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 /**
  * 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;
 }