Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)  0.16
Performance library for Deep Learning
Functions
BLAS functions

Functions

mkldnn_status_t MKLDNN_API mkldnn_sgemm (const char *transa, const char *transb, const int *M, const int *N, const int *K, const float *alpha, const float *A, const int *lda, const float *B, const int *ldb, const float *beta, float *C, const int *ldc)
 SGEMM performs matrix-matrix multiplication operation C := alpha*op( A )*op( B ) + beta*C, where op( X ) is one of op( X ) = X or op( X ) = X**T, alpha and beta are scalars, and A, B and C are matrices, with op( A ) an m by k matrix, op( B ) a k by n matrix and C an m by n matrix. More...
 

Detailed Description

Function Documentation

◆ mkldnn_sgemm()

mkldnn_status_t MKLDNN_API mkldnn_sgemm ( const char *  transa,
const char *  transb,
const int *  M,
const int *  N,
const int *  K,
const float *  alpha,
const float *  A,
const int *  lda,
const float *  B,
const int *  ldb,
const float *  beta,
float *  C,
const int *  ldc 
)

SGEMM performs matrix-matrix multiplication operation C := alpha*op( A )*op( B ) + beta*C, where op( X ) is one of op( X ) = X or op( X ) = X**T, alpha and beta are scalars, and A, B and C are matrices, with op( A ) an m by k matrix, op( B ) a k by n matrix and C an m by n matrix.

Note
API is different compared to standard BLAS routine as it returns mkldnn_status_t for error handling. XERBLA is not supported: no error message will be printed in case of incorrect parameters