Benchmark of vec class vs. valarray

benchmark.md

N (dimension)	vec runtime [s]	valarray runtime [s]
3	1.82	14.7
10	1.82	14.7
15	1.82	14.7
20	13.8	14.7
25	17.2	14.7
50	40.5	14.7
100	78.4	14.7

valarray_test.cpp

#include <iostream>
#include <valarray>

using namespace std;

inline double norm_sq(const valarray<double>& v) {
    return (v*v).sum();
}

int main(int argc, char *argv[]) {
    const size_t N = 3;
    const size_t M = 100000000;

    volatile double sum = 0.;
    for (size_t m = 0; m < M; ++m) {
        valarray<double> v(N, 1);
        valarray<double> w(N, 1);
        sum += norm_sq(v);
        sum += norm_sq(w);
        sum += norm_sq(v+w);
        sum += norm_sq(v-w);
        sum += (42. * v)[1];
    }

    return 0;
}

vec_test.cpp

#include <iostream>
#include <vec.hpp>

using namespace std;
using namespace Vec;

int main(int argc, char *argv[]) {
    const size_t N = 3;
    const size_t M = 100000000;

    volatile double sum = 0.;
    for (size_t m = 0; m < M; ++m) {
        vec<N,double> v(1.);
        vec<N,double> w(1.);
        sum += v.norm_sq();
        sum += w.norm_sq();
        sum += (v+w).norm_sq();
        sum += (v-w).norm_sq();
        sum += (42. * v)[1];
    }

    return 0;
}