I have a small piece of code that I would like to parallelize as I upscale. I've been using cilk_for
from Cilk Plus to run the multithreading. The trouble is that I get a different result depending on the number of workers.
I've read that this might be due to a race condition, but I'm not sure what specifically about the code causes that or how to ameliorate it. Also, I realize that long
and __float128
are overkill for this problem, but might be necessary in the upscaling.
Code:
#include <assert.h>
#include "cilk/cilk.h"
#include <cstring>
#include <iostream>
#include <math.h>
#include <stdio.h>
#include <string>
#include <vector>
using namespace std;
__float128 direct(const vector<double>& Rpct, const vector<unsigned>& values, double Rbase, double toWin) {
unsigned count = Rpct.size();
__float128 sumProb = 0.0;
__float128 rProb = 0.0;
long nCombo = static_cast<long>(pow(2, count));
// for (long j = 0; j < nCombo; ++j) { //over every combination
cilk_for (long j = 0; j < nCombo; ++j) { //over every combination
vector<unsigned> binary;
__float128 prob = 1.0;
unsigned point = Rbase;
for (unsigned i = 0; i < count; ++i) { //over all the individual events
long exp = static_cast<long>(pow(2, count-i-1));
bool odd = (j/exp) % 2;
if (odd) {
binary.push_back(1);
point += values[i];
prob *= static_cast<__float128>(Rpct[i]);
} else {
binary.push_back(0);
prob *= static_cast<__float128>(1.0 - Rpct[i]);
}
}
sumProb += prob;
if (point >= toWin) rProb += prob;
assert(sumProb >= rProb);
}
//print sumProb
cout << " sumProb = " << (double)sumProb << endl;
assert( fabs(1.0 - sumProb) < 0.01);
return rProb;
}
int main(int argc, char *argv[]) {
vector<double> Rpct;
vector<unsigned> value;
value.assign(20,1);
Rpct.assign(20,0.25);
unsigned Rbase = 22;
unsigned win = 30;
__float128 rProb = direct(Rpct, value, Rbase, win);
cout << (double)rProb << endl;
return 0;
}
Sample output for export CILK_NWORKERS=1 && ./code.exe
:
sumProb = 1
0.101812
Sample output for export CILK_NWORKERS=4 && ./code.exe
:
sumProb = 0.948159
Assertion failed: (fabs(1.0 - sumProb) < 0.01), function direct, file code.c, line 61.
Abort trap: 6