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dgmm_batch
Computes a group of (diagonal matrix-matrix product (dgmm) operations.
Description
The dgmm_batch routines perform multiple diagonal matrix-matrix product (dgmm) operations in a single call. The diagonal matrices are stored as dense vectors and the operations are performed with groups of matrices and vectors.
dgmm_batch supports the following precisions:
T |
|---|
float |
double |
std::complex<float> |
std::complex<double> |
dgmm_batch (Buffer Version)
Buffer version of dgmm_batch supports only strided API.
Strided API
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
if (left_right == side::left)
C = diag(X) * A
else
C = A * diag(X)
end for
where:
A is a matrix
X is a diagonal matrix stored as a vector
For strided API, all matrices A and C and vector X have the same parameters (size, increments) and are stored at a constant stride given by stridea, stridec and stridex from each other.
The a and x buffers contain all the input matrices. Total number of matrices in a and x are given by batch_size parameter.
Syntax
namespace oneapi::mkl::blas::column_major {
void dgmm_batch(sycl::queue &queue,
oneapi::mkl::side left_right,
std::inte64_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,
oneapi::mkl::side left_right,
std::inte64_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 Data Types for more details.
- m
-
Number of rows of matrix A and matrix C. Must be at least zero.
- n
-
Number of columns of matrix A and matrix C. Must be at least zero.
- a
-
Buffer holding input matrices A. Size of the buffer must be at least lda * k + stridea * (batch_size - 1) where k is n if column major layout or m if row major layout is used.
- lda
-
Leading dimension of matrices A. Must be at least m if column major layout or n if row major layout is used. Must be positive.
- stridea
-
Stride between two consecutive A matrices. Must be at least zero. See Matrix Storage for more details.
- x
-
Buffer holding input matrices X. Size of the buffer must be 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 two consecutive X vectors. Must be at least zero. See Matrix Storage for more details.
- c
-
Buffer holding input/output matrices C. Size of the buffer must be at least batch_size * stridec.
- ldc
-
Leading dimension of matrices C. Must be at least m if column major layout or n if row major layout is used. Must be positive.
- stridec
-
Stride between two consecutive C matrices. Must be at least ldc * n if column major layout or ldc * m if row major layout is used. See Matrix Storage for more details.
- batch_size
-
Number of dgmm computations to perform. Must be at least zero.
Output Parameters
- c
-
Buffer holding output matrices C overwritten by batch_sizedgmm operations.
dgmm_batch (USM Version)
USM version of dgmm_batch supports group API and 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 and C are matrices at a[idx] and c[idx]
X is a vector at x[idx]
if (left_right[idx] == side::left)
C = diag(X) * A
else
C = A * diag(X)
idx = idx + 1
end for
end for
where:
A is a matrix
X is a diagonal matrix stored as a vector
For group API, each group contain matrices and vectors with the same parameters (size, increment). The a and x arrays contain the pointers for all the input matrices. Total number of matrices in a and x are given by:
Syntax
namespace oneapi::mkl::blas::column_major {
sycl::event dgmm_batch(sycl::queue &queue,
const oneapi::mkl::side *left_right,
const std::int64_t *m,
const std::int64_t *n,
const T **a,
const std::int64_t *lda,
const T **x,
const std::int64_t *incx,
T **c,
const std::int64_t *ldc,
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 dgmm_batch(sycl::queue &queue,
const oneapi::mkl::side *left_right,
const std::int64_t *m,
const std::int64_t *n,
const T **a,
const std::int64_t *lda,
const T **x,
const std::int64_t *incx,
T **c,
const std::int64_t *ldc,
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.
- left_right
-
Array of group_count parameters. left_right[i] specifies the position of the diagonal matrix in group i. See Data Types for more details.
- m
-
Array of group_count integers. m[i] specifies 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 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. Size of the array must be at least lda[i] * n[i] if column major layout 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 or at least n[i] if row major layout is used.
- x
-
Array of pointers to input vectors X with size total_batch_count. Size of the array must be at least (1 + len[i] – 1)*abs(incx[i])) where len[i] is n[i] if 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. Size of the array must be least ldc[i] * n[i] if column major layout 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 at least m[i] if column major layout or at least n[i] if row major layout is used.
- group_count
-
Specifies number of groups. Must be at least zero.
- 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 zero.
- dependencies
-
List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.
Output Parameters
- c
-
Array of pointers to output matrices C overwritten by total_batch_countdgmm operations.
Return Values
Output event to wait on to ensure computation is complete.
Strided API
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
if (left_right == side::left)
C = diag(X) * A
else
C = A * diag(X)
end for
where:
A is a matrix
X is a diagonal matrix stored as a vector
For strided API, all matrices A and C and vector X have the same parameters (size, increments) and are stored at a constant stride given by stridea, stridec and stridex from each other.
The a and x buffers contain all the input matrices. Total number of matrices in a and x are given by batch_size parameter.
Syntax
namespace oneapi::mkl::blas::column_major {
sycl::event dgmm_batch(sycl::queue &queue,
oneapi::mkl::side left_right,
std::inte64_t m,
std::int64_t n,
const T *a,
std::int64_t lda,
std::int64_t stridea,
const T *x,
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,
oneapi::mkl::side left_right,
std::inte64_t m,
std::int64_t n,
const T *a,
std::int64_t lda,
std::int64_t stridea,
const T *x,
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 Data Types for more details.
- m
-
Number of rows of matrix A and matrix C. Must be at least zero.
- n
-
Number of columns of matrix A and matrix C. Must be at least zero.
- a
-
Pointer to input matrices A. Size of the array must be at least lda * k + stridea * (batch_size - 1) where k is n if column major layout or m if row major layout is used.
- lda
-
Leading dimension of matrices A. Must be at least m if column major layout or n if row major layout is used. Must be positive.
- stridea
-
Stride between two consecutive A matrices. Must be at least zero. See Matrix Storage for more details.
- x
-
Pointer to input matrices X. Size of the array must be 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 two consecutive X vectors. Must be at least zero. See Matrix Storage for more details.
- c
-
Pointer to input/output matrices C. Size of the array must be at least batch_size * stridec.
- ldc
-
Leading dimension of matrices C. Must be at least m if column major layout or n if row major layout is used. Must be positive.
- stridec
-
Stride between two consecutive C matrices. Must be at least ldc * n if column major layout or ldc * m if row major layout is used. See Matrix Storage for more details.
- batch_size
-
Number of dgmm 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
- c
-
Pointer to output matrices C overwritten by batch_sizedgmm operations.
Return Values
Output event to wait on to ensure computation is complete.