CODEWITHSUNDEEP
copenmp
nick
nick

Reputation: 121

how to avoid overhead of openMP in nested loops

I have two versions of code that produce equivalent results where I am trying to parallelize only the inner loop of a nested for loop. I am not getting much speedup but I didn't expect a 1-to-1 since I'm trying only to parallelize the inner loop.

My main question is why these two versions have similar runtimes? Doesn't the second version fork threads only once and avoid the overhead of starting new threads on every iteration over i as in the first version?

The first version of code starts up threads on every iteration of the outer loop like this:

for(i=0; i<2000000; i++){
  sum = 0;
  #pragma omp parallel for private(j) reduction(+:sum)
  for(j=0; j<1000; j++){
    sum += 1;
  }
  final += sum;
}
printf("final=%d\n",final/2000000);

With this output and runtime:

OMP_NUM_THREADS=1

final=1000
real    0m5.847s
user    0m5.628s
sys     0m0.212s

OMP_NUM_THREADS=4

final=1000
real    0m4.017s
user    0m15.612s
sys     0m0.336s

The second version of code starts threads once(?) before the outer loop and parallelizes the inner loop like this:

#pragma omp parallel private(i,j)
for(i=0; i<2000000; i++){
  sum = 0;
  #pragma omp barrier
  #pragma omp for reduction(+:sum)
  for(j=0; j<1000; j++){
    sum += 1;
  }
  #pragma omp single
  final += sum;
}
printf("final=%d\n",final/2000000);

With this output and runtime:

OMP_NUM_THREADS=1

final=1000
real    0m5.476s
user    0m4.964s
sys     0m0.504s

OMP_NUM_THREADS=4

final=1000
real    0m4.347s
user    0m15.984s
sys     0m1.204s

Why isn't the second version much faster than the first? Doesn't it avoid the overhead of starting threads on every loop iteration or am I doing something wrong?

Upvotes: 11

Views: 1474

Answers (2)

Dellowar
Dellowar

Reputation: 3352

You appear to be retracing the steps of Amdahl's Law: It speaks of parallel process vs it's own overhead. One thing that Amadhl found was regardless of how much parallelism you put into a program, it will always have to same speedup to begin with. Parallelism only starts to improve run time/performance when the program requires enough work to compensate the extra processing power.

Upvotes: 0

Josh Milthorpe
Josh Milthorpe

Reputation: 1038

An OpenMP implementation may use thread pooling to eliminate the overhead of starting threads on encountering a parallel construct. A pool of OMP_NUM_THREADS threads is started for the first parallel construct, and after the construct is completed the slave threads are returned to the pool. These idle threads can be reallocated when a later parallel construct is encountered.

See for example this explanation of thread pooling in the Sun Studio OpenMP implementation.

Upvotes: 1

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