Selection of Parallel Runtime Systems for Tasking Models

The ubiquity of multi- and many-core processors means that many general purpose programmers are beginning to face the difficult task of using runtime systems designed for large-scale parallelism. Not only do they have to deal with finding and exploiting irregular parallelism through Tasking, but they have to deal with runtime systems that require an expert tuning of task granularity and scheduling for performance. This paper provides hands-on experiences to help programmers to select an appropriate tasking model and design programs. It investigates the scheduling strategies of three different runtime tasking models: Cilk, OpenMP and High Performance ParalleX (HPX-5). Six different simple benchmarks are used to expose how well each runtime performs when provided untuned implementations of irregular code fragments. The benchmarks, which have irregular and dynamic structures, provide information about the pros and cons of each system's runtime model, particularly the differences to the programmer between help-first and work-first scheduling.