oneapi::mkl::sparse::optimize

oneMKL - Data Parallel C++ Developer Reference

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ID 772045

Date 10/31/2024

Version

Public

Visible to Intel only — GUID: GUID-2207FB40-A6D3-46B9-8BF5-0ACB0FBE72B4

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oneapi::mkl::sparse::optimize_trmv

Performs internal optimizations for oneapi::mkl::sparse::trmv by analyzing the matrix structure.

Description
API

Description

The oneapi::mkl::sparse::optimize_trmv routine analyzes matrix structure and performs optimizations. Optimized data is then stored in the matrix handle.

NOTE:

Refer to Error Handling for a detailed description of the possible exceptions thrown.

API

Syntax

Using USM and SYCL buffers:

namespace oneapi::mkl::sparse {
    sycl::event optimize_trmv (
        sycl::queue &queue,
        oneapi::mkl::uplo uplo_val,
        oneapi::mkl::transpose opA,
        oneapi::mkl::diag diag_val,
        oneapi::mkl::sparse::matrix_handle_t A,
        const std::vector<sycl::event> &dependencies = {});
}

Include Files

oneapi/mkl/spblas.hpp

Input Parameters

queue

Specifies the SYCL command queue which will be used for SYCL kernels execution.

uplo_val

Specifies which part of the matrix is to be processed.

`oneapi::mkl::uplo::lower`	The lower triangular matrix part is processed.
`oneapi::mkl::uplo::upper`	The upper triangular matrix part is processed.

opA

Specifies operation op() on input matrix.

`oneapi::mkl::transpose::nontrans`	Non-transpose, .
`oneapi::mkl::transpose::trans`	Transpose, .
`oneapi::mkl::transpose::conjtrans`	Conjugate transpose, .

NOTE:

Currently, the only supported case for operation is oneapi::mkl::transpose::nontrans.

diag_val

Specifies if the diagonal used for computations is unit or not.

`oneapi::mkl::diag::nonunit`	Diagonal elements might not be equal to one.
`oneapi::mkl::diag::unit`	Diagonal elements are equal to one.

NOTE:

Currently, the only supported case for diag_val is oneapi::mkl::diag::nonunit.

A

Handle to object containing sparse matrix and other internal data. Created using one of the oneapi::mkl::sparse::set_<sparse_matrix_type>_data routines.

NOTE:

The supported cases for <sparse_matrix_type> are csr on CPU and GPU devices, and coo only on CPU device.

dependencies

A vector of type std::vector<sycl::event> & containing the list of events that the oneapi::mkl::sparse::optimize_trmv routine depends on.

Return Values

sycl::event

SYCL event which can be waited upon or added as a dependency for the completion of the optimize_trmv routine.

sycl::event ev_opt = sparse::optimize_trmv(queue, uplo_val, opA, diag_val, A);               // Allowed use in case of USM
sycl::event ev_opt = sparse::optimize_trmv(queue, uplo_val, opA, diag_val, A, {});           // Allowed use in case of USM
sycl::event ev_opt = sparse::optimize_trmv(queue, uplo_val, opA, diag_val, A, dependencies); // Allowed use in case of USM
sparse::optimize_trmv(queue, uplo_val, opA, diag_val, A);                                    // OK Recommended use in case of sycl::buffer
static_cast<void>(sparse::optimize_trmv(queue, uplo_val, opA, diag_val, A));                 // OK Recommended use in case of sycl::buffer (explicitly say we aren't using the event)(will be used in examples)
sparse::optimize_trmv(queue, uplo_val, opA, diag_val, A, {});                                // Not recommended in case of sycl::buffer, but supported;
sparse::optimize_trmv(queue, uplo_val, opA, diag_val, A, dependencies);                      // Not recommended in case of sycl::buffer, but supported;
sycl::event ev_opt = sparse::optimize_trmv(queue, uplo_val, opA, diag_val, A);               // Allowed use in case of sycl::buffer, but most sycl::buffer oneMKL APIs do not have ability to pass in dependencies

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oneMKL - Data Parallel C++ Developer Reference

oneapi::mkl::sparse::optimize_trmv

Description

API