static doublea[100000000];static doubleb[100000000];static doublec[100000000]; cblas_dgemm(CblasColMajor, CblasNoTrans, CblasNoTrans, (MKL_INT)10000, (MKL_INT)10000, (MKL_INT)10000, 1.0, &a[0], (MKL_INT)10000, &b[0], (MKL_INT)10000, 0.0, &c[0], ...
CBLAS是BLAS(Basic Linear Algebra Subprograms)的C语言接口。 LAPACK提供了线性代数问题的解决方案,如线性方程组、特征值问题等。 性能优化,适用于大规模矩阵运算。 Eigen 主要是C++库,但提供了C接口。 支持高级矩阵和线性代数运算。 表达式模板技术,实现高效的编译时优化。 3. 安装和使用 GNU Scientific Library (...
BLAS库分为三级:一级包括向量操作,二级包括矩阵-向量操作,三级包括矩阵-矩阵操作。 #include <cblas.h> void matrix_multiply(const double *A, const double *B, double *C, int n) { cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans, n, n, n, 1.0, A, n, B, n, 0.0, C, n); } 2....
double* result_data = (double*)PyArray_DATA((PyArrayObject*)result_array); cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans, rows1, cols2, cols1,1.0, matrix1_data, cols1, matrix2_data, cols2,0.0, result_data, cols2); returnresult_array; } staticPyMethodDef MatrixMultiplyMethods[] ...
blas_dgemm(CblasNoTrans,CblasNoTrans,1.0,A,B,0.0,C);// C=1.0*A*B+0.0*Cgsl_blas_dsymm(CblasLeft,CblasUpper,1.0,A,B,0.0,C);// C=1.0*B*A+0.0*Cgsl_blas_dsymm(CblasRight,CblasUpper,1.0,A,B,0.0,C);//三角矩阵在左侧 上三角 不转置 不对角单位化 B=1.0*A*Bgsl_blas_dtrmm(Cblas...
本节的代码可在github.com/dev-cafe/cmake-cookbook/tree/v1.0/chapter-10/recipe-01找到,并包含一个 C++示例。本节适用于 CMake 版本 3.6(及更高版本),并在 GNU/Linux、macOS 和 Windows 上进行了测试。 在本节的第一节中,我们将介绍我们的小项目以及将在后续节中使用的一些基本概念。安装文件、库和可执...
cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans, M, N, K, alpha, A, K, B, N, beta, C, N); for (i = 0; i < 9; i++) { printf("%lf ", C[i]); } printf("\n"); return 0; } 1. 2. 3. 4. 5. 6.
"_cblas_dgemm", referenced from: lapack_gemm64f(double const*, unsigned long, double const*, unsigned long, double, double const*, unsigned long, double, double*, unsigned long, int, int, int, int) in libopencv_core.a(hal_internal.cpp.o) "_cblas_sgemm", referenced from: lapack_ge...
clblasSgemm(cblas_row_major, transA, transB, m, n, k, alpha, A.ocl_buf, ct.c_size_t(A_offset), lda, B.ocl_buf, ct.c_size_t(B_offset), ldb, beta, C.ocl_buf, ct.c_size_t(C_offset), ldc, ct.c_size_t(1), ct.byref(_queue), ct.c_size_t(num_wait), wait_for, ...
BLAS:dgemm, dgemm_, andDGEMM SeeExample "Calling a Complex BLAS Level 1 Function from C++"on how to call BLAS routines from C. See also the Intel® oneAPI Math Kernel Library (oneMKL) Developer Reference for a description of the C interface to LAPACK functio...