scalar.d

/**
 * Demo: scalar.d
 * Purpose: Slightly modified source from question on [Stack Overflow](http://stackoverflow.com/questions/5142366/how-fast-is-d-compared-to-c)
 *     Original code posted wasn't portable because of dynamic array length type (ulong on Linux, uint on Windows from testing)
 *     Replaced platform-dependent types (array.length) with typeof and auto statements.
 *
 *     Source was compiled with `rdmd --compiler=ldc2 -O3 -boundscheck=off  scalar.d`.
 * Authors: @lars, Erich Gubler (@erichdongubler)
 * Date: 3/30/2015
 */
import std.stdio;
import std.datetime;
import std.random;

const long N = 20000;
const int size = 10;

alias int value_type;
alias long result_type;
alias value_type[] vector_t;
alias typeof(vector_t.init.length) size_type;// Changed this to make portable - Linux is ulong, Win8.1 is uint

value_type scalar_product(const ref vector_t x, const ref vector_t y) {
  value_type res = 0;
  size_type siz = x.length;
  for (size_type i = 0; i < siz; ++i)
    res += x[i] * y[i];
  return res;
}

int main() {
  auto tm_before = Clock.currTime();

  // 1. allocate and fill randomly many short vectors
  vector_t[] xs;
  xs.length = N;
  for (int i = 0; i < N; ++i) {
    xs[i].length = size;
  }
  writefln("allocation: %s ", (Clock.currTime() - tm_before));
  tm_before = Clock.currTime();

  for (int i = 0; i < N; ++i)
    for (int j = 0; j < size; ++j)
      xs[i][j] = uniform(-1000, 1000);
  writefln("random: %s ", (Clock.currTime() - tm_before));
  tm_before = Clock.currTime();

  // 2. compute all pairwise scalar products:
  result_type avg = cast(result_type) 0;
  for (int i = 0; i < N; ++i)
    for (int j = 0; j < N; ++j)
      avg += scalar_product(xs[i], xs[j]);
  avg = avg / N*N;
  writefln("result: %d", avg);
  auto time = Clock.currTime() - tm_before;
  writefln("scalar products: %s ", time);

  return 0;
}