# Weird OpenMP Reduction

Typical reductions in OpenMP* involve using a associative operator op to do local reductions, and then using a reduction clause to collect those local reductions.  For example, the following code computes a dot product by computing local sums on each thread and then summing them.

```
// Returns dot product of two vectors int dot( int x[], int y[], int n ) {
int sum = 0;
#pragma omp parallel for reduction(+:sum)
for( int i=0; i<n; ++i ) {
sum += x[i]*y[i];
}
return sum;
}

```
The reduction clause specifies two things:
1. When control enters the parallel region, each thread in the region gets a thread-private copy of sum, initialized to the identity element for +.
2. When control leaves the parallel region, the original sum is updated by combining its value with the final values of thethread-private copies, using +.  Since + is associative (or nearly so for floating-point), the final sum has the same value (or nearly so) as it would for serial execution of the code.
The reduction clause does not say specify anything more -- you are allowed to do anything with the thread-local copies of a reduction variable.  The code below demonstrates this point.  It computes the dot product of two integer vectors without using any addition operations inside the loop.  It assumes two's complement arithmetic.

```
// Returns dot product of two vectors
int dot( int x[], int y[], int n ) {
int c = 0;
int s = 0;
#pragma omp parallel for reduction(+:c,s)
for( int i=0; i<n; ++i ) {
int p = x[i]*y[i];
int q = c^p;
c &= p|s;
c |= p&s;
c <<= 1;
s ^= q;
}
return c+s;
}

```

Consider it a puzzle, not recommended practice.  If you need a hint for why it works correctly, look up the datasheet for the classic TTL 74183 chip.  [Last line edited 2015-4-1 because old link to 74183 datasheet broke.]

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