#include <iostream> #include <fstream> #include <vector> #include <Eigen/Core> #include "../../BenchTimer.h" using namespace Eigen; #ifndef SCALAR #error SCALAR must be defined #endif typedef SCALAR Scalar; template<typename MatA, typename MatB, typename MatC> EIGEN_DONT_INLINE void lazy_gemm(const MatA &A, const MatB &B, MatC &C) { // escape((void*)A.data()); // escape((void*)B.data()); C.noalias() += A.lazyProduct(B); // escape((void*)C.data()); } template<int m, int n, int k, int TA> EIGEN_DONT_INLINE double bench() { typedef Matrix<Scalar,m,k,TA> MatA; typedef Matrix<Scalar,k,n> MatB; typedef Matrix<Scalar,m,n> MatC; MatA A(m,k); MatB B(k,n); MatC C(m,n); A.setRandom(); B.setRandom(); C.setZero(); BenchTimer t; double up = 1e7*4/sizeof(Scalar); double tm0 = 10, tm1 = 20; double flops = 2. * m * n * k; long rep = std::max(10., std::min(10000., up/flops) ); long tries = std::max(tm0, std::min(tm1, up/flops) ); BENCH(t, tries, rep, lazy_gemm(A,B,C)); return 1e-9 * rep * flops / t.best(); } template<int m, int n, int k> double bench_t(int t) { if(t) return bench<m,n,k,RowMajor>(); else return bench<m,n,k,0>(); } EIGEN_DONT_INLINE double bench_mnk(int m, int n, int k, int t) { int id = m*10000 + n*100 + k; switch(id) { case 10101 : return bench_t< 1, 1, 1>(t); break; case 20202 : return bench_t< 2, 2, 2>(t); break; case 30303 : return bench_t< 3, 3, 3>(t); break; case 40404 : return bench_t< 4, 4, 4>(t); break; case 50505 : return bench_t< 5, 5, 5>(t); break; case 60606 : return bench_t< 6, 6, 6>(t); break; case 70707 : return bench_t< 7, 7, 7>(t); break; case 80808 : return bench_t< 8, 8, 8>(t); break; case 90909 : return bench_t< 9, 9, 9>(t); break; case 101010 : return bench_t<10,10,10>(t); break; case 111111 : return bench_t<11,11,11>(t); break; case 121212 : return bench_t<12,12,12>(t); break; } return 0; } int main(int argc, char **argv) { std::vector<double> results; std::ifstream settings("lazy_gemm_settings.txt"); long m, n, k, t; while(settings >> m >> n >> k >> t) { //std::cerr << " Testing " << m << " " << n << " " << k << std::endl; results.push_back( bench_mnk(m, n, k, t) ); } std::cout << RowVectorXd::Map(results.data(), results.size()); return 0; }