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Visible to Intel only — GUID: GUID-B7F142EE-6AEB-4535-8B95-AC61C9C34EDE
Visible to Intel only — GUID: GUID-B7F142EE-6AEB-4535-8B95-AC61C9C34EDE
gemm_bias
Computes a matrix-matrix product using general integer matrices with bias.
Description
The gemm_bias routines compute a scalar-matrix-matrix product and add the result to a scalar-matrix product, using general integer matrices with biases/offsets. The operation is defined as:
where:
op(X) is one of op(X) = X, or op(X) = XT, or op(X) = XH
alpha and beta are scalars
A_offset is m x k matrix with every element equal to the value ao
B_offset is k x n matrix with every element equal to the value bo
C_offset is m x n matrix defined by the co buffer. See Data Types for more details.
A, B, and C are matrices
op(A) is m x k, op(B) is k x n, and C is m x n
gemm_bias supports the following precisions:
Ta |
Tb |
|---|---|
std::uint8_t |
std::uint8_t |
std::int8_t |
std::uint8_t |
std::uint8_t |
std::int8_t |
std::int8_t |
std::int8_t |
gemm_bias (Buffer Version)
Syntax
namespace oneapi::mkl::blas::column_major {
void gemm_bias(sycl::queue &queue,
oneapi::mkl::transpose transa,
oneapi::mkl::transpose transb,
oneapi::mkl::offset offsetc,
std::int64_t m,
std::int64_t n,
std::int64_t k,
float alpha,
sycl::buffer<Ta,1> &a,
std::int64_t lda,
Ta ao,
sycl::buffer<Tb,1> &b,
std::int64_t ldb,
Tb bo,
float beta,
sycl::buffer<std::int32_t,1> &c,
std::int64_t ldc,
sycl::buffer<std::int32_t,1> &co,
compute_mode mode = compute_mode::unset)
}
namespace oneapi::mkl::blas::row_major {
void gemm_bias(sycl::queue &queue,
oneapi::mkl::transpose transa,
oneapi::mkl::transpose transb,
oneapi::mkl::offset offsetc,
std::int64_t m,
std::int64_t n,
std::int64_t k,
float alpha,
sycl::buffer<Ta,1> &a,
std::int64_t lda,
Ta ao,
sycl::buffer<Tb,1> &b,
std::int64_t ldb,
Tb bo,
float beta,
sycl::buffer<std::int32_t,1> &c,
std::int64_t ldc,
sycl::buffer<std::int32_t,1> &co,
compute_mode mode = compute_mode::unset)
}
Input Parameters
- queue
-
The queue where the routine should be executed.
- transa
-
Specifies op(A), the transposition operation applied to matrix A. See Data Types for more details.
- transb
-
Specifies op(B), the transposition operation applied to matrix B. See Data Types for more details.
- offsetc
-
Specifies the form of C_offset used in the matrix multiplication. See Data Types for more details.
- m
-
Number of rows of matrix op(A) and matrix C. Must be at least zero.
- n
-
Number of columns of matrix op(B) and matrix C. Must be at least zero.
- k
-
Number of columns of matrix op(A) and rows of matrix op(B). Must be at least zero.
- alpha
-
Scaling factor for matrix-matrix product.
- a
-
Buffer holding input matrix A. See Matrix Storage for more details.
transa = transpose::nontrans
transa = transpose::trans or trans = transpose::conjtrans
Column major
A is m x k matrix. Size of array a must be at least lda * k
A is k x m matrix. Size of array a must be at least lda * m
Row major
A is m x k matrix. Size of array a must be at least lda * m
A is k x m matrix. Size of array a must be at least lda * k
- lda
-
Leading dimension of matrix A. Must be positive.
transa = transpose::nontrans
transa = transpose::trans or trans = transpose::conjtrans
Column major
Must be at least m
Must be at least k
Row major
Must be at least k
Must be at least m
- ao
-
Specifies the scalar offset value for matrix A.
- b
-
Buffer holding input matrix B. See Matrix Storage for more details.
transb = transpose::nontrans
transb = transpose::trans or trans = transpose::conjtrans
Column major
B is k x n matrix. Size of array b must be at least ldb * n
B is n x k matrix. Size of array b must be at least ldb * k
Row major
B is k x n matrix. Size of array b must be at least ldb * k
B is n x k matrix. Size of array b must be at least ldb * n
- ldb
-
Leading dimension of matrix B. Must be positive.
transb = transpose::nontrans
transb = transpose::trans or trans = transpose::conjtrans
Column major
Must be at least k
Must be at least n
Row major
Must be at least n
Must be at least k
- bo
-
Specifies the scalar offset value for matrix B.
- beta
-
Scaling factor for matrix C.
- c
-
Buffer holding input/output matrix C. See Matrix Storage for more details.
Column major
C is m x n matrix. Size of array c must be at least ldc * n
Row major
C is m x n matrix. Size of array c must be at least ldc * m
- ldc
-
Leading dimension of matrix C. Must be positive.
Column major
Must be at least m
Row major
Must be at least n
- co
-
Buffer holding the offset values for matrix C.
If offset_type = offset::fix, size of co array must be at least 1.
If offset_type = offset::col, size of co array must be at least max(1,m).
If offset_type = offset::row, size of co array must be at least max(1,n).
See Data Types for more details.
- mode
-
Optional. Compute mode settings. See Compute Modes for more details.
Output Parameters
- c
-
Output buffer overwritten by alpha * (op(A) - A_offset) * (op(B) - B_offset) + beta * C + C_offset.
gemm_bias (USM Version)
Syntax
namespace oneapi::mkl::blas::column_major {
sycl::event gemm_bias(sycl::queue &queue,
oneapi::mkl::transpose transa,
oneapi::mkl::transpose transb,
oneapi::mkl::offset offsetc,
std::int64_t m,
std::int64_t n,
std::int64_t k,
float alpha,
const Ta *a,
std::int64_t lda,
Ta ao,
const Tb *b,
std::int64_t ldb,
Tb bo,
float beta,
std::int32_t *c,
std::int64_t ldc,
const std::int32_t *co,
compute_mode mode = compute_mode::unset,
const std::vector<sycl::event> &dependencies = {})
}
namespace oneapi::mkl::blas::row_major {
sycl::event gemm_bias(sycl::queue &queue,
oneapi::mkl::transpose transa,
oneapi::mkl::transpose transb,
oneapi::mkl::offset offsetc,
std::int64_t m,
std::int64_t n,
std::int64_t k,
float alpha,
const Ta *a,
std::int64_t lda,
Ta ao,
const Tb *b,
std::int64_t ldb,
Tb bo,
float beta,
std::int32_t *c,
std::int64_t ldc,
const std::int32_t *co,
compute_mode mode = compute_mode::unset,
const std::vector<sycl::event> &dependencies = {})
}
Input Parameters
- queue
-
The queue where the routine should be executed.
- transa
-
Specifies op(A), the transposition operation applied to matrix A. See Data Types for more details.
- transb
-
Specifies op(B), the transposition operation applied to matrix B. See Data Types for more details.
- offsetc
-
Specifies the form of C_offset used in the matrix multiplication. See Data Types for more details.
- m
-
Number of rows of matrix op(A) and matrix C. Must be at least zero.
- n
-
Number of columns of matrix op(B) and matrix C. Must be at least zero.
- k
-
Number of columns of matrix op(A) and rows of matrix op(B). Must be at least zero.
- alpha
-
Scaling factor for matrix-matrix product.
- a
-
Pointer to input matrix A. See Matrix Storage for more details.
transa = transpose::nontrans
transa = transpose::trans or trans = transpose::conjtrans
Column major
A is m x k matrix. Size of array a must be at least lda * k
A is k x m matrix. Size of array a must be at least lda * m
Row major
A is m x k matrix. Size of array a must be at least lda * m
A is k x m matrix. Size of array a must be at least lda * k
- lda
-
Leading dimension of matrix A. Must be positive.
transa = transpose::nontrans
transa = transpose::trans or trans = transpose::conjtrans
Column major
Must be at least m
Must be at least k
Row major
Must be at least k
Must be at least m
- ao
-
Specifies the scalar offset value for matrix A.
- b
-
Pointer to input matrix B. See Matrix Storage for more details.
transb = transpose::nontrans
transb = transpose::trans or trans = transpose::conjtrans
Column major
B is k x n matrix. Size of array b must be at least ldb * n
B is n x k matrix. Size of array b must be at least ldb * k
Row major
B is k x n matrix. Size of array b must be at least ldb * k
B is n x k matrix. Size of array b must be at least ldb * n
- ldb
-
Leading dimension of matrix B. Must be positive.
transb = transpose::nontrans
transb = transpose::trans or trans = transpose::conjtrans
Column major
Must be at least k
Must be at least n
Row major
Must be at least n
Must be at least k
- bo
-
Specifies the scalar offset value for matrix B.
- beta
-
Scaling factor for matrix C.
- c
-
Pointer to input/output matrix C. See Matrix Storage for more details.
Column major
C is m x n matrix. Size of array c must be at least ldc * n
Row major
C is m x n matrix. Size of array c must be at least ldc * m
- ldc
-
Leading dimension of matrix C. Must be positive.
Column major
Must be at least m
Row major
Must be at least n
- co
-
Pointer to array holding offset values for matrix C.
If offset_type = offset::fix, size of co array must be at least 1.
If offset_type = offset::col, size of co array must be at least max(1,m).
If offset_type = offset::row, size of co array must be at least max(1,n).
See Data Types for more details.
- mode
-
Optional. Compute mode settings. See Compute Modes for more details.
- dependencies
-
Optional. List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.
mode and dependencies may be omitted independently; it is not necessary to specify mode in order to provide dependencies.
Output Parameters
- c
-
Pointer to output matrix C overwritten by alpha * (op(A) - A_offset) * (op(B) - B_offset) + beta * C + C_offset.
Return Values
Output event to wait on to ensure computation is complete.