I am dealing with a large confusing codebase, and I have a situation like this.
#pragma omp parallel for
for ( int i = 0; i < N; i++) {
problemFunction();
}
void problemFunction() {
static bool inFunction;
if ( inFunction == true ) {
return;
}
else {
inFunction = true;
}
}
Would this create a race condition?
Unlike automatic local variables that usually reside on the thread's stack (which is private), local variables with static storage class reside in the data segment of the process and are thus shared between all threads executing the given function, therefore your code contains a race condition. To prevent the sharing, you should use OpenMP's threadprivate construct:
void problemFunction() {
static bool inFunction;
#pragma omp threadprivate(inFunction)
if ( inFunction == true ) {
return;
}
else {
inFunction = true;
}
}
This will alter the place the variable is stored in from the data segment to the so-called Thread-Local Storage (TLS). The original static semantics are kept, i.e. the value is retained between the function calls, but now each thread has its own copy. The threadprivate construct should always come after the variable declaration.
Yes, this will cause a race at execution (obviously). To avoid, you can use thread_local (see also here) variable (also, your function seems unnecessary complicated):
void problemFunction() {
static thread_local bool inFunction;
inFunction = true;
}
when each thread has their own variable inFunction. This way your function works with any threading implementation, not just OpenMP.
static variables and (2) uses multi-threading knows enough about these topics to understand that and why this will be a data race. Perhaps I anticipated that you have read (& understood) some basic text on concurrency. I would recommend doing so before starting to code and/or asking on SO.
[openmp]. Why are you then proposing a solution that uses a language keyword instead of the OpenMP construct? There is no guarantee whatsoever that the OpenMP runtime will interoperate with the compiler's implementation of thread-local variables. Besides, thread_local is a C++11 keyword.thread_local worked for me in a similar situation. C++11 is an (almost) 7 years old standard and widely considered the least to expect these days (and implied by the SO tag C++).