Issue #

A variable is being incorrectly shared in the OpenMP datascoping clauses.

Relevance #

Specifying an invalid scope for a variable may introduce race conditions and produce incorrect results. For instance, when a variable is written from parallel threads and the specified scoping is shared instead of private.

Actions #

Change the data scope of the variable from shared to private.

Code example #

In the following code no variable is privatized:

void example(int **result, unsigned rows, unsigned cols) {
 int i, j;
 
 // j is implicitly shared and it should be private!
#pragma omp parallel for shared(result)
 for (i = 0; i < rows; i++) {
   for (j = 0; j < cols; j++) {
     result[i][j] = 0;
   }
 }
}

This introduced a data race due to j being shared among threads. It should be privatized:

void example(int **result, unsigned rows, unsigned cols) {
 int i, j;
 
 // j is implicitly shared and it should be private!
#pragma omp parallel for shared(result) private(j)
 for (i = 0; i < rows; i++) {
   for (j = 0; j < cols; j++) {
     result[i][j] = 0;
   }
 }
}

Related resources #

• PWD010 examples at GitHub

References #

• Data-Sharing Attribute Clauses – OPENMP API Specification: Version 5.0 November 2018  [last checked August 2021]