizeExt returns the size of the temporary storage buffer required by hipsparseXcoosort(). The temporary storage buffer must be allocated by the user.

hipsparseXcoosortByRow()#

hipsparseStatus_t hipsparseXcoosortByRow(hipsparseHandle_t handle, int m, int n, int nnz, int *cooRows, int *cooCols, int *P, void *pBuffer)#

Sort a sparse COO matrix by row.

hipsparseXcoosortByRow sorts a matrix in COO format by row. The sorted permutation vector perm can be used to obtain sorted coo_val array. In this case, perm must be initialized as the identity permutation, see hipsparseCreateIdentityPermutation().

hipsparseXcoosortByRow requires extra temporary storage buffer that has to be allocated by the user. Storage buffer size can be determined by hipsparseXcoosort_bufferSizeExt().

Note

perm can be NULL if a sorted permutation vector is not required.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXcoosortByColumn()#

hipsparseStatus_t hipsparseXcoosortByColumn(hipsparseHandle_t handle, int m, int n, int nnz, int *cooRows, int *cooCols, int *P, void *pBuffer)#

Sort a sparse COO matrix by column.

hipsparseXcoosortByColumn sorts a matrix in COO format by column. The sorted permutation vector perm can be used to obtain sorted coo_val array. In this case, perm must be initialized as the identity permutation, see hipsparseCreateIdentityPermutation().

hipsparseXcoosortByColumn requires extra temporary storage buffer that has to be allocated by the user. Storage buffer size can be determined by hipsparseXcoosort_bufferSizeExt().

Note

perm can be NULL if a sorted permutation vector is not required.

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

hipsparseXgebsr2gebsr_bufferSize()#

hipsparseStatus_t hipsparseSgebsr2gebsr_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, int nnzb, const hipsparseMatDescr_t descrA, const float *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDimA, int colBlockDimA, int rowBlockDimC, int colBlockDimC, int *bufferSize)#
hipsparseStatus_t hipsparseDgebsr2gebsr_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, int nnzb, const hipsparseMatDescr_t descrA, const double *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDimA, int colBlockDimA, int rowBlockDimC, int colBlockDimC, int *bufferSize)#
hipsparseStatus_t hipsparseCgebsr2gebsr_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, int nnzb, const hipsparseMatDescr_t descrA, const hipComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDimA, int colBlockDimA, int rowBlockDimC, int colBlockDimC, int *bufferSize)#
hipsparseStatus_t hipsparseZgebsr2gebsr_bufferSize(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, int nnzb, const hipsparseMatDescr_t descrA, const hipDoubleComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDimA, int colBlockDimA, int rowBlockDimC, int colBlockDimC, int *bufferSize)#

This function computes the the size of the user allocated temporary storage buffer used when converting a sparse general BSR matrix to another sparse general BSR matrix.

hipsparseXgebsr2gebsr_bufferSize returns the size of the temporary storage buffer that is required by hipsparseXgebsr2gebsrNnz() and hipsparseXgebsr2gebsr(). The temporary storage buffer must be allocated by the user.

hipsparseXgebsr2gebsrNnz()#

hipsparseStatus_t hipsparseXgebsr2gebsrNnz(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, int nnzb, const hipsparseMatDescr_t descrA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDimA, int colBlockDimA, const hipsparseMatDescr_t descrC, int *bsrRowPtrC, int rowBlockDimC, int colBlockDimC, int *nnzTotalDevHostPtr, void *buffer)#

This function is used when converting a general BSR sparse matrix A to another general BSR sparse matrix C. Specifically, this function determines the number of non-zero blocks that will exist in C (stored using either a host or device pointer), and computes the row pointer array for C.

The routine does support asynchronous execution.

hipsparseXgebsr2gebsr()#

hipsparseStatus_t hipsparseSgebsr2gebsr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, int nnzb, const hipsparseMatDescr_t descrA, const float *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDimA, int colBlockDimA, const hipsparseMatDescr_t descrC, float *bsrValC, int *bsrRowPtrC, int *bsrColIndC, int rowBlockDimC, int colBlockDimC, void *buffer)#
hipsparseStatus_t hipsparseDgebsr2gebsr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, int nnzb, const hipsparseMatDescr_t descrA, const double *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDimA, int colBlockDimA, const hipsparseMatDescr_t descrC, double *bsrValC, int *bsrRowPtrC, int *bsrColIndC, int rowBlockDimC, int colBlockDimC, void *buffer)#
hipsparseStatus_t hipsparseCgebsr2gebsr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, int nnzb, const hipsparseMatDescr_t descrA, const hipComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDimA, int colBlockDimA, const hipsparseMatDescr_t descrC, hipComplex *bsrValC, int *bsrRowPtrC, int *bsrColIndC, int rowBlockDimC, int colBlockDimC, void *buffer)#
hipsparseStatus_t hipsparseZgebsr2gebsr(hipsparseHandle_t handle, hipsparseDirection_t dirA, int mb, int nb, int nnzb, const hipsparseMatDescr_t descrA, const hipDoubleComplex *bsrValA, const int *bsrRowPtrA, const int *bsrColIndA, int rowBlockDimA, int colBlockDimA, const hipsparseMatDescr_t descrC, hipDoubleComplex *bsrValC, int *bsrRowPtrC, int *bsrColIndC, int rowBlockDimC, int colBlockDimC, void *buffer)#

This function converts the general BSR sparse matrix A to another general BSR sparse matrix C.

The conversion uses three steps. First, the user calls hipsparseXgebsr2gebsr_bufferSize() to determine the size of the required temporary storage buffer. The user then allocates this buffer. Secondly, the user then allocates mb_C+1 integers for the row pointer array for C where mb_C=(m+row_block_dim_C-1)/row_block_dim_C. The user then calls hipsparseXgebsr2gebsrNnz() to fill in the row pointer array for C ( bsr_row_ptr_C ) and determine the number of non-zero blocks that will exist in C. Finally, the user allocates space for the colimn indices array of C to have nnzb_C elements and space for the values array of C to have nnzb_C*roc_block_dim_C*col_block_dim_C and then calls hipsparseXgebsr2gebsr() to complete the conversion.

hipsparseXcsru2csr_bufferSizeExt()#

hipsparseStatus_t hipsparseScsru2csr_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int nnz, float *csrVal, const int *csrRowPtr, int *csrColInd, csru2csrInfo_t info, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseDcsru2csr_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int nnz, double *csrVal, const int *csrRowPtr, int *csrColInd, csru2csrInfo_t info, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseCcsru2csr_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int nnz, hipComplex *csrVal, const int *csrRowPtr, int *csrColInd, csru2csrInfo_t info, size_t *pBufferSizeInBytes)#
hipsparseStatus_t hipsparseZcsru2csr_bufferSizeExt(hipsparseHandle_t handle, int m, int n, int nnz, hipDoubleComplex *csrVal, const int *csrRowPtr, int *csrColInd, csru2csrInfo_t info, size_t *pBufferSizeInBytes)#

This function calculates the amount of temporary storage required for hipsparseXcsru2csr() and hipsparseXcsr2csru().

hipsparseXcsru2csr()#

hipsparseStatus_t hipsparseScsru2csr(hipsparseHandle_t handle, int m, int n, int nnz, const hipsparseMatDescr_t descrA, float *csrVal, const int *csrRowPtr, int *csrColInd, csru2csrInfo_t info, void *pBuffer)#
hipsparseStatus_t hipsparseDcsru2csr(hipsparseHandle_t handle, int m, int n, int nnz, const hipsparseMatDescr_t descrA, double *csrVal, const int *csrRowPtr, int *csrColInd, csru2csrInfo_t info, void *pBuffer)#
hipsparseStatus_t hipsparseCcsru2csr(hipsparseHandle_t handle, int m, int n, int nnz, const hipsparseMatDescr_t descrA, hipComplex *csrVal, const int *csrRowPtr, int *csrColInd, csru2csrInfo_t info, void *pBuffer)#
hipsparseStatus_t hipsparseZcsru2csr(hipsparseHandle_t handle, int m, int n, int nnz, const hipsparseMatDescr_t descrA, hipDoubleComplex *csrVal, const int *csrRowPtr, int *csrColInd, csru2csrInfo_t info, void *pBuffer)#

This function converts unsorted CSR format to sorted CSR format. The required temporary storage has to be allocated by the user.

hipsparseXcsr2csru()#

hipsparseStatus_t hipsparseScsr2csru(hipsparseHandle_t handle, int m, int n, int nnz, const hipsparseMatDescr_t descrA, float *csrVal, const int *csrRowPtr, int *csrColInd, csru2csrInfo_t info, void *pBuffer)#
hipsparseStatus_t hipsparseDcsr2csru(hipsparseHandle_t handle, int m, int n, int nnz, const hipsparseMatDescr_t descrA, double *csrVal, const int *csrRowPtr, int *csrColInd, csru2csrInfo_t info, void *pBuffer)#
hipsparseStatus_t hipsparseCcsr2csru(hipsparseHandle_t handle, int m, int n, int nnz, const hipsparseMatDescr_t descrA, hipComplex *csrVal, const int *csrRowPtr, int *csrColInd, csru2csrInfo_t info, void *pBuffer)#
hipsparseStatus_t hipsparseZcsr2csru(hipsparseHandle_t handle, int m, int n, int nnz, const hipsparseMatDescr_t descrA, hipDoubleComplex *csrVal, const int *csrRowPtr, int *csrColInd, csru2csrInfo_t info, void *pBuffer)#

This function converts sorted CSR format to unsorted CSR format. The required temporary storage has to be allocated by the user.

Sparse Reordering Functions#

This module holds all sparse reordering routines.

hipsparseXcsrcolor()#

hipsparseStatus_t hipsparseScsrcolor(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, const float *csrValA, const int *csrRowPtrA, const int *csrColIndA, const float *fractionToColor, int *ncolors, int *coloring, int *reordering, hipsparseColorInfo_t info)#
hipsparseStatus_t hipsparseDcsrcolor(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, const double *csrValA, const int *csrRowPtrA, const int *csrColIndA, const double *fractionToColor, int *ncolors, int *coloring, int *reordering, hipsparseColorInfo_t info)#
hipsparseStatus_t hipsparseCcsrcolor(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, const hipComplex *csrValA, const int *csrRowPtrA, const int *csrColIndA, const float *fractionToColor, int *ncolors, int *coloring, int *reordering, hipsparseColorInfo_t info)#
hipsparseStatus_t hipsparseZcsrcolor(hipsparseHandle_t handle, int m, int nnz, const hipsparseMatDescr_t descrA, const hipDoubleComplex *csrValA, const int *csrRowPtrA, const int *csrColIndA, const double *fractionToColor, int *ncolors, int *coloring, int *reordering, hipsparseColorInfo_t info)#

Coloring of the adjacency graph of the matrix \(A\) stored in the CSR format.

hipsparseXcsrcolor performs the coloring of the undirected graph represented by the (symmetric) sparsity pattern of the matrix \(A\) stored in CSR format. Graph coloring is a way of coloring the nodes of a graph such that no two adjacent nodes are of the same color. The fraction_to_color is a parameter to only color a given percentage of the graph nodes, the remaining uncolored nodes receive distinct new colors. The optional reordering array is a permutation array such that unknowns of the same color are grouped. The matrix \(A\) must be stored as a general matrix with a symmetric sparsity pattern, and if the matrix \(A\) is non-symmetric then the user is responsible to provide the symmetric part \(\frac{A+A^T}{2}\).

Sparse Generic Functions#

This module holds all sparse generic routines.

The sparse generic routines describe operations that manipulate sparse matrices.

hipsparseAxpby()#

hipsparseStatus_t hipsparseAxpby(hipsparseHandle_t handle, const void *alpha, hipsparseSpVecDescr_t vecX, const void *beta, hipsparseDnVecDescr_t vecY)#

hipsparseGather()#

hipsparseStatus_t hipsparseGather(hipsparseHandle_t handle, hipsparseDnVecDescr_t vecY, hipsparseSpVecDescr_t vecX)#

hipsparseScatter()#

hipsparseStatus_t hipsparseScatter(hipsparseHandle_t handle, hipsparseSpVecDescr_t vecX, hipsparseDnVecDescr_t vecY)#

hipsparseRot()#

hipsparseStatus_t hipsparseRot(hipsparseHandle_t handle, const void *c_coeff, const void *s_coeff, hipsparseSpVecDescr_t vecX, hipsparseDnVecDescr_t vecY)#

hipsparseSparseToDense_bufferSize()#

hipsparseStatus_t hipsparseSparseToDense_bufferSize(hipsparseHandle_t handle, hipsparseSpMatDescr_t matA, hipsparseDnMatDescr_t matB, hipsparseSparseToDenseAlg_t alg, size_t *bufferSize)#

hipsparseSparseToDense()#

hipsparseStatus_t hipsparseSparseToDense(hipsparseHandle_t handle, hipsparseSpMatDescr_t matA, hipsparseDnMatDescr_t matB, hipsparseSparseToDenseAlg_t alg, void *externalBuffer)#

hipsparseDenseToSparse_bufferSize()#

hipsparseStatus_t hipsparseDenseToSparse_bufferSize(hipsparseHandle_t handle, hipsparseDnMatDescr_t matA, hipsparseSpMatDescr_t matB, hipsparseDenseToSparseAlg_t alg, size_t *bufferSize)#

hipsparseDenseToSparse_analysis()#

hipsparseStatus_t hipsparseDenseToSparse_analysis(hipsparseHandle_t handle, hipsparseDnMatDescr_t matA, hipsparseSpMatDescr_t matB, hipsparseDenseToSparseAlg_t alg, void *externalBuffer)#

hipsparseDenseToSparse_convert()#

hipsparseStatus_t hipsparseDenseToSparse_convert(hipsparseHandle_t handle, hipsparseDnMatDescr_t matA, hipsparseSpMatDescr_t matB, hipsparseDenseToSparseAlg_t alg, void *externalBuffer)#

hipsparseSpVV_bufferSize()#

hipsparseStatus_t hipsparseSpVV_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t opX, hipsparseSpVecDescr_t vecX, hipsparseDnVecDescr_t vecY, void *result, hipDataType computeType, size_t *bufferSize)#

hipsparseSpVV()#

hipsparseStatus_t hipsparseSpVV(hipsparseHandle_t handle, hipsparseOperation_t opX, hipsparseSpVecDescr_t vecX, hipsparseDnVecDescr_t vecY, void *result, hipDataType computeType, void *externalBuffer)#

hipsparseSpMV_bufferSize()#

hipsparseStatus_t hipsparseSpMV_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t opA, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnVecDescr_t vecX, const void *beta, const hipsparseDnVecDescr_t vecY, hipDataType computeType, hipsparseSpMVAlg_t alg, size_t *bufferSize)#

hipsparseSpMV()#

hipsparseStatus_t hipsparseSpMV(hipsparseHandle_t handle, hipsparseOperation_t opA, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnVecDescr_t vecX, const void *beta, const hipsparseDnVecDescr_t vecY, hipDataType computeType, hipsparseSpMVAlg_t alg, void *externalBuffer)#

hipsparseSpMM_bufferSize()#

hipsparseStatus_t hipsparseSpMM_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnMatDescr_t matB, const void *beta, const hipsparseDnMatDescr_t matC, hipDataType computeType, hipsparseSpMMAlg_t alg, size_t *bufferSize)#

hipsparseSpMM_preprocess()#

hipsparseStatus_t hipsparseSpMM_preprocess(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnMatDescr_t matB, const void *beta, const hipsparseDnMatDescr_t matC, hipDataType computeType, hipsparseSpMMAlg_t alg, void *externalBuffer)#

hipsparseSpMM()#

hipsparseStatus_t hipsparseSpMM(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnMatDescr_t matB, const void *beta, const hipsparseDnMatDescr_t matC, hipDataType computeType, hipsparseSpMMAlg_t alg, void *externalBuffer)#

hipsparseSpGEMM_createDescr()#

hipsparseStatus_t hipsparseSpGEMM_createDescr(hipsparseSpGEMMDescr_t *descr)#

hipsparseSpGEMM_destroyDescr()#

hipsparseStatus_t hipsparseSpGEMM_destroyDescr(hipsparseSpGEMMDescr_t descr)#

hipsparseSpGEMM_workEstimation()#

hipsparseStatus_t hipsparseSpGEMM_workEstimation(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, hipsparseSpMatDescr_t matA, hipsparseSpMatDescr_t matB, const void *beta, hipsparseSpMatDescr_t matC, hipDataType computeType, hipsparseSpGEMMAlg_t alg, hipsparseSpGEMMDescr_t spgemmDescr, size_t *bufferSize1, void *externalBuffer1)#

hipsparseSpGEMM_compute()#

hipsparseStatus_t hipsparseSpGEMM_compute(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, hipsparseSpMatDescr_t matA, hipsparseSpMatDescr_t matB, const void *beta, hipsparseSpMatDescr_t matC, hipDataType computeType, hipsparseSpGEMMAlg_t alg, hipsparseSpGEMMDescr_t spgemmDescr, size_t *bufferSize2, void *externalBuffer2)#

hipsparseSpGEMM_copy()#

hipsparseStatus_t hipsparseSpGEMM_copy(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, hipsparseSpMatDescr_t matA, hipsparseSpMatDescr_t matB, const void *beta, hipsparseSpMatDescr_t matC, hipDataType computeType, hipsparseSpGEMMAlg_t alg, hipsparseSpGEMMDescr_t spgemmDescr)#

hipsparseSDDMM_bufferSize()#

hipsparseStatus_t hipsparseSDDMM_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseDnMatDescr_t A, const hipsparseDnMatDescr_t B, const void *beta, hipsparseSpMatDescr_t C, hipDataType computeType, hipsparseSDDMMAlg_t alg, size_t *bufferSize)#

hipsparseSDDMM_preprocess()#

hipsparseStatus_t hipsparseSDDMM_preprocess(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseDnMatDescr_t A, const hipsparseDnMatDescr_t B, const void *beta, hipsparseSpMatDescr_t C, hipDataType computeType, hipsparseSDDMMAlg_t alg, void *tempBuffer)#

hipsparseSDDMM()#

hipsparseStatus_t hipsparseSDDMM(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseDnMatDescr_t A, const hipsparseDnMatDescr_t B, const void *beta, hipsparseSpMatDescr_t C, hipDataType computeType, hipsparseSDDMMAlg_t alg, void *tempBuffer)#

hipsparseSpSV_createDescr()#

hipsparseStatus_t hipsparseSpSV_createDescr(hipsparseSpSVDescr_t *descr)#

hipsparseSpSV_destroyDescr()#

hipsparseStatus_t hipsparseSpSV_destroyDescr(hipsparseSpSVDescr_t descr)#

hipsparseSpSV_bufferSize()#

hipsparseStatus_t hipsparseSpSV_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t opA, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnVecDescr_t x, const hipsparseDnVecDescr_t y, hipDataType computeType, hipsparseSpSVAlg_t alg, hipsparseSpSVDescr_t spsvDescr, size_t *bufferSize)#

hipsparseSpSV_analysis()#

hipsparseStatus_t hipsparseSpSV_analysis(hipsparseHandle_t handle, hipsparseOperation_t opA, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnVecDescr_t x, const hipsparseDnVecDescr_t y, hipDataType computeType, hipsparseSpSVAlg_t alg, hipsparseSpSVDescr_t spsvDescr, void *externalBuffer)#

hipsparseSpSV_solve()#

hipsparseStatus_t hipsparseSpSV_solve(hipsparseHandle_t handle, hipsparseOperation_t opA, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnVecDescr_t x, const hipsparseDnVecDescr_t y, hipDataType computeType, hipsparseSpSVAlg_t alg, hipsparseSpSVDescr_t spsvDescr, void *externalBuffer)#

hipsparseSpSM_createDescr()#

hipsparseStatus_t hipsparseSpSM_createDescr(hipsparseSpSMDescr_t *descr)#

hipsparseSpSM_destroyDescr()#

hipsparseStatus_t hipsparseSpSM_destroyDescr(hipsparseSpSMDescr_t descr)#

hipsparseSpSM_bufferSize()#

hipsparseStatus_t hipsparseSpSM_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnMatDescr_t matB, const hipsparseDnMatDescr_t matC, hipDataType computeType, hipsparseSpSMAlg_t alg, hipsparseSpSMDescr_t spsmDescr, size_t *bufferSize)#

hipsparseSpSM_analysis()#

hipsparseStatus_t hipsparseSpSM_analysis(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnMatDescr_t matB, const hipsparseDnMatDescr_t matC, hipDataType computeType, hipsparseSpSMAlg_t alg, hipsparseSpSMDescr_t spsmDescr, void *externalBuffer)#

hipsparseSpSM_solve()#

hipsparseStatus_t hipsparseSpSM_solve(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnMatDescr_t matB, const hipsparseDnMatDescr_t matC, hipDataType computeType, hipsparseSpSMAlg_t alg, hipsparseSpSMDescr_t spsmDescr, void *externalBuffer)#
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