转来的，来自：http://www.cnblogs.com/huashiyiqike/p/3886670.html
总结的很赞，转到这里，留一下笔记。感觉cblas的函数名字很好记的，试着去找过源代码，但是是fortran的，我当时写过的那些fortran程序早忘记了。
Y=alpha * X +beta*Y
Y=alpha * X +beta*Y template <>void caffe_cpu_axpby(const int N, const float alpha, const float* X, const float beta, float* Y) { cblas_saxpby(N, alpha, X, 1, beta, Y, 1);}template <>void caffe_cpu_axpby (const int N, const double alpha, const double* X, const double beta, double* Y) { cblas_daxpby(N, alpha, X, 1, beta, Y, 1);} cblas_dscal(N, beta, Y, incY); Y=Y*beta cblas_daxpy(N, alpha, X, incX, Y, incY); Y= (alpha * X) + Y)
Y=alpha * X + Y
template <>void caffe_axpy(const int N, const float alpha, const float* X, float* Y) { cblas_saxpy(N, alpha, X, 1, Y, 1); }template <>void caffe_axpy (const int N, const double alpha, const double* X, double* Y) { cblas_daxpy(N, alpha, X, 1, Y, 1); }
DEFINE_VSL_BINARY_FUNC(Add, y[i] = a[i] + b[i]);DEFINE_VSL_BINARY_FUNC(Sub, y[i] = a[i] - b[i]);DEFINE_VSL_BINARY_FUNC(Mul, y[i] = a[i] * b[i]);DEFINE_VSL_BINARY_FUNC(Div, y[i] = a[i] / b[i]);template <>void caffe_add(const int n, const float* a, const float* b,float* y) {vsAdd(n, a, b, y);}template <>void caffe_add (const int n, const double* a, const double* b,double* y) {vdAdd(n, a, b, y);}
y=x;
template <>void caffe_copy(const int N, const float* X, float* Y) { cblas_scopy(N, X, 1, Y, 1);}template <>void caffe_copy (const int N, const double* X, double* Y) { cblas_dcopy(N, X, 1, Y, 1);}template <>void caffe_gpu_copy (const int N, const float* X, float* Y) { CUBLAS_CHECK(cublasScopy(Caffe::cublas_handle(), N, X, 1, Y, 1));}template <>void caffe_gpu_copy (const int N, const double* X, double* Y) { CUBLAS_CHECK(cublasDcopy(Caffe::cublas_handle(), N, X, 1, Y, 1));}
Computes alpha*x*y' + A.
cblas_sgerMultiplies vector X by the transform of vector Y, then adds matrix A (single precison).Multiplies vector X by the transform of vector Y, then adds matrix A (single precison).void cblas_sger (const enum CBLAS_ORDER Order,const int M,const int N,const float alpha,const float *X,const int incX,const float *Y,const int incY,float *A,const int lda);
Y(vetor)←αAX + βYThis function multiplies A * X (after transposing A, if needed) and multiplies the resulting matrix by alpha.It then multiplies vector Y by beta. It stores the sum of these two products in vector Y.template <>void caffe_cpu_gemv(const CBLAS_TRANSPOSE TransA, const int M, const int N, const float alpha, const float* A, const float* x, const float beta, float* y) { cblas_sgemv(CblasRowMajor, TransA, M, N, alpha, A, N, x, 1, beta, y, 1);}
C(matrix)←αAB + βC
templatevoid gpu_multmat(T* A, T* B, T* C, int M,int K,int N){ const T alpha = 1,beta=0; caffe_gpu_gemm(CblasNoTrans,CblasNoTrans,M,N,K,alpha,A,B,beta,C);}template<>void caffe_cpu_gemm (const CBLAS_TRANSPOSE TransA, const CBLAS_TRANSPOSE TransB, const int M, const int N, const int K, const float alpha, const float* A, const float* B, const float beta, float* C) { int lda = (TransA == CblasNoTrans) ? K : M; int ldb = (TransB == CblasNoTrans) ? N : K; cblas_sgemm(CblasRowMajor, TransA, TransB, M, N, K, alpha, A, lda, B, ldb, beta, C, N);}
A=M*N B=M*KC=A'*B N M Ktemplatevoid cpu_multTmat(T* A, T* B, T* C, int M,int K,int N){ const T alpha = 1,beta=0; caffe_cpu_gemm(CblasTrans,CblasNoTrans,M,N,K,alpha,A,B,beta,C); // cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans, M, N, K, alpha, A, M, B, K, beta, C, M);}A=M*N B=N*KC=A*B M N Ktemplate void cpu_multmat(T* A, T* B, T* C, int M,int K,int N){ const T alpha = 1,beta=0; caffe_cpu_gemm(CblasNoTrans,CblasNoTrans,M,N,K,alpha,A,B,beta,C); // cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans, M, N, K, alpha, A, M, B, K, beta, C, M);}