aclblasGemvEx

Applicability

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

Description

Computes matrix-vector multiplication: y = αAx + βy. The data types of the input and output data are set using arguments. This API is asynchronous.

A, x, and y support a limited combination of data types, where α and β have the same data types as y.

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

Prototype

aclError aclblasGemvEx(aclTransType transA,
int m,
int n,
const void *alpha,
const void *a,
int lda,
aclDataType dataTypeA,
const void *x,
int incx,
aclDataType dataTypeX,
const void *beta,
void *y,
int incy,
aclDataType dataTypeY,
aclComputeType type,
aclrtStream stream)

Parameters

Parameter	Input/Output	Description
transA	Input	Transpose flag of matrix A.
m	Input	Number of rows in matrix A (row-major first in data storing).
n	Input	Number of columns in matrix A.
alpha	Input	Pointer to scalar α used for executing the multiplication operation.
a	Input	Pointer to matrix A.
lda	Input	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.
dataTypeA	Input	Data type of matrix A.
x	Input	Pointer to vector x.
incx	Input	Increment between successive x elements. This parameter is reserved and can only be set to –1.
dataTypeX	Input	Data type of vector x.
beta	Input	Pointer to scalar β used for executing the multiplication operation.
y	Input/Output	Pointer to vector y.
incy	Input	Increment between successive y elements. This parameter is reserved and can only be set to –1.
dataTypeY	Input	Data type of vector y.
type	Input	Computation precision type (high precision by default).
stream	Input	Stream where the operator is executed.

Returns