I assume that if you are new to C++, you are also new to C and Fortran. In that case I would definitely suggest to you, not to start with BLAS/LAPACK, at least not without a nice C++ wrapper.
My suggestion would be to have a look at Eigen which offers a much easier start to matrix operations using native C++ code. You can have a look at their tutorial to get started. The Eigen performance is said to be comparable to that of BLAS/LAPACK. See e.g. their benchmark. However I didn't test that myself.
If you really want to go low level and use BLAS/LAPACK, have a look at the available functions of cBlas (the C
-Wrapper of BLAS) and LAPACK. Additionally, you can find some examples how to use Lapacke (The C
-Wrapper of LAPACK) here. But don't expect things to be nice and well documented!
To finally give an answer to your question: Here is a code snipped I wrote some time ago for benchmarking. The code creates two random matrices A
and B
and multiplies them into the matrix C
.
#include <random>
#include <cblas.h>
int main ( int argc, char* argv[] ) {
// Random numbers
std::mt19937_64 rnd;
std::uniform_real_distribution<double> doubleDist(0, 1);
// Create arrays that represent the matrices A,B,C
const int n = 20;
double* A = new double[n*n];
double* B = new double[n*n];
double* C = new double[n*n];
// Fill A and B with random numbers
for(uint i =0; i <n; i++){
for(uint j=0; j<n; j++){
A[i*n+j] = doubleDist(rnd);
B[i*n+j] = doubleDist(rnd);
}
}
// Calculate A*B=C
cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans, n, n, n, 1.0, A, n, B, n, 0.0, C, n);
// Clean up
delete[] A;
delete[] B;
delete[] C;
return 0;
}