ger#

Computes a rank-1 update of a general matrix.

Description

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

\[A \leftarrow alpha*x*y^T + A\]

where:

alpha is scalar,

A is an m-by-n matrix,

x is a vector of length m,

y is a vector of length n.

ger supports the following precisions.

T

float

double

T
`float`
`double`

ger (Buffer Version)#

Syntax

namespace oneapi::mkl::blas::column_major {
    void 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)
}

namespace oneapi::mkl::blas::row_major {
    void 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 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 Storage for more details.
incy: Stride of vector y.
a: Buffer holding input matrix A. Must have size at least lda*n if column major layout is used or at least lda*m if row major layout is used. See Matrix Storage for more details.
lda: Leading dimension of matrix A. Must be positive and at least m if column major layout is used or at least n if row major layout is used.

Output Parameters

a: Buffer holding the updated matrix A.

Throws

This routine shall throw the following exceptions if the associated condition is detected. An implementation may throw additional implementation-specific exception(s) in case of error conditions not covered here.

oneapi::mkl::invalid_argument

oneapi::mkl::unsupported_device

oneapi::mkl::host_bad_alloc

oneapi::mkl::device_bad_alloc

oneapi::mkl::unimplemented

ger (USM Version)#

Syntax

namespace oneapi::mkl::blas::column_major {
    sycl::event 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 std::vector<sycl::event> &dependencies = {})
}

namespace oneapi::mkl::blas::row_major {
    sycl::event 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 std::vector<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 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 Storage for more details.
incy: Stride of vector y.
a: Pointer to input matrix A. Must have size at least lda*n if column major layout is used or at least lda*m if row major layout is used. See Matrix Storage for more details.
lda: Leading dimension of matrix A. Must be positive and at least m if column major layout is used or at least n if row major layout is used.
dependencies: List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.