gemv_batch¶

Computes a group of gemv operations.

Description¶

The gemv_batch routines are batched versions of gemv, performing multiple gemv operations in a single call. Each gemv operations perform a scalar-matrix-vector product and add the result to a scalar-vector product.

gemv_batch supports the following precisions:

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

gemv_batch (Buffer Version)¶

Buffer version of gemv_batch supports only strided API.

Strided API¶

Strided API operation is defined as:

for i = 0 … batch_size – 1
    A is a matrix at offset i * stridea in a.
    X and Y are vctors at offset i * stridex, i * stridey, in x and y.
    Y = alpha * op(A) * X + beta * Y
end for

where:

op(A) is one of op(A) = A, or op(A) = A^T, or op(A) = A^H
alpha and beta are scalars
A is matrix and X and Y are vectors

For strided API, x and y buffers contain all the input vectors. The stride between vectors is either given by the stride parameters. Total number of vectors in x and y buffers is given by batch_size parameter.

Syntax¶

namespace oneapi::mkl::blas::column_major {
    void gemv_batch(sycl::queue &queue,
                    oneapi::mkl::transpose trans,
                    std::int64_t m,
                    std::int64_t n,
                    T alpha,
                    sycl::buffer<T,1> &a,
                    std::int64_t lda,
                    std::int64_t stridea,
                    sycl::buffer<T,1> &x,
                    std::int64_t incx,
                    std::int64_t stridex,
                    T beta,
                    sycl::buffer<T,1> &y,
                    std::int64_t incy,
                    std::int64_t stridey,
                    std::int64_t batch_size)
}

namespace oneapi::mkl::blas::row_major {
    void gemv_batch(sycl::queue &queue,
                    oneapi::mkl::transpose trans,
                    std::int64_t m,
                    std::int64_t n,
                    T alpha,
                    sycl::buffer<T,1> &a,
                    std::int64_t lda,
                    std::int64_t stridea,
                    sycl::buffer<T,1> &x,
                    std::int64_t incx,
                    std::int64_t stridex,
                    T beta,
                    sycl::buffer<T,1> &y,
                    std::int64_t incy,
                    std::int64_t stridey,
                    std::int64_t batch_size)
}

Input Parameters¶

queue: The queue where the routine should be executed.
trans: Specifies op(A), the transposition operation applied to matrices A. See Data Types for more details.
m: Number of rows of matrices op(A). Must be at least zero.
n: Number of columns of matrices op(A). Must be at least zero.
alpha: Scaling factor for matrix-vector product.
a: The buffer holding input matrices A. Size of the buffer must be at least stridea * batch_size.
lda: Leading dimension of matrices A. Must be positive and at least m if column major layout or at least n if row major layout is used.
stridea: Stride between two consecutive A matrices.
x: Buffer holding input vectors X. Size of the buffer must be at least stridex * batch_size.
incx: Stride between two consecutive elements of X vectors.
stridex: Stride between two consecutive X vectors. Must be at least zero.
beta: Scaling factor for vectors Y.
y: Buffer holding input/output vectors Y. Size of the buffer must be at least stridey * batch_size.
incy: Stride between two consecutive elements of Y vectors.
stridey: Stride between two consecutive Y vectors. Must be at least zero.
batch_size: Number of gemv computations to perform. Must be at least zero.

Output Parameters¶

y: Output buffer overwritten by batch_size gemv operations of the form alpha * op(A) * X + beta * Y.

gemv_batch (USM Version)¶

USM version of gemv_batch supports group API strided API.

Group API¶

Group API operation is defined as:

idx = 0
for i = 0 … group_count – 1
    for j = 0 … group_size – 1
        A is an m x n matrix in a[idx]
        X and Y are vectors in x[idx] and y[idx]
        Y = alpha[i] * op(A) * X + beta[i] * Y
        idx = idx + 1
    end for
end for

where:

op(A) is one of op(A) = A, or op(A) = A^T, or op(A) = A^H
alpha and beta are scalars
A is matrix and X and Y are vectors

For group API, x and y arrays contain the pointers for all the input vectors. a array contains the pointers to all input matrices. The total number of vectors in x and y and matrices in a is given by:

$total\_batch\_count = \sum_{i=0}^{group\_count-1}group\_size[i]$

Syntax¶

namespace oneapi::mkl::blas::column_major {
    sycl::event gemv_batch(sycl::queue &queue,
                           oneapi::mkl::transpose *trans,
                           std::int64_t *m,
                           std::int64_t *n,
                           T *alpha,
                           const T **a,
                           std::int64_t *lda,
                           const T **x,
                           std::int64_t *incx,
                           T *beta,
                           T **y,
                           std::int64_t *incy,
                           std::int64_t group_count,
                           std::int64_t *group_size,
                           const std::vector<sycl::event> &dependencies = {})
}

namespace oneapi::mkl::blas::row_major {
    sycl::event gemv_batch(sycl::queue &queue,
                           oneapi::mkl::transpose *trans,
                           std::int64_t *m,
                           std::int64_t *n,
                           T *alpha,
                           const T **a,
                           std::int64_t *lda,
                           const T **x,
                           std::int64_t *incx,
                           T *beta,
                           T **y,
                           std::int64_t *incy,
                           std::int64_t group_count,
                           std::int64_t *group_size,
                           const std::vector<sycl::event> &dependencies = {})
}

Input Parameters¶

queue: The queue where the routine should be executed.
trans: Array of group_count oneapi::mkl::transpose values. transa[i] specifies op(A), the transposition operation applied to matrices A in group i. See Data Types for more details.
m: Array of group_count integers. m[i] specifies number of rows of matrices op(A) in group i. All entries must be at least zero.
n: Array of group_count integers. n[i] specifies number of columns of matrices op(A) in group i. All entries must be at least zero.
alpha: Array of group_count scalar elements. alpha[i] specifies scaling factor for matrix-vector products in group i.
a: Array of total_batch_count pointers for input matrices A. See Matrix Storage for more details.
lda: Array of group_count integers. lda[i] specifies leading dimension of matrices A in group i. Must be positive and at least m[i] if column major layout or at least n[i] if row major layout is used.
x: Array of total_batch_count pointers for input vectors X. See Matrix Storage for more details.
incx: Array of group_count integers. incx[i] specifies stride of vectors X in group i.
beta: Array of group_count scalar elements. beta[i] specifies scaling factor for vectors Y in group i.
y: Array of total_batch_count pointers for input/output vectors Y. See Matrix Storage for more details.
incy: Array of group_count integers. incy[i] specifies stride of vectors Y in group i.
group_count: Number of groups. Must be at least zero.
group_size: Array of group_count integers. group_size[i] specifies the number of gemv operations in group i. Each element in group_size must be at least zero.
dependencies: List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.

Output Parameters¶

y: Array of pointers to output vectors Y overwritten by total_batch_count gemv operations of the form alpha * op(A) * X + beta * Y.

Return Values¶

Output event to wait on to ensure computation is complete.

Examples¶

An example of how to use USM version of gemv_batch can be found in oneMKL installation directory, under:

examples/dpcpp/blas/source/gemv_batch_usm.cpp

Strided API¶

Strided API operation is defined as:

for i = 0 … batch_size – 1
    A is a matrix at offset i * stridea in a.
    X and Y are vctors at offset i * stridex, i * stridey, in x and y.
    Y = alpha * op(A) * X + beta * Y
end for

where:

op(A) is one of op(A) = A, or op(A) = A^T, or op(A) = A^H
alpha and beta are scalars
A is matrix and X and Y are vectors

For strided API, x and y arrays contain all the input vectors. The stride between vectors is given by the stride parameters. Total number of vectors in x and y arrays is given by batch_size parameter.

Syntax¶

namespace oneapi::mkl::blas::column_major {
    sycl::event gemv_batch(sycl::queue &queue,
                           oneapi::mkl::transpose trans,
                           std::int64_t m,
                           std::int64_t n,
                           T alpha,
                           const T *a,
                           std::int64_t lda,
                           std::int64_t stridea,
                           const T *x,
                           std::int64_t incx,
                           std::int64_t stridex,
                           T beta,
                           T *y,
                           std::int64_t incy,
                           std::int64_t stridey,
                           std::int64_t batch_size)
}

namespace oneapi::mkl::blas::row_major {
    sycl::event gemv_batch(sycl::queue &queue,
                           oneapi::mkl::transpose trans,
                           std::int64_t m,
                           std::int64_t n,
                           T alpha,
                           const T *a,
                           std::int64_t lda,
                           std::int64_t stridea,
                           const T *x,
                           std::int64_t incx,
                           std::int64_t stridex,
                           T beta,
                           T *y,
                           std::int64_t incy,
                           std::int64_t stridey,
                           std::int64_t batch_size)
}

Input Parameters¶

queue: The queue where the routine should be executed.
trans: Specifies op(A), the transposition operation applied to matrices A. See Data Types for more details.
m: Number of rows of matrices op(A). Must be at least zero.
n: Number of columns of matrices op(A). Must be at least zero.
alpha: Scaling factor for matrix-vector product.
a: Pointer to input matrices A. Size of the array must be at least stridea * batch_size.
lda: Leading dimension of matrices A. Must be positive and at least m if column major layout or at least n if row major layout is used.
stridea: Stride between two consecutive A matrices.
x: Pointer to input vectors X. Size of the array must be at least stridex * batch_size.
incx: Stride between two consecutive elements of X vectors.
stridex: Stride between two consecutive X vectors. Must be at least zero.
beta: Scaling factor for vectors Y.
y: Pointer to input/output vectors Y. Size of the array must be at least stridey * batch_size.
incy: Stride between two consecutive elements of Y vectors.
stridey: Stride between two consecutive Y vectors. Must be at least zero.
batch_size: Number of gemv computations to perform. Must be at least zero.
dependencies: List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.

Output Parameters¶

y: Pointer to output vectors Y overwritten by batch_size gemv operations of the form alpha * op(A) * X + beta * Y.

Return Values¶

Output event to wait on to ensure computation is complete.

gemmt syrk_batch

oneAPI Math Kernel Library (oneMKL) documentation

gemv_batch¶

Description¶

gemv_batch (Buffer Version)¶

Strided API¶

Syntax¶

Input Parameters¶

Output Parameters¶

gemv_batch (USM Version)¶

Group API¶

Syntax¶

Input Parameters¶

Output Parameters¶

Return Values¶

Examples¶

Strided API¶

Syntax¶

Input Parameters¶

Output Parameters¶

Return Values¶