Intel® oneAPI Math Kernel Library (oneMKL) - Data Parallel C++ Developer Reference
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Visible to Intel only — GUID: GUID-E414BBD9-EC9B-46B9-A706-FD2190F837D2
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) = AT, or op(A) = AH
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_sizegemv 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) = AT, or op(A) = AH
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:
Syntax
namespace oneapi::mkl::blas::column_major {
sycl::event gemv_batch(sycl::queue &queue,
const oneapi::mkl::transpose *trans,
const std::int64_t *m,
const std::int64_t *n,
const T *alpha,
const T **a,
const std::int64_t *lda,
const T **x,
const std::int64_t *incx,
const T *beta,
T **y,
const std::int64_t *incy,
std::int64_t group_count,
const std::int64_t *group_size,
const std::vector<sycl::event> &dependencies = {})
}
namespace oneapi::mkl::blas::row_major {
sycl::event gemv_batch(sycl::queue &queue,
const oneapi::mkl::transpose *trans,
const std::int64_t *m,
const std::int64_t *n,
const T *alpha,
const T **a,
const std::int64_t *lda,
const T **x,
const std::int64_t *incx,
const T *beta,
T **y,
const std::int64_t *incy,
std::int64_t group_count,
const 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_countoneapi::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_countgemv 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) = AT, or op(A) = AH
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_sizegemv operations of the form alpha * op(A) * X + beta * Y.
Return Values
Output event to wait on to ensure computation is complete.