Abstract
In the prospect of the upcoming exa-scale era with millions of execution units, the question of how to deal with this level of parallelism efficiently is of time-critical relevance. State-of-the-Art parallelization techniques such as OpenMP and MPI are not guaranteed to solve the expected problems of starvation, growing latencies, overheads, and contention. On the other hand, new parallelization paradigms promise to efficiently hide latencies and contain starvation and contention. In this paper we analyze the performance of one novel parallelization strategy for shared and distributed memory machines. We will focus on shared memory architectures and compare the performance of the ParalleX execution model against the quasi-standard OpenMP for a standard stencil-based problem. We compare in detail the OpenMP implementation of two applications of Jacobi solvers (one based on regular grid and one based on an irregular grid structure) with the corresponding implementation of these applications using HPX (High Performance ParalleX), the first feature-complete, open-source implementation of ParalleX, and analyze the results of both implementations on a multi-socket NUMA node.
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