Column-wise dot product in Eigen C++

Question

Is there an easy way to evaluate the column wise dot product of 2 matrices (lets call them A and B, of type Eigen::MatrixXd) that have

Answer 1

I did experiment based on @ggael's answer.

MatrixXd A = MatrixXd::Random(600000,30);
MatrixXd B = MatrixXd::Random(600000,30);

MatrixXd res;
clock_t start, end;
start = clock();
res.noalias() = (A * B.transpose()).diagonal();
end = clock();
cout << "Dur 1 : " << (end - start) / (double)CLOCKS_PER_SEC << endl;

MatrixXd res2;
start = clock();
res2 = (A.array() * B.array()).rowwise().sum();
end = clock();
cout << "Dur 2 : " << (end - start) / (double)CLOCKS_PER_SEC << endl;

MatrixXd res3;
start = clock();
res3 = (A.cwiseProduct(B)).rowwise().sum();
end = clock();
cout << "Dur 3 : " << (end - start) / (double)CLOCKS_PER_SEC << endl;

And the output is:

Dur 1 : 10.442
Dur 2 : 8.415
Dur 3 : 7.576

Seems that the diagonal() solution is the slowest one. The cwiseProduct one is the fastest. And the memory usage is the same.