hemm

Computes a matrix-matrix product where one input matrix is Hermitian and one is general.

Description

The hemm routines compute a scalar-matrix-matrix product and add tresult to a scalar-matrix product, where one of the matrices in the multiplication is Hermitian. The argument left_right determines if the Hermitian matrix, A, is on the left of the multiplication (left_right = side::left) or on the right (left_right = side::right). Depending on left_right, the operation is defined as

\[C \leftarrow alpha*A*B + beta*C\]

or

\[C \leftarrow alpha*B*A + beta*C\]

where:

  • alpha and beta are scalars,

  • A is a Hermitian matrix, either m-by-m or n-by-n matrices,

  • B and C are m-by-n matrices.

API

Syntax

namespace oneapi::mkl::blas::column_major {
    void hemm(sycl::queue &queue,
              onemkl::side left_right,
              onemkl::uplo upper_lower,
              std::int64_t m,
              std::int64_t n,
              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 hemm(sycl::queue &queue,
              onemkl::side left_right,
              onemkl::uplo upper_lower,
              std::int64_t m,
              std::int64_t n,
              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)
}

hemm supports the following precisions and devices:

T

Devices Supported

std::complex<float>

Host, CPU, and GPU

std::complex<double>

Host, CPU, and GPU

Input Parameters

exec_queue

The queue where the routine should be executed.

left_right

Specifies whether A is on the left side of the multiplication (side::left) or on the right side (side::right). See Data Types for more details.

uplo

Specifies whether A’s data is stored in its upper or lower triangle. See Data Types for more details.

m

Specifies the number of rows of the matrix B and C.

The value of m must be at least zero.

n

Specifies the number of columns of the matrix B and C.

The value of n must be at least zero.

alpha

Scaling factor for the matrix-matrix product.

a

Buffer holding input matrix A. Must have size at least lda* m if A is on the left of the multiplication, or lda*n if A is on the right. See Matrix Storage for more details.

lda

Leading dimension of A. Must be at least m if A is on the left of the multiplication, or at least n if A is on the right. Must be positive.

b

Buffer holding input matrix B. It must have a size of at least ldb*n if column major layout is used to store matrices or at least ldb*m if row major layout is used to store matrices. See Matrix Storage for more details.

ldb

Leading dimension of B. It must be positive and at least m if column major layout is used to store matrices or at least n if column major layout is used to store matrices.

beta

Scaling factor for matrix C.

c

Buffer holding input/output matrix C. It must have a size of at least ldc*n if column major layout is used to store matrices or at least ldc*m if row major layout is used to store matrices. See ref:matrix-storage for more details.

ldc

Leading dimension of C. It must be positive and at least m if column major layout is used to store matrices or at least n if column major layout is used to store matrices.

Output Parameters

c

Output buffer, overwritten by alpha*A*B + beta*C (left_right = side::left) or alpha*B*A + beta*C (left_right = side::right).

Note

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