ger¶

Computes a rank-1 update of a general matrix.

ger supports the following precisions.

T

float

double

Description

The ger routines compute a scalar-vector-vector product and add the result to a general matrix. The operation is defined as

A <- alpha*x*y ^T + A

where:

alpha is scalar,

A is an m-by-n matrix,

x is a vector length m,

y is a vector length n.

ger (Buffer Version)¶

Syntax

void onemkl::blas::ger(sycl::queue &queue, std::int64_t m, std::int64_t n, T alpha, sycl::buffer<T, 1> &x, std::int64_t incx, sycl::buffer<T, 1> &y, std::int64_t incy, sycl::buffer<T, 1> &a, std::int64_t lda)¶

Input Parameters

queue: The queue where the routine should be executed.
m: Number of rows of A. Must be at least zero.
n: Number of columns of A. Must be at least zero.
alpha: Scaling factor for the matrix-vector product.
x: Buffer holding input vector x. The buffer must be of size at least (1 + (m - 1)*abs(incx)). See Matrix and Vector Storage for more details.
incx: Stride of vector x.
y: Buffer holding input/output vector y. The buffer must be of size at least (1 + (n - 1)*abs(incy)). See Matrix and Vector Storage for more details.
incy: Stride of vector y.
a: Buffer holding input matrix A. Must have size at least lda*n. See Matrix and Vector Storage for more details.
lda: Leading dimension of matrix A. Must be at least m, and positive.

Output Parameters

Syntax

sycl::event onemkl::blas::ger(sycl::queue &queue, std::int64_t m, std::int64_t n, T alpha, const T *x, std::int64_t incx, const T *y, std::int64_t incy, T *a, std::int64_t lda, const sycl::vector_class<sycl::event> &dependencies = {})¶

Input Parameters

queue: The queue where the routine should be executed.
m: Number of rows of A. Must be at least zero.
n: Number of columns of A. Must be at least zero.
alpha: Scaling factor for the matrix-vector product.
x: Pointer to input vector x. The array holding input vector x must be of size at least (1 + (m - 1)*abs(incx)). See Matrix and Vector Storage for more details.
incx: Stride of vector x.
y: Pointer to input/output vector y. The array holding input/output vector y must be of size at least (1 + (n - 1)*abs(incy)). See Matrix and Vector Storage for more details.
incy: Stride of vector y.
a: Pointer to input matrix A. Must have size at least lda*n. See Matrix and Vector Storage for more details.
lda: Leading dimension of matrix A. Must be at least m, and positive.
dependencies: List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.

Output Parameters

Return Values

Output event to wait on to ensure computation is complete.

Parent topic: BLAS Level 2 Routines