Hi,
I found random access to large matrix is slower in Eigen than std vector. Testing code is listed below. It's compiled with -O3 flag. Could I make Eigen run faster? Thank you.

Xiaoqing

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#include <iostream>
#include <vector>
#include <Eigen/Dense>
#include <time.h>
using namespace std;

int main()
{
Eigen::MatrixXf A = Eigen::MatrixXf::Random(100000,100);
vector<vector<float> > B(100000,vector<float>(100));

for(int i = 0; i < 100000; ++i) for (int j = 0; j < 100; ++j) B[i][j] = A(i,j);

float r = 0;
clock_t t1,t2;

t1 = clock();
r = 0.0;
for(int i = 0; i < 100000; ++i) {
int m = rand()%100000;
float f = 0;
for (int j = 0; j < 100; j++) f += B[m][j];
r += f;
}
t2 = clock();
cout<<"vector: "<<(double)(t2-t1)/CLOCKS_PER_SEC<<endl;
cout<<r<<endl;

t1 = clock();
r = 0.0;
for(int i = 0; i < 100000; ++i) {
int m = rand()%100000;
float f = A.row(m).sum();
r += f;
}
t2 = clock();
cout<<"eigen: "<<(double)(t2-t1)/CLOCKS_PER_SEC<<endl;
cout<<r<<endl;

return 0;
}

Note that MatrixXf is column major whereas your std::vector version is row-major. So to make a fair comparison, use:

typedef Matrix<float,Dynamic,Dynamic,RowMajor> RowMajMatrixXf;