omatcopy_batch

Computes a group of out-of-place scaled matrix transpose or copy operations using general dense matrices.

Description

The omatcopy_batch routines perform a series of out-of-place scaled matrix copies or transpositions. They are batched versions of omatcopy, but the omatcopy_batch routines perform their operations with groups of matrices. Each group contains matrices with the same parameters.

There is a strided API, in which the matrices in a batch are a set distance away from each other in memory and in which all matrices share the same parameters (for example matrix size), and a more flexible group API where each group of matrices has the same parameters but the user may provide multiple groups that have different parameters. The group API argument structure is better suited to USM pointers than to sycl::buffer arguments, so we only specify it for USM inputs. The strided API works with both USM and buffer memory.

	strided API	group API
Buffer memory	supported	not supported
USM pointers	supported	supported

omatcopy_batch supports the following precisions:

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

omatcopy_batch (Buffer Version)

Description

The buffer version of omatadd_batch supports only the strided API.

The operation for the strided API is defined as:

for i = 0 … batch_size – 1
    A and B are matrices at offset i * stridea in a and i * strideb in b
    B := alpha * op(A)
end for

where:

op(X) is one of op(X) = X, or op(X) = X^T, or op(X) = X^H,

alpha is a scalar,

A and B are input and output matrices,

A is m x n,

and B is m x n if the matrix is not transposed or n by m if it is.

The a buffer contains all the input matrices while the b buffer contains all the output matrices. The locations of the individual matrices within the buffer are given by the stride_a and stride_b parameters, while the total number of matrices in each buffer is given by the batch_size parameter.

Strided API

Syntax

namespace oneapi::math::blas::column_major {
    void omatcopy_batch(sycl::queue &queue,
                        oneapi::math::transpose trans,
                        std::int64_t m,
                        std::int64_t n,
                        T alpha,
                        sycl::buffer<T, 1> &a,
                        std::int64_t lda,
                        std::int64_t stride_a,
                        sycl::buffer<T, 1> &b,
                        std::int64_t ldb,
                        std::int64_t stride_b,
                        std::int64_t batch_size);
}

namespace oneapi::math::blas::row_major {
    void omatcopy_batch(sycl::queue &queue,
                        oneapi::math::transpose trans,
                        std::int64_t m,
                        std::int64_t n,
                        T alpha,
                        sycl::buffer<T, 1> &a,
                        std::int64_t lda,
                        std::int64_t stride_a,
                        sycl::buffer<T, 1> &b,
                        std::int64_t ldb,
                        std::int64_t stride_b,
                        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 the matrices A. See oneMath defined datatypes for more details.

m

Number of rows for each matrix A. Must be at least zero.

n

Number of columns for each matrix A. Must be at least zero.

alpha

Scaling factor for the matrix transposition or copy operations.

a

Buffer holding the input matrices A with size stride_a * batch_size.

lda

The leading dimension of the matrices A. It must be positive, and must be at least m if column major layout is used, and at least n if row-major layout is used.

stride_a

Stride between the different A matrices. If matrices are stored using column major layout, stride_a must be at least lda*n. If matrices are stored using row major layout, stride_a must be at least lda*m.

b

Buffer holding the output matrices B with size stride_b * batch_size.

ldb

The leading dimension of the matrices B. It must be positive.

	B not transposed	B transposed
Column major	ldb must be at least m.	ldb must be at least n.
Row major	ldb must be at least n.	ldb must be at least m.

stride_b

Stride between different B matrices.

	B not transposed	B transposed
Column major	stride_b must be at least ldb x n.	stride_b must be at least ldb x m.
Row major	stride_b must be at least ldb x m.	stride_b must be at least ldb x n.

batch_size

Specifies the number of matrix transposition or copy operations to perform.

Output Parameters

b

Output buffer, overwritten by batch_size matrix copy or transposition operations of the form alpha * op(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::math::invalid_argument

oneapi::math::unsupported_device

oneapi::math::host_bad_alloc

oneapi::math::device_bad_alloc

oneapi::math::unimplemented

omatcopy_batch (USM Version)

Description

The USM version of omatcopy_batch supports the group API and the strided API.

The operation for the group API is defined as:

idx = 0
for i = 0 … group_count – 1
    m, n, alpha, lda, ldb and group_size at position i in their respective arrays
    for j = 0 … group_size – 1
        A and B are matrices at position idx in their respective arrays
        B := alpha * op(A)
        idx := idx + 1
    end for
end for

The operation for the strided API is defined as:

for i = 0 … batch_size – 1
    A and B are matrices at offset i * stridea in a and i * strideb in b
    B := alpha * op(A)
end for

where:

op(X) is one of op(X) = X, or op(X) = X^T, or op(X) = X^H,

alpha is a scalar,

A and B are input and output matrices,

A is m x n,

and B is m x n if the matrix is not transposed or n by m if it is.

For the group API, the matrices are given by arrays of pointers. A and B represent matrices stored at addresses pointed to by a_array and b_array respectively. The number of entries in a_array and b_array is given by:

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

For the strided API, the single input array contains all the input matrices, and the single output array contains all the output matrices. The locations of the individual matrices within the array are given by stride lengths, while the number of matrices is given by the batch_size parameter.

Group API

Syntax

namespace oneapi::math::blas::column_major {
    sycl::event omatcopy_batch(sycl::queue &queue,
                               const oneapi::math::transpose *trans_array,
                               const std::int64_t *m_array,
                               const std::int64_t *n_array,
                               const T *alpha_array,
                               const T **a_array,
                               const std::int64_t *lda_array,
                               T **b_array,
                               const std::int64_t *ldb_array,
                               std::int64_t group_count,
                               const std::int64_t *groupsize,
                               const std::vector<sycl::event> &dependencies = {});
}

namespace oneapi::math::blas::row_major {
    sycl::event omatcopy_batch(sycl::queue &queue,
                               const oneapi::math::transpose *trans_array,
                               const std::int64_t *m_array,
                               const std::int64_t *n_array,
                               const T *alpha_array,
                               const T **a_array,
                               const std::int64_t *lda_array,
                               T **b_array,
                               const std::int64_t *ldb_array,
                               std::int64_t group_count,
                               const std::int64_t *groupsize,
                               const std::vector<sycl::event> &dependencies = {});
}

Input Parameters

queue

The queue where the routine should be executed.

trans_array

Array of size group_count. Each element i in the array specifies op(A) the transposition operation applied to the matrices A.

m_array

Array of size group_count of number of rows of A. Each must be at least 0.

n_array

Array of size group_count of number of columns of A. Each must be at least 0.

alpha_array

Array of size group_count containing scaling factors for the matrix transpositions or copies.

a_array

Array of size total_batch_count, holding pointers to arrays used to store A matrices.

lda_array

Array of size group_count of leading dimension of the A matrices. If matrices are stored using column major layout, lda_array[i] must be at least m_array[i]. If matrices are stored using row major layout, lda_array[i] must be at least n_array[i]. Each must be positive.

b_array

Array of size total_batch_count of pointers used to store B matrices. The array allocated for each B matrix of the group i must be of size at least:

	B not transposed	B transposed
Column major	ldb_array[i] x n_array[i]	ldb_array[i] x m_array[i]
Row major	ldb_array[i] x m_array[i]	ldb_array[i] x n_array[i]

ldb_array

Array of size group_count. The leading dimension of the output matrix B. Each entry ldb_array[i] must be positive and at least:

	B not transposed	B transposed
Column major	ldb[i] must be at least m_array[i].	ldb[i] must be at least n_array[i].
Row major	ldb[i] must be at least n_array[i].	ldb[i] must be at least m_array[i].

group_count

Number of groups. Must be at least 0.

group_size

Array of size group_count. The element group_size[i] is the number of matrices in the group i. Each element in group_size must be at least 0.

dependencies

List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.

Output Parameters

b_array

Output array of pointers to B matrices, overwritten by total_batch_count matrix transpose or copy operations of the form alpha*op(A).

Return Values

Output event to wait on to ensure computation is complete.

Strided API

Syntax

namespace oneapi::math::blas::column_major {
    event omatcopy_batch(queue &queue,
        transpose trans,
        std::int64_t m,
        std::int64_t n,
        value_or_pointer<T> alpha,
        const T *a,
        std::int64_t lda,
        std::int64_t stride_a,
        T *b,
        std::int64_t ldb,
        std::int64_t stride_b,
        std::int64_t batch_size,
        const std::vector<sycl::event> &dependencies = {});
}

namespace oneapi::math::blas::row_major {
    event omatcopy_batch(queue &queue,
        transpose trans,
        std::int64_t m,
        std::int64_t n,
        value_or_pointer<T> alpha,
        const T *a,
        std::int64_t lda,
        std::int64_t stride_a,
        T *b,
        std::int64_t ldb,
        std::int64_t stride_b,
        std::int64_t batch_size,
        const vector_class<event> &dependencies = {});
}

Input Parameters

queue

The queue where the routine will be executed.

trans

Specifies op(A), the transposition operation applied to the matrices A.

m

Number of rows for each matrix A. Must be at least 0.

n

Number of columns for each matrix B. Must be at least 0.

alpha

Scaling factor for the matrix transpose or copy operation. See Scalar Arguments in BLAS for more details.

a

Array holding the matrices A. Must have size at least stride_a*batch_size.

lda

Leading dimension of the A matrices. If matrices are stored using column major layout, lda must be at least m. If matrices are stored using row major layout, lda must be at least n. Must be positive.

stride_a

Stride between the different A matrices. If matrices are stored using column major layout, stride_a must be at least lda*n. If matrices are stored using row major layout, stride_a must be at least lda*m.

b

Array holding the matrices B. Must have size at least stride_b*batch_size.

ldb

Leading dimension of the B matrices. Must be positive.

	B not transposed	B transposed
Column major	ldb must be at least m.	ldb must be at least n.
Row major	ldb must be at least n.	ldb must be at least m.

stride_b

Stride between different B matrices.

	B not transposed	B transposed
Column major	stride_b must be at least ldb x n.	stride_b must be at least ldb x m.
Row major	stride_b must be at least ldb x m.	stride_b must be at least ldb x n.

batch_size

Specifies the number of matrices to transpose or copy.

dependencies

List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.

Output Parameters

b

Output array, overwritten by batch_size matrix transposition or copy operations of the form alpha*op(A).

Return Values

Output event to wait on to ensure computation is complete.

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::math::invalid_argument

oneapi::math::unsupported_device

oneapi::math::host_bad_alloc

oneapi::math::device_bad_alloc

oneapi::math::unimplemented

Parent topic: BLAS-like Extensions