cpp, mkl 加速 eigen 实例
安装mklhttps://software.intel.com/en-us/get-started-with-mkl-for-linux把eigen放到代码文件平行目录使用mkl编译:mkl_test.cpp#define EIGEN_USE_MKL_ALL#include <iostream>#include <Eigen/Core>#in
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安装mkl
https://software.intel.com/en-us/get-started-with-mkl-for-linux
把eigen放到代码文件平行目录
使用mkl编译:
mkl_test.cpp
#define EIGEN_USE_MKL_ALL
#include <iostream>
#include <Eigen/Core>
#include <Eigen/Dense>
#include <time.h>
using namespace std;
using namespace Eigen;
// 使用Eigen+Intel MKL
int main(int argc, char *argv[])
{
MatrixXd a = MatrixXd::Random(1000, 1000); // 随机初始化矩阵
MatrixXd b = MatrixXd::Random(1000, 1000);
double start = clock();
MatrixXd c = a * b; // 乘法好简洁
double endd = clock();
double thisTime = (double)(endd - start) / CLOCKS_PER_SEC;
cout << thisTime << endl;
//system("PAUSE");
return 0;
}
编译指令:
g++ mkl_test.cpp /home/tong.guo/intel/mkl/lib/intel64/libmkl_rt.so -Ieigen -Wl,–no-as-needed -lpthread -lm -ldl -m64 -I/home/tong.guo/intel/mkl/include
然后运行./a.out
打印 0.23
对比不编译mkl:
mkl_test2.cpp
#include <iostream>
#include <Eigen/Core>
#include <Eigen/Dense>
#include <time.h>
using namespace std;
using namespace Eigen;
int main(int argc, char *argv[])
{
MatrixXd a = MatrixXd::Random(1000, 1000); // 随机初始化矩阵
MatrixXd b = MatrixXd::Random(1000, 1000);
double start = clock();
MatrixXd c = a * b; // 乘法好简洁
double endd = clock();
double thisTime = (double)(endd - start) / CLOCKS_PER_SEC;
cout << thisTime << endl;
//system("PAUSE");
return 0;
}
编译指令:g++ mkl_test2.cpp -o b.out -Ieigen
运行./b.out
打印11.94
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