omatadd

oneMKL - Data Parallel C++ Developer Reference

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ID 772045

Date 3/22/2024

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omatadd

Computes a sum of two general matrices, with optional transposes.

Description

The omatadd routine performs an out-of-place scaled matrix addition with optional transposes in the arguments. The operation is defined as:

where:

op(X) is one of op(X) = X, or op(X) = X^T, or op(X) = X^H
alpha and beta are scalars
A, B and C are matrices
op(A) is m x n matrix
op(B) is m x n matrix
C is m x n matrix

In general, A, B, and C must not overlap in memory, with the exception of the following in-place operations:

A and C may point to the same memory if op(A) is non-transpose and lda = ldc;
B and C may point to the same memory if op(B) is non-transpose and ldb = ldc.

omatadd supports the following precisions:

T
`float`
`double`
`std::complex<float>`
`std::complex<double>`

omatadd (Buffer Version)

Syntax

namespace oneapi::mkl::blas::column_major {
    void omatadd(sycl::queue &queue,
                 oneapi::mkl::transpose transa,
                 oneapi::mkl::transpose transb,
                 std::int64_t m,
                 std::int64_t n,
                 T alpha,
                 sycl::buffer<T, 1> &a,
                 std::int64_t lda,
                 T beta,
                 sycl::buffer<T, 1> &b,
                 std::int64_t ldb,
                 sycl::buffer<T, 1> &c,
                 std::int64_t ldc)
 }

namespace oneapi::mkl::blas::row_major {
    void omatadd(sycl::queue &queue,
                 oneapi::mkl::transpose transa,
                 oneapi::mkl::transpose transb,
                 std::int64_t m,
                 std::int64_t n,
                 T alpha,
                 sycl::buffer<T, 1> &a,
                 std::int64_t lda,
                 T beta,
                 sycl::buffer<T, 1> &b,
                 std::int64_t ldb,
                 sycl::buffer<T, 1> &c,
                 std::int64_t ldc)
 }

Input Parameters

queue

The queue where the routine will be executed.

transa

Specifies op(A), the transposition operation applied to the matrix A.

transb

Specifies op(B), the transposition operation applied to the matrix B.

m

Number of rows for the result matrix C. Must be at least zero.

n

Number of columns for the result matrix C. Must be at least zero.

alpha

Scaling factor for the matrix A.

a

Buffer holding the input matrix A.

	`transa` = `transpose::nontrans`	`transa` = `transpose::trans` or `transa` = `transpose::conjtrans`
Column major	`A` is `m` x `n` matrix. Size of array `a` must be at least `lda` * `n`	`A` is `n` x `m` matrix. Size of array `a` must be at least `lda` * `m`
Row major	`A` is `m` x `n` matrix. Size of array `a` must be at least `lda` * `m`	`A` is `n` x `m` matrix. Size of array `a` must be at least `lda` * `n`

lda

Leading dimension of matrix A. Must be positive

	`transa` = `transpose::nontrans`	`transa` = `transpose::trans` or `transa` = `transpose::conjtrans`
Column major	Must be at least `m`	Must be at least `n`
Row major	Must be at least `n`	Must be at least `m`

beta

Scaling factor for the matrix B.

b

Buffer holding the input matrix B.

	`transb` = `transpose::nontrans`	`transb` = `transpose::trans` or `transb` = `transpose::conjtrans`
Column major	`B` is `m` x `n` matrix. Size of array `b` must be at least `ldb` * `n`	`B` is `n` x `m` matrix. Size of array `b` must be at least `ldb` * `m`
Row major	`B` is `m` x `n` matrix. Size of array `b` must be at least `ldb` * `m`	`B` is `n` x `m` matrix. Size of array `b` must be at least `ldb` * `n`

ldb

Leading dimension of marix B. Must be positive.

	`transb` = `transpose::nontrans`	`transb` = `transpose::trans` or `transb` = `transpose::conjtrans`
Column major	Must be at least `m`	Must be at least `n`
Row major	Must be at least `n`	Must be at least `m`

ldc

Leading dimension of the matrix C. If matrices are stored using column major layout, ldc must be at least m. If matrices are stored using row major layout, ldc must be at least n. Must be positive.

Output Parameters

c

Output buffer overwritten by alpha * op(A) + beta * op(B).

Column major	`C` is `m` x `n` matrix. Size of array `c` must be at least `ldc` * `n`
Row major	`C` is `m` x `n` matrix. Size of array `c` must be at least `ldc` * `m`

omatadd (USM Version)

Syntax

namespace oneapi::mkl::blas::column_major {
    sycl::event omatadd(sycl::queue &queue,
                        oneapi::mkl::transpose transa,
                        oneapi::mkl::transpose transb,
                        std::int64_t m,
                        std::int64_t n,
                        oneapi::mkl::value_or_pointer<T> alpha,
                        const T *a,
                        std::int64_t lda,
                        oneapi::mkl::value_or_pointer<T> beta,
                        const T *b,
                        std::int64_t ldb,
                        T *c,
                        std::int64_t ldc,
                        const std::vector<sycl::event> &dependencies = {});
 }

namespace oneapi::mkl::blas::row_major {
    sycl::event omatadd(sycl::queue &queue,
                        oneapi::mkl::transpose transa,
                        oneapi::mkl::transpose transb,
                        std::int64_t m,
                        std::int64_t n,
                        oneapi::mkl::value_or_pointer<T> alpha,
                        const T *a,
                        std::int64_t lda,
                        oneapi::mkl::value_or_pointer<T> beta,
                        const T *b,
                        std::int64_t ldb,
                        T *c,
                        std::int64_t ldc,
                        const std::vector<sycl::event> &dependencies = {});
 }

Input Parameters

queue

The queue where the routine will be executed.

transa

Specifies op(A), the transposition operation applied to matrix A. See Data Types for more details.

transb

Specifies op(B), the transposition operation applied to matrix B. See Data Types for more details.

m

Number of rows for the result matrix C. Must be at least zero.

n

Number of columns for the result matrix C. Must be at least zero.

alpha

Scaling factor for the matrix A. See Scalar Arguments for more information on the value_or_pointer data type.

a

Pointer to input matrix A. See Matrix Storage for more details.

	`transa` = `transpose::nontrans`	`transa` = `transpose::trans` or `transa` = `transpose::conjtrans`
Column major	`A` is `m` x `n` matrix. Size of array `a` must be at least `lda` * `n`	`A` is `n` x `m` matrix. Size of array `a` must be at least `lda` * `m`
Row major	`A` is `m` x `n` matrix. Size of array `a` must be at least `lda` * `m`	`A` is `n` x `m` matrix. Size of array `a` must be at least `lda` * `n`

lda

Leading dimension of matrix A. Must be positive

	`transa` = `transpose::nontrans`	`transa` = `transpose::trans` or `transa` = `transpose::conjtrans`
Column major	Must be at least `m`	Must be at least `n`
Row major	Must be at least `n`	Must be at least `m`

beta

Scaling factor for the matrix B. See Scalar Arguments for more information on the value_or_pointer data type.

b

Pointer to input matrix B. See Matrix Storage for more details.

	`transb` = `transpose::nontrans`	`transb` = `transpose::trans` or `transb` = `transpose::conjtrans`
Column major	`B` is `m` x `n` matrix. Size of array `b` must be at least `ldb` * `n`	`B` is `n` x `m` matrix. Size of array `b` must be at least `ldb` * `m`
Row major	`B` is `m` x `n` matrix. Size of array `b` must be at least `ldb` * `m`	`B` is `n` x `m` matrix. Size of array `b` must be at least `ldb` * `n`

ldb

Leading dimension of marix B. Must be positive.

	`transb` = `transpose::nontrans`	`transb` = `transpose::trans` or `transb` = `transpose::conjtrans`
Column major	Must be at least `m`	Must be at least `n`
Row major	Must be at least `n`	Must be at least `m`

ldc

dependencies

List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.

Output Parameters

c

Pointer to output matrix overwritten by alpha * op(A) + beta * op(B).

Column major	`C` is `m` x `n` matrix. Size of array `c` must be at least `ldc` * `n`
Row major	`C` is `m` x `n` matrix. Size of array `c` must be at least `ldc` * `m`

Return Values

Output event to wait for to ensure computation is complete.

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oneMKL - Data Parallel C++ Developer Reference

omatadd

Description

omatadd (Buffer Version)

omatadd (USM Version)