segmentation fault when using omp parallel for, but not sequentially

MutantTurkey picture MutantTurkey · Apr 29, 2013 · Viewed 7.8k times · Source

I'm having trouble using the #pragma omp parallel for

Basically I have several hundred DNA sequences that I want to run against an algorithm called NNLS.

I figured that doing it in parallel would give me a pretty good speed up, so I applied the #pragma operators.

When I run it sequentially there is no issue, the results are fine, but when I run it with #pragma omp parallel for I get a segfault within the algorithm (sometimes at different points).

#pragma omp parallel for
for(int i = 0; i < dir_count; i++ ) {

  int z = 0;
  int w = 0;
  struct dirent *directory_entry;
  char filename[256];

  directory_entry = readdir(input_directory_dh);

  if(strcmp(directory_entry->d_name, "..") == 0 || strcmp(directory_entry->d_name, ".") == 0) {
    continue;
  }

  sprintf(filename, "%s/%s", input_fasta_directory, directory_entry->d_name);

  double *count_matrix = load_count_matrix(filename, width, kmer);

  //normalize_matrix(count_matrix, 1, width)
  for(z = 0; z < width; z++) 
    count_matrix[z] = count_matrix[z] * lambda;

  // output our matricies if we are in debug mode
  printf("running NNLS on %s, %d, %d\n", filename, i, z);
  double *trained_matrix_copy = malloc(sizeof(double) * sequences * width);
  for(w = 0; w < sequences; w++) {
    for(z = 0; z < width; z++) {
      trained_matrix_copy[w*width + z] = trained_matrix[w*width + z];
    }
  } 

  double *solution = nnls(trained_matrix_copy, count_matrix, sequences, width, i);


  normalize_matrix(solution, 1, sequences);
  for(z = 0; z < sequences; z++ )  {
    solutions(i, z) = solution[z]; 
  }

  printf("finished NNLS on %s\n", filename);

  free(solution);
  free(trained_matrix_copy);
}

gdb always exits at a different pint in my thread, so I can't figure out what is going wrong.

What I have tried:

  • allocating a copy of each matrix, so that they would not be writing on top of eachother
  • using a mixture of private/shared operators for the #pragma piece
  • using different input sequences
  • writing out my trained_matrix and count_matrix prior to calling NNLS, ensuring that they look OK. (they do!)

I'm sort of out of ideas. Does anyone have some advice?

Answer

MutantTurkey picture MutantTurkey · May 1, 2013

Solution: make sure not use static variables in your function when multithreading (damned f2c translator)