When Julia is faster than C

On e-day, I came across this cool tweet from Fermat’s library

So I spend a few minutes coding this into Julia

function euler(n)
    m=0
    for i=1:n
        the_sum=0.0
        while true
            m+=1
            the_sum+=rand()
            (the_sum>1.0) && break;
        end
    end
    m/n
end

Timing this on my machine, I got

julia> @time euler(1000000000)
 15.959913 seconds (5 allocations: 176 bytes)
2.718219862

Gave a little under 16 seconds.

Tried a c implementation

#include <stdio.h>      /* printf, NULL */
#include <stdlib.h>     /* srand, rand */
#include <time.h>       /* time */
 
double r2()
{
    return (double)rand() / (double)((unsigned)RAND_MAX + 1);
}
 
double euler(long int n)
{
    long int m=0;
    long int i;
    for(i=0; i<n; i++){
        double the_sum=0;
        while(1) {
            m++;
            the_sum+=r2();
            if(the_sum>1.0) break;
        }
    }
    return (double)m/(double)n;
}
 
 
int main ()
{
  printf ("Euler : %2.5f\n", euler(1000000000));
 
  return 0;
}

and compiling with either gcc

gcc  -Ofast euler.c

or clang

clang  -Ofast euler.c

gave a timing twice as long

$ time ./a.out 
Euler : 2.71829
 
real    0m36.213s
user    0m36.238s
sys 0m0.004s

For the curios, I am using this version of Julia

julia> versioninfo()
Julia Version 0.6.3-pre.0
Commit 93168a6 (2017-12-18 07:11 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: Intel(R) Core(TM) i7-4770HQ CPU @ 2.20GHz
  WORD_SIZE: 64
  BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell)
  LAPACK: libopenblas64_
  LIBM: libopenlibm
  LLVM: libLLVM-3.9.1 (ORCJIT, haswell)

Now one should not put too much emphasis on such micro benchmarks. However, I found this a very curious examples when a high level language like Julia could be twice as fast a c. The Julia language authors must be doing some amazing mojo.

3 thoughts on “When Julia is faster than C

  1. Pingback: When Julia is faster than C, digging deeper | Perfectionatic's blog

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