dgmm_batch#

Computes a group of dgmm operations.

Description

The dgmm_batch routines perform multiple diagonal matrix-matrix product operations in a single call.

dgmm_batch supports the following precisions.

T

float

double

std::complex<float>

std::complex<double>

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

dgmm_batch (Buffer Version)#

Description

The buffer version of dgmm_batch supports only the strided API.

The strided API operation is defined as:

for i = 0 … batch_size – 1
    A and C are matrices at offset i * stridea in a, i * stridec in c.
    X is a vector at offset i * stridex in x
    C := diag(X) * A or  C = A * diag(X)
end for

where:

A is a matrix,

X is a diagonal matrix stored as a vector

The a and x buffers contain all the input matrices. The stride between matrices is given by the stride parameter. The total number of matrices in a and x buffers is given by the batch_size parameter.

Strided API

Syntax

namespace oneapi::mkl::blas::column_major {
    void dgmm_batch(sycl::queue &queue,
                    onemkl::mkl::side left_right,
                    std::int64_t m,
                    std::int64_t n,
                    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,
                    sycl::buffer<T,1> &c,
                    std::int64_t ldc,
                    std::int64_t stridec,
                    std::int64_t batch_size)
}

namespace oneapi::mkl::blas::row_major {
    void dgmm_batch(sycl::queue &queue,
                    onemkl::mkl::side left_right,
                    std::int64_t m,
                    std::int64_t n,
                    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,
                    sycl::buffer<T,1> &c,
                    std::int64_t ldc,
                    std::int64_t stridec,
                    std::int64_t batch_size)
}

Input Parameters

queue: The queue where the routine should be executed.
left_right: Specifies the position of the diagonal matrix in the product. See oneMKL defined datatypes for more details.
m: Number of rows of matrices A and C. Must be at least zero.
n: Number of columns of matrices A and C. Must be at least zero.

Buffer holding the input matrices A with size stridea * batch_size. Must be of at least lda * j + stridea * (batch_size - 1) where j is n if column major layout is used or m if major layout is used.

lda: The leading dimension of the matrices A. It must be positive and at least m if column major layout is used or at least n if row major layout is used.
stridea: Stride between different A matrices.
x: Buffer holding the input matrices X with size stridex * batch_size. Must be of size at least (1 + (len - 1)*abs(incx)) + stridex * (batch_size - 1) where len is n if the diagonal matrix is on the right of the product or m otherwise.
incx: Stride between two consecutive elements of the x vectors.
stridex: Stride between different X vectors, must be at least 0.
c: Buffer holding input/output matrices C with size stridec * batch_size.
ldc: The leading dimension of the matrices C. It must be positive and at least m if column major layout is used to store matrices or at least n if column major layout is used to store matrices.
stridec: Stride between different C matrices. Must be at least ldc * n if column major layout is used or ldc * m if row major layout is used.
batch_size: Specifies the number of diagonal matrix-matrix product operations to perform.

Output Parameters

c: Output overwritten by batch_size diagonal matrix-matrix product operations.

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

dgmm_batch (USM Version)#

Description

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

The group API operation is defined as:

idx = 0
for i = 0 … group_count – 1
    for j = 0 … group_size – 1
        a and c are matrices of size mxn at position idx in a_array and c_array
        x is a vector of size m or n depending on left_right, at position idx in x_array
        if (left_right == oneapi::mkl::side::left)
            c := diag(x) * a
        else
            c := a * diag(x)
        idx := idx + 1
    end for
end for

The strided API operation is defined as

for i = 0 … batch_size – 1
    A and C are matrices at offset i * stridea in a, i * stridec in c.
    X is a vector at offset i * stridex in x
    C := diag(X) * A or  C = A * diag(X)
end for

where:

A is a matrix,

X is a diagonal matrix stored as a vector

For group API, a and x arrays contain the pointers for all the input matrices. The total number of matrices in a and x are given by:

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

For strided API, a and x arrays contain all the input matrices. The total number of matrices in a and x are given by the batch_size parameter.

Group API

Syntax

namespace oneapi::mkl::blas::column_major {
    sycl::event dgmm_batch(sycl::queue &queue,
                           onemkl::mkl::side *left_right,
                           std::int64_t *m,
                           std::int64_t *n,
                           const T **a,
                           std::int64_t *lda,
                           const T **x,
                           std::int64_t *incx,
                           T **c,
                           std::int64_t *ldc,
                           std::int64_t group_count,
                           std::int64_t *group_size,
                           const std::vector<sycl::event> &dependencies = {})
}

namespace oneapi::mkl::blas::row_major {
    sycl::event dgmm_batch(sycl::queue &queue,
                           onemkl::mkl::side *left_right,
                           std::int64_t *m,
                           std::int64_t *n,
                           const T **a,
                           std::int64_t *lda,
                           const T **x,
                           std::int64_t *incx,
                           T **c,
                           std::int64_t *ldc,
                           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.
left_right: Specifies the position of the diagonal matrix in the product. See oneMKL defined datatypes for more details.
m: Array of group_count integers. m[i] specifies the number of rows of A for every matrix in group i. All entries must be at least zero.
n: Array of group_count integers. n[i] specifies the number of columns of A for every matrix in group i. All entries must be at least zero.
a: Array of pointers to input matrices A with size total_batch_count. Must be of size at least lda[i] * n[i] if column major layout is used or at least lda[i] * m[i] if row major layout is used. See Matrix Storage for more details.
lda: Array of group_count integers. lda[i] specifies the leading dimension of A for every matrix in group i. All entries must be positive and at least m[i] if column major layout is used or at least n[i] if row major layout is used.
x: Array of pointers to input vectors X with size total_batch_count. Must be of size at least (1 + len[i] – 1)*abs(incx[i])) where len[i] is n[i] if the diagonal matrix is on the right of the product or m[i] otherwise. See Matrix Storage for more details.
incx: Array of group_count integers. incx[i] specifies the stride of x for every vector in group i. All entries must be positive.
c: Array of pointers to input/output matrices C with size total_batch_count. Must be of size at least ldc[i] * n[i] if column major layout is used or at least ldc[i] * m[i] if row major layout is used. See Matrix Storage for more details.
ldc: Array of group_count integers. ldc[i] specifies the leading dimension of C for every matrix in group i. All entries must be positive and ldc[i] must be at least m[i] if column major layout is used to store matrices or at least n[i] if row major layout is used to store matrices.
group_count: Specifies the number of groups. Must be at least 0.
group_size: Array of group_count integers. group_size[i] specifies the number of diagonal matrix-matrix product operations in group i. All entries 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

c: Output overwritten by batch_size diagonal matrix-matrix product operations.

Return Values

Output event to wait on to ensure computation is complete.

Strided API

Syntax

namespace oneapi::mkl::blas::column_major {
    sycl::event dgmm_batch(sycl::queue &queue,
                           onemkl::mkl::side left_right,
                           std::int64_t m,
                           std::int64_t n,
                           const T *a,
                           std::int64_t lda,
                           std::int64_t stridea,
                           const T *b,
                           std::int64_t incx,
                           std::int64_t stridex,
                           T *c,
                           std::int64_t ldc,
                           std::int64_t stridec,
                           std::int64_t batch_size,
                           const std::vector<sycl::event> &dependencies = {})
}

namespace oneapi::mkl::blas::row_major {
    sycl::event dgmm_batch(sycl::queue &queue,
                           onemkl::mkl::side left_right,
                           std::int64_t m,
                           std::int64_t n,
                           const T *a,
                           std::int64_t lda,
                           std::int64_t stridea,
                           const T *b,
                           std::int64_t incx,
                           std::int64_t stridex,
                           T *c,
                           std::int64_t ldc,
                           std::int64_t stridec,
                           std::int64_t batch_size,
                           const std::vector<sycl::event> &dependencies = {})
}

Input Parameters

queue: The queue where the routine should be executed.
left_right: Specifies the position of the diagonal matrix in the product. See oneMKL defined datatypes for more details.
m: Number of rows of A. Must be at least zero.
n: Number of columns of A. Must be at least zero.
a: Pointer to input matrices A with size stridea * batch_size. Must be of size at least lda * k + stridea * (batch_size - 1) where k is n if column major layout is used or m if row major layout is used.
lda: The leading dimension of the matrices A. It must be positive and at least m. Must be positive and at least m if column major layout is used or at least n if row major layout is used.
stridea: Stride between different A matrices.
x: Pointer to input matrices X with size stridex * batch_size. Must be of size at least (1 + (len - 1)*abs(incx)) + stridex * (batch_size - 1) where len is n if the diagonal matrix is on the right of the product or m otherwise.
incx: Stride between two consecutive elements of the x vector.
stridex: Stride between different X vectors, must be at least 0.
c: Pointer to input/output matrices C with size stridec * batch_size.
ldc: The leading dimension of the matrices C. It must be positive and at least ldc * m if column major layout is used to store matrices or at least ldc * n if column major layout is used to store matrices.
stridec: Stride between different C matrices. Must be at least ldc * n if column major layout is used or ldc * m if row major layout is used.
batch_size: Specifies the number of diagonal matrix-matrix product operations to perform.