F77NAME(daxpy)(&MN, &a, &X, &one, &Y, &one); 堆栈二维矩阵也一样 double A[3][2]; 由于此内存是按顺序分配的。 否则,您需要使用 for 循环并分别添加每一行。智能推荐numpy.distutils.system_info.NotFoundError: no lapack/blas resources found Python小白求助!引入sklearn时总是出现这句话:numpy...
BLAS daxpy functionalityMichael J. Kane
1. VectorAPI向量化 BLAS库中的函数分为矢量-矢量、矢量-矩阵、矩阵-矩阵的计算,其中多数场景为对数组、矩阵进行计算,因此使用向量化进行优化,一次处理多个数据,提升效率,下面以daxpy函数为例: daxpy => y = alpha * x + y, 其中alpha为常数,x和y为一维向量,数据类型均为double; 原生朴素实现:对x和y中的元...
cblas_daxpy(N, alpha, X, incX, Y, incY); Y= (alpha * X) +Y) Y=alpha * X + Y template <>voidcaffe_axpy<float>(constintN,constfloatalpha,constfloat*X,float* Y) { cblas_saxpy(N, alpha, X,1, Y,1); } template<>voidcaffe_axpy<double>(constintN,constdoublealpha,constdouble*...
void cblas_daxpy(const BLASINT n, const double alpha, const double *x, const BLASINT incx, double *y, const BLASINT incy); void cblas_caxpy(const BLASINT n, const void *alpha, const void *x, const BLASINT incx, void *y, const BLASINT incy); ...
void cblas_daxpy(const BLASINT n, const double alpha, const double *x, const BLASINT incx, double *y, const BLASINT incy); void cblas_caxpy(const BLASINT n, const void *alpha, const void *x, const BLASINT incx, void *y, const BLASINT incy); ...
BLAS库中的函数分为矢量-矢量、矢量-矩阵、矩阵-矩阵的计算,其中多数场景为对数组、矩阵进行计算,因此使用向量化进行优化,一次处理多个数据,提升效率,下面以daxpy函数为例: daxpy => y = alpha * x + y, 其中alpha为常数,x和y为一维向量,数据类型均为double; ...
SAXPY, DAXPY, CAXPY, DAXPY Copies a vector x into vector y y := x SCOPY, DCOPY, CCOPY, DCOPY Computes a dot product of two vectors _dot := x**T*y = SUM(i=1 to n)[ x(i)*y(i) ] _dotc := x**H*y = SUM(i=1 to n)[ x(i)**H*y(i) ] _dotu := x**T*y =...
cblas_daxpy Computes a constant times a vector plus a vector (double-precision). On return, the contents of vector Y are replaced with the result. The value computed is (alpha * X[i]) + Y[i]. #include<OpenBlas/cblas.h>#include<OpenBlas/common.h>#include<iostream>#include<vector>intma...
(n,beta, incy);y=y*beta cblas_daxpy(n, alpha, voidcaffe_axpy<float>(const int constfloat alpha, const float* cblas_saxpy(n,alpha, voidcaffe_axpy<double>(const int constdouble alpha, const double* cblas_daxpy(n,alpha, voidcaffe_add<float>(const int constfloat* constfloat* voidcaffe_...