#define min(x,y) (((x) < (y)) ? (x) : (y))

#include <stdio.h>

#include <stdlib.h>

#include <cublas_v2.h>

#include <iostream>

#include <vector>

//extern "C"

//{

   #include <cblas.h>

//}

using namespace std;

int main()

{

    const enum CBLAS_ORDER Order=CblasRowMajor;

    const enum CBLAS_TRANSPOSE TransA=CblasNoTrans;

    const enum CBLAS_TRANSPOSE TransB=CblasNoTrans;

    const int M=;//A的行数，C的行数

    const int N=;//B的列数，C的列数

    const int K=;//A的列数，B的行数

    const float alpha=;

    const float beta=;

    const int lda=K;//A的列

    const int ldb=N;//B的列

    const int ldc=N;//C的列

    const float A[M*K]={,,,,,,,,,,,};

    const float B[K*N]={,,,,,};

    float C[M*N];

    cblas_sgemm(Order, TransA, TransB, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc);

    for(int i=;i<M;i++)

    {

       for(int j=;j<N;j++)

       {

           cout<<C[i*N+j]<<"\n";

       }

       cout<<endl;

    }

    return EXIT_SUCCESS;

}

cblas_sgemm

Multiplies two matrices (single-precision).

void cblas_sgemm (

const enum CBLAS_ORDER Order,  // Specifies row-major (C) or column-major (Fortran) data ordering.

//typedef enum CBLAS_ORDER     {CblasRowMajor=101, CblasColMajor=102} CBLAS_ORDER;

const enum CBLAS_TRANSPOSE TransA,//Specifies whether to transpose matrix A.

const enum CBLAS_TRANSPOSE TransB,

const int M,   //Number of rows in matrices A and C.

const int N,//Number of rows in matrices A and C.

const int K,  //Number of columns in matrix A; number of rows in matrix B

const float alpha, //Scaling factor for the product of matrices A and B

const float *A,

const int lda, //The size of the first dimention of matrix A; if you are passing a matrix A[m][n], the value should be m.  stride

lda, ldb and ldc (the strides) are not relevant to my problem after all, but here's an explanation of them : 

The elements of a matrix (i.e a 2D array) are stored contiguously in memory. However, they may be stored in either column-major or row-major fashion. The stride represents the distance in memory between elements in adjacent rows (if row-major) or in adjacent columns (if column-major). This means that the stride is usually equal to the number of rows/columns in the matrix.

Matrix A =
[1 2 3]
[4 5 6]
Row-major stores values as {1,2,3,4,5,6}
Stride here is 3

Col-major stores values as {1, 4, 2, 5, 3, 6}
Stride here is 2

Matrix B =
[1 2 3]
[4 5 6]
[7 8 9]

Col-major storage is {1, 4, 7, 2, 5, 8, 3, 6, 9}
Stride here is 3

Read more: http://www.physicsforums.com 

const float *B,

const int ldb,  //The size of the first dimention of matrix B; if you are passing a matrix B[m][n], the value should be m.

const float beta,  //Scaling factor for matrix C.

float *C,

const int ldc    //The size of the first dimention of matrix C; if you are passing a matrix C[m][n], the value should be m.

);

Thus, it calculates either

C←αAB + βC

or

C←αBA + βC

with optional use of transposed forms of A, B, or both.

typedef enum CBLAS_ORDER     {CblasRowMajor=101, CblasColMajor=102} CBLAS_ORDER;

typedef enum CBLAS_TRANSPOSE {CblasNoTrans=111, CblasTrans=112, CblasConjTrans=113, CblasConjNoTrans=114} CBLAS_TRANSPOSE;

cblas_sgemv

Multiplies a matrix by a vector (single precision).

void cblas_sgemv (

const enum CBLAS_ORDER Order,

const enum CBLAS_TRANSPOSE TransA,

const int M,

const int N,

const float alpha,

const float *A,

const int lda,

const float *X,

const int incX,

const float beta,

float *Y,

const int incY

);

#include <OpenBlas/cblas.h>

#include <OpenBlas/common.h>

#include <iostream>

#include <vector>

int main()

{

    blasint n = ;

    blasint in_x =;

    blasint in_y =;

    std::vector<double> x(n);

    std::vector<double> y(n);

    double alpha = ;

    std::fill(x.begin(),x.end(),1.0);

    std::fill(y.begin(),y.end(),2.0);

    cblas_daxpy( n, alpha, &x[], in_x, &y[], in_y);

    //Print y

    for(int j=;j<n;j++)

        std::cout << y[j] << "\t";

    std::cout << std::endl;

}

cublas

cublasStatus_t
cublasCreate(cublasHandle_t *handle)

Return Value Meaning
CUBLAS_STATUS_SUCCESS the initialization succeeded
CUBLAS_STATUS_NOT_INITIALIZED the CUDATM Runtime initialization failed
CUBLAS_STATUS_ALLOC_FAILED the resources could not be allocated

cublasStatus_t
cublasDestroy(cublasHandle_t handle)

Return Value Meaning
CUBLAS_STATUS_SUCCESS the shut down succeeded
CUBLAS_STATUS_NOT_INITIALIZED the library was not initialized

cublasStatus_t cublasSgemm(cublasHandle_t handle,  // 唯一的不同：handle to the cuBLAS library context.

cublasOperation_t transa,
 cublasOperation_t transb

int m,
 int n, 
int k,

const float *alpha,

const float*A, 
int lda,

const float*B, 
int ldb,

const float*beta,

float*C,
 int ldc
)

void cblas_sgemm (

const enum CBLAS_ORDER Order,  // Specifies row-major (C) or column-major (Fortran) data ordering.

//typedef enum CBLAS_ORDER     {CblasRowMajor=101, CblasColMajor=102} CBLAS_ORDER;

const enum CBLAS_TRANSPOSE TransA,//Specifies whether to transpose matrix A.

const enum CBLAS_TRANSPOSE TransB,

const int M,   //Number of rows in matrices A and C.

const int N,//Number of rows in matrices A and C.

const int K,  //Number of columns in matrix A; number of rows in matrix B

const float alpha, //Scaling factor for the product of matrices A and B

const float *A,

const int lda, //The size of the first dimention of matrix A; if you are passing a matrix A[m][n], the value should be m.

const float *B,

const int ldb,  //The size of the first dimention of matrix B; if you are passing a matrix B[m][n], the value should be m.

const float beta,  //Scaling factor for matrix C.

float *C,

const int ldc    //The size of the first dimention of matrix C; if you are passing a matrix C[m][n], the value should be m.

);