Function: s8gemv

Applicability

Product	Supported
Atlas 350 Accelerator Card	√
Atlas A3 training product / Atlas A3 inference product	√
Atlas A2 training product / Atlas A2 inference product	√
Atlas training product	√
Atlas inference product	√
Atlas 200I/500 A2 inference product	√

Function Usage

Computes matrix-vector multiplication: y = αAx + βy. The input data type is int8_t, and the output data type is int32_t. This API is asynchronous.

Prototype

C Prototype

        
             aclError aclblasS8gemv(aclTransType transA,
int m,
int n,
const int32_t *alpha,
const int8_t *a,
int lda,
const int8_t *x,
int incx,
const int32_t *beta,
int32_t *y,
int incy,
aclComputeType type,
aclrtStream stream)

Python Function

        
             ret = acl.blas.s8gemv(trans_a, m, n, alpha, a, lda, x, incx, beta, y, incy, type, stream)

Parameters

Parameter	Description
trans_a	Int, whether matrix A is transposed.
m	Int, number of rows in matrix A (row-major first in data storing).
n	Int, number of columns in matrix A.
alpha	Int, data pointer address of scalar alpha used for executing the multiplication operation.
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.
x	Int, data pointer address of vector x.
incx	Int, increment between successive x elements. This parameter is reserved and can only be set to –1.
beta	Int, data pointer address of scalar beta used for executing the multiplication operation.
y	Int, data pointer address of vector y.
incy	Int, increment between successive y elements. This parameter is reserved and can only be set to –1.
type	Int, computation precision.
stream	Int, stream where the operator is executed.

Returns

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

Reference

For the API call sequence, see API Call Sequence.

Parent topic: CBLAS Interfaces (blas)