A static cut-off for task parallel programs

Abstract

Task parallel models supporting dynamic and hierarchical parallelism are believed to offer a promising direction to achieving higher performance and programmability. Divide-and-conquer is the most frequently used idiom in task parallel models, which decomposes the problem instance into smaller ones until they become “trivial” to solve. However, it incurs a high tasking overhead if a task is created for each subproblem. In order to reduce this overhead, a “cut-off” is commonly used, which eliminates task creations where they are unlikely to be beneficial. The manual cut-off typically enlarges leaf tasks by stopping task creations when a subproblem becomes smaller than a threshold, and possibly transforms the enlarged leaf tasks into specialized versions for solving small instances (e.g., use loops instead of recursive calls); it duplicates the coding work and hinders productivity.