gemmt

Computes a matrix-matrix product with general matrices, but updates only the upper or lower triangular part of the result matrix.

Description

The gemmt routines compute a scalar-matrix-matrix product and add the result to the upper or lower part of a scalar-matrix product, with general matrices. The operation is defined as:

\[C \leftarrow alpha*op(A)*op(B) + beta*C\]

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 n x k, op(B) is k x n, and C is n x n.

gemmt supports the following precisions.

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

gemmt (Buffer Version)

Syntax

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

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

Input Parameters

queue

The queue where the routine should be executed.

upper_lower

Specifies whether C’s data is stored in its upper or lower triangle. See oneMKL Defined Datatypes for more details.

transa

Specifies op(A), the transposition operation applied to A. See oneMKL Defined Datatypes for more details.

transb

Specifies op(B), the transposition operation applied to B. See oneMKL Defined Datatypes for more details.

n

Number of rows of op(A), columns of op(B), and columns and rows ofC. Must be at least zero.

k

Number of columns of op(A) and rows of op(B). Must be at least zero.

alpha

Scaling factor for the matrix-matrix product.

a

Buffer holding the input matrix A.

	A not transposed	A transposed
Column major	A is an n-by-k matrix so the array a must have size at least lda*k.	A is an k-by-n matrix so the array a must have size at least lda*n
Row major	A is an n-by-k matrix so the array a must have size at least lda*n.	A is an k-by-n matrix so the array a must have size at least lda*k.

See Matrix Storage for more details.

lda

The leading dimension of A. It must be positive.

	A not transposed	A transposed
Column major	lda must be at least n.	lda must be at least k.
Row major	lda must be at least k.	lda must be at least n.

b

Buffer holding the input matrix B.

	B not transposed	B transposed
Column major	B is an k-by-n matrix so the array b must have size at least ldb*n.	B is an n-by-k matrix so the array b must have size at least ldb*k
Row major	B is an k-by-n matrix so the array b must have size at least ldb*k.	B is an n-by-k matrix so the array b must have size at least ldb*n.

See Matrix Storage for more details.

ldb

The leading dimension of B. It must be positive.

	B not transposed	B transposed
Column major	ldb must be at least k.	ldb must be at least n.
Row major	ldb must be at least n.	ldb must be at least k.

beta

Scaling factor for matrix C.

c

Buffer holding the input/output matrix C. Must have size at least ldc * n. See Matrix Storage for more details.

ldc

Leading dimension of C. Must be positive and at least m.

Output Parameters

c

Output buffer, overwritten by the upper or lower triangular part of alpha * op(A)*op(B) + beta * C.

Notes

If beta = 0, matrix C does not need to be initialized before calling gemmt.

gemmt (USM Version)

Syntax

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

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

Input Parameters

queue

The queue where the routine should be executed.

upper_lower

Specifies whether C’s data is stored in its upper or lower triangle. See oneMKL Defined Datatypes for more details.

transa

Specifies op(A), the transposition operation applied to A. See oneMKL Defined Datatypes for more details.

transb

Specifies op(B), the transposition operation applied to B. See oneMKL Defined Datatypes for more details.

n

Number of columns of op(A), columns of op(B), and columns ofC. Must be at least zero.

k

Number of columns of op(A) and rows of op(B). Must be at least zero.

alpha

Scaling factor for the matrix-matrix product.

a

Pointer to input matrix A.

	A not transposed	A transposed
Column major	A is an n-by-k matrix so the array a must have size at least lda*k.	A is an k-by-n matrix so the array a must have size at least lda*n
Row major	A is an n-by-k matrix so the array a must have size at least lda*n.	A is an k-by-n matrix so the array a must have size at least lda*k

See Matrix Storage for more details.

lda

The leading dimension of A. It must be positive.

	A not transposed	A transposed
Column major	lda must be at least n.	lda must be at least k.
Row major	lda must be at least k.	lda must be at least n.

b

Pointer to input matrix B.

	B not transposed	B transposed
Column major	B is an k-by-n matrix so the array b must have size at least ldb*n.	B is an n-by-k matrix so the array b must have size at least ldb*k
Row major	B is an k-by-n matrix so the array b must have size at least ldb*k.	B is an n-by-k matrix so the array b must have size at least ldb*n

See Matrix Storage for more details.

ldb

The leading dimension of B. It must be positive.

	B not transposed	B transposed
Column major	ldb must be at least k.	ldb must be at least n.
Row major	ldb must be at least n.	ldb must be at least k.

beta

Scaling factor for matrix C.

c

Pointer to input/output matrix C. Must have size at least ldc * n. See Matrix Storage for more details.

ldc

Leading dimension of C. Must be positive and at least m.

dependencies

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

Output Parameters

c

Pointer to the output matrix, overwritten by the upper or lower triangular part of alpha * op(A)*op(B) + beta * C.

Notes

If beta = 0, matrix C does not need to be initialized before calling gemmt.

Return Values

Output event to wait on to ensure computation is complete.

Parent topic: BLAS-like Extensions