spmm#

Computes a sparse matrix by dense matrix product.

Description and Assumptions

The oneapi::mkl::sparse::spmm routine computes a sparse matrix by dense matrix product defined as:

\[C \leftarrow \alpha \cdot \text{op}(A) \cdot \text{op}(B) + \beta \cdot C\]

where:

\(\alpha\) and \(\beta\) are scalars,
\(C\) is a dense matrix of size m-by-n,
\(\text{op}(A)\) is a transformed sparse matrix of size m-by-k,
\(\text{op}(B)\) is a transformed dense matrix of size k-by-n,
\(\text{op}()\) is the transform operation using the following description:

\[\begin{split}\text{op}(A) = \begin{cases} A,& \text{oneapi::mkl::transpose::nontrans}\\ A^\mathsf{T},& \text{oneapi::mkl::transpose::trans}\\ A^\mathsf{H},& \text{oneapi::mkl::transpose::conjtrans} \end{cases}\end{split}\]

spmm_descr#

Definition

namespace oneapi::mkl::sparse {

    struct spmm_descr;
    using spmm_descr_t = spmm_descr*;

}

Description

Defines spmm_descr_t as an opaque pointer to the incomplete type spmm_descr. Each backend may provide a different implementation of the type spmm_descr. The spmm_descr_t object persists through the various stages of the spmm operation to house relevant state, optimizations and workspaces.

init_spmm_descr#

Syntax

namespace oneapi::mkl::sparse {

    void init_spmm_descr (sycl::queue                       &queue,
                          oneapi::mkl::sparse::spmm_descr_t *p_spmm_descr);

}

Input parameters

queue: The SYCL command queue which will be used for SYCL kernels execution.
p_spmm_descr: The address of the p_spmm_descr object to be initialized. Must only be called on an uninitialized spmm_descr_t object.

Output parameters

p_spmm_descr: On return, the address is updated to point to a newly allocated and initialized spmm_descr_t object that can be used to perform spmm.

Throws

This function shall throw the following exceptions if the associated condition is detected. An implementation may throw additional implementation-specific exception(s) in case of error conditions not covered here.

oneapi::mkl::host_bad_alloc
oneapi::mkl::invalid_argument
oneapi::mkl::unimplemented
oneapi::mkl::unsupported_device

release_spmm_descr#

Syntax

namespace oneapi::mkl::sparse {

    sycl::event release_spmm_descr (sycl::queue                       &queue,
                                    oneapi::mkl::sparse::spmm_descr_t spmm_descr,
                                    const std::vector<sycl::event>    &dependencies = {});

}

Input parameters

queue: The SYCL command queue which will be used for SYCL kernels execution.
spmm_descr: Descriptor initialized with init_spmm_descr.
dependencies: List of events to depend on before starting asynchronous tasks that access data on the device. Defaults to no dependencies.

Return Values

Output event that can be waited upon or added as a dependency for the completion of the function.

Throws

oneapi::mkl::invalid_argument
oneapi::mkl::unimplemented
oneapi::mkl::unsupported_device

spmm_alg#

Syntax

namespace oneapi::mkl::sparse {

    enum class spmm_alg {
        default_alg,
        no_optimize_alg,
        coo_alg1,
        coo_alg2,
        coo_alg3,
        coo_alg4,
        csr_alg1,
        csr_alg2,
        csr_alg3,
    };

}

Description

These algorithm enums are provided in case backends would like to implement various different algorithms for the operation. Behavior of the algorithms (e.g., bitwise reproducibility, atomics usage) and the preconditions to using specific algorithms (e.g. sortedness of matrix arrays) is implementation-defined and must be documented in the library implementing the oneAPI specification.

spmm#

Syntax

namespace oneapi::mkl::sparse {

    void spmm_buffer_size(
        sycl::queue                                &queue,
        oneapi::mkl::transpose                     opA,
        oneapi::mkl::transpose                     opB,
        const void*                                alpha,
        oneapi::mkl::sparse::matrix_view           A_view,
        oneapi::mkl::sparse::matrix_handle_t       A_handle,
        oneapi::mkl::sparse::dense_matrix_handle_t B_handle,
        const void*                                beta,
        oneapi::mkl::sparse::dense_matrix_handle_t C_handle,
        oneapi::mkl::sparse::spmm_alg              alg,
        oneapi::mkl::sparse::spmm_descr_t          spmm_descr,
        std::size_t                                &temp_buffer_size);

    void spmm_optimize(
        sycl::queue                                &queue,
        oneapi::mkl::transpose                     opA,
        oneapi::mkl::transpose                     opB,
        const void*                                alpha,
        oneapi::mkl::sparse::matrix_view           A_view,
        oneapi::mkl::sparse::matrix_handle_t       A_handle,
        oneapi::mkl::sparse::dense_matrix_handle_t B_handle,
        const void*                                beta,
        oneapi::mkl::sparse::dense_matrix_handle_t C_handle,
        oneapi::mkl::sparse::spmm_alg              alg,
        oneapi::mkl::sparse::spmm_descr_t          spmm_descr,
        sycl::buffer<std::uint8_t, 1>              workspace);

    sycl::event spmm_optimize(
        sycl::queue                                &queue,
        oneapi::mkl::transpose                     opA,
        oneapi::mkl::transpose                     opB,
        const void*                                alpha,
        oneapi::mkl::sparse::matrix_view           A_view,
        oneapi::mkl::sparse::matrix_handle_t       A_handle,
        oneapi::mkl::sparse::dense_matrix_handle_t B_handle,
        const void*                                beta,
        oneapi::mkl::sparse::dense_matrix_handle_t C_handle,
        oneapi::mkl::sparse::spmm_alg              alg,
        oneapi::mkl::sparse::spmm_descr_t          spmm_descr,
        void*                                      workspace,
        const std::vector<sycl::event>             &dependencies = {});

    sycl::event spmm(
        sycl::queue                                &queue,
        oneapi::mkl::transpose                     opA,
        oneapi::mkl::transpose                     opB,
        const void*                                alpha,
        oneapi::mkl::sparse::matrix_view           A_view,
        oneapi::mkl::sparse::matrix_handle_t       A_handle,
        oneapi::mkl::sparse::dense_matrix_handle_t B_handle,
        const void*                                beta,
        oneapi::mkl::sparse::dense_matrix_handle_t C_handle,
        oneapi::mkl::sparse::spmm_alg              alg,
        oneapi::mkl::sparse::spmm_descr_t          spmm_descr,
        const std::vector<sycl::event>             &dependencies = {});

}

Notes

spmm_buffer_size and spmm_optimize must be called at least once before spmm with the same arguments. spmm can then be called multiple times. Calling spmm_optimize on the same descriptor can reset some of the descriptor’s data such as the workspace.
In the general case, not calling the functions in the order specified above is undefined behavior. Not calling spmm_buffer_size or spmm_optimize at least once with a given descriptor will throw an oneapi::mkl::uninitialized exception. Calling spmm with arguments not matching spmm_optimize will throw an oneapi::mkl::invalid_argument exception, unless stated otherwise.
The data of the dense handles B_handle and C_handle and the scalars alpha and beta can be reset before each call to spmm. Changing the data of the sparse handle A_handle is undefined behavior.
The data must be available on the device when calling spmm_optimize by using event dependencies if needed.
spmm_optimize and spmm are asynchronous.
The algorithm defaults to spmm_alg::default_alg if a backend does not support the provided algorithm.
The container type of all the handles and workspace must be consistent and use either USM pointers or SYCL buffers.

Input Parameters

queue

The SYCL command queue which will be used for SYCL kernels execution.

opA

Specifies operation op() on the input matrix A. The possible options are described in transpose enum class.

opB

Specifies operation op() on the input matrix B. The possible options are described in transpose enum class.

alpha

Host or USM pointer representing \(\alpha\). The USM allocation can be on the host or device. The requirements are:

Must use the same kind of memory as beta.
Must be a host pointer if SYCL buffers are used.
Must be of the same type as the handles’ data type.

A_view

Specifies which part of the handle should be read as described by matrix_view. The type_view field must be matrix_descr::general and the uplo_view and diag_view fields are ignored.

A_handle

Sparse matrix handle object representing \(A\).

B_handle

Dense matrix handle object representing \(B\).

beta

Host or USM pointer representing \(\beta\). The USM allocation can be on the host or device. The requirements are:

Must use the same kind of memory as alpha.
Must be a host pointer if SYCL buffers are used.
Must be of the same type as the handles’ data type.

C_handle

Dense matrix handle object representing \(C\).

alg

Specifies the spmm algorithm to use.

spmm_descr

Initialized spmm descriptor.

temp_buffer_size

Output buffer size in bytes.

workspace

Workspace buffer or USM pointer, must be at least of size
temp_buffer_size bytes and the address aligned on the size of the
handles’ data type.
If it is a buffer, its lifetime is extended until the spmm
descriptor is released or the workspace is
reset by spmm_optimize. The workspace cannot be a sub-buffer.
If it is a USM pointer, it must not be free’d until the corresponding
spmm has completed. The data must be accessible on the device.

dependencies

List of events to depend on before starting asynchronous tasks that access data on the device. Ignored if buffers are used. Defaults to no dependencies.

Output Parameters

temp_buffer_size: Output buffer size in bytes. A temporary workspace of at least this size must be allocated to perform the specified spmm.
C_handle: Dense matrix handle object representing \(C\), result of the spmm operation.

Return Values

Output event that can be waited upon or added as a dependency for the completion of the function. May be an empty event if buffers are used.

Throws

These functions shall throw the following exceptions if the associated condition is detected. An implementation may throw additional implementation-specific exception(s) in case of error conditions not covered here.

oneapi::mkl::computation_error
oneapi::mkl::device_bad_alloc
oneapi::mkl::invalid_argument
oneapi::mkl::unimplemented
oneapi::mkl::uninitialized
oneapi::mkl::unsupported_device

Parent topic: Sparse BLAS

spmm

Contents

spmm#

spmm_descr#

init_spmm_descr#

release_spmm_descr#

spmm_alg#

spmm#