Function: gemm_ex

Applicability

Product	Supported (√/x)
Atlas A3 training products / Atlas A3 inference products	√
Atlas A2 training products / Atlas A2 inference products	√
Atlas training products	√
Atlas inference products	√
Atlas 200I/500 A2 inference products	√

Function Usage

Computes matrix-matrix multiplication: C = αAB + βC. The data types of the input and output data are set using arguments. This API is asynchronous.

Prototype

C Prototype

        
         
           
           
             aclError aclblasGemmEx(aclTransType transA,
aclTransType transB,
aclTransType transC,
int m,
int n,
int k,
const void *alpha,
const void *matrixA,
int lda,
aclDataType dataTypeA,
const void *matrixB,
int ldb,
aclDataType dataTypeB,
const void *beta,
void *matrixC,
int ldc,
aclDataType dataTypeC,
aclComputeType type,
aclrtStream stream)

            

          

        
       

Python Function

        
             ret = acl.blas.gemm_ex(trans_a, trans_b, trans_c,
m, n, k,
alpha, matrix_a, lda, data_type_a,
matrix_b, ldb, data_type_b,
beta, matrix_c, ldc, data_type_c,
type, stream)

Parameter Description

Parameter	Description
trans_a	Int, whether matrix A is transposed.
trans_b	Int, whether matrix B is transposed.
trans_c	Int, whether matrix C is transposed. Currently, only aclTrans_N is supported.
m	Int, number of rows in matrix A and matrix C.
n	Int, number of columns in matrix B and matrix C.
k	Int, number of columns in matrix A and number of rows in matrix B.
alpha	Int, data pointer address of scalar alpha used for executing the multiplication operation.
matrix_a	Int, data pointer address of matrix A.
lda	Int, leading dimension of matrix A. For row-major transpose, lda is the number of columns of matrix A. This parameter is reserved and can only be set to –1.
data_type_a	Int, data type of matrix A.
matrix_b	Int, data pointer address of matrix B.
ldb	Int, leading dimension of matrix B. For row-major transpose, ldb is the number of columns of matrix B. This parameter is reserved and can only be set to –1.
data_type_b	Int, data type of matrix B.
beta	Int, data pointer address of scalar beta used for executing the multiplication operation.
matrix_c	Int, data pointer address of matrix C.
ldc	Int, leading dimension of matrix C. This parameter is reserved and can only be set to –1.
data_type_c	Int, data type of matrix C.
type	Int, computation precision.
stream	Int, stream where the operator is executed.

Return Value Description

Return Value	Description
ret	Int, error code: 0 on success; else, failure.

Restrictions

A, B, and C support a limited combination of data types. α and β have the same data types as C.

Data Type of A	Data Type of x	Data Type of y
aclFloat16	aclFloat16	aclFloat16
aclFloat16	aclFloat16	float(float32)
int8_t	int8_t	float(float32)
int8_t	int8_t	int32_t

Reference

For details about the API call sequence and example, see API Call Sequence.

Parent topic: CBLAS Interfaces (blas)