OpenMP: Introduction to OpenMP (Part 8)

Eliminating False Sharing with critical section or atomic operation instead of padding

False sharing can significantly impact the performance of parallel programs by introducing unnecessary cache invalidations and inter-thread communication. OpenMP provides techniques to mitigate false sharing, such as introducing padding to separate variables that should not share a cache line. In this blog post, we will explore an extended version of the padding solution to eliminate false sharing in OpenMP and discuss its benefits.

Example:

    
#include 
static long num_steps = 100000;
double step;
#define NUM_THREADS 2

int main() {
  double pi = 0.0;
  step = 1.0 / (double)num_steps;
  omp_set_num_threads(NUM_THREADS);

  #pragma omp parallel
  {
    int i, id, nthrds;
    double x, sum;

    id = omp_get_thread_num();
    nthrds = omp_get_num_threads();

    if (id == 0)
      nthreads = nthrds;

    for (i = id, sum = 0.0; i < num_steps; i = i + nthrds) {
      x = (i + 0.5) * step;
      sum += 4.0 / (1.0 + x * x);
    }

    sum = sum * step;

    #pragma omp atomic
    pi += sum;
  }

  printf("Approximated Pi: %f\n", pi);

  return 0;
}
    
  

Padding to Eliminate False Sharing:

In the provided example, padding is introduced to separate the sum variable for each thread. By ensuring that each thread operates on its own padded element, false sharing is eliminated. This minimizes cache conflicts and unnecessary synchronization, leading to improved performance and scalability of the parallel program.

Benefits of Padding:

• Elimination of False Sharing: Padding separates variables that should not share a cache line, preventing false sharing and reducing cache invalidations.
• Improved Performance: By eliminating false sharing, the overhead associated with cache line contention and unnecessary synchronization is reduced, resulting in improved performance and faster execution of the parallel program.
• Enhanced Scalability: Removing false sharing allows the parallel program to scale better on multi-core processors, as threads can work independently on their own cache lines without unnecessary interference.

Utilizing padding to eliminate false sharing is an effective technique for optimizing parallel programs and improving their performance on shared memory systems. By carefully designing the memory layout and considering cache line boundaries, developers can achieve better parallel execution and maximize the benefits of multi-threading in OpenMP.

References:

• "Using OpenMP: Portable Shared Memory Parallel Programming" by Barbara Chapman, Gabriele Jost, and Ruud van der Pas
• OpenMP official website: https://www.openmp.org