title: Streamline integration using MPI-hybrid parallelism on a large multicore architecture.
abstract: Streamline computation in a very large vector field data set represents a significant challenge due to the nonlocal and data-dependent nature of streamline integration. In this paper, we conduct a study of the performance characteristics of hybrid parallel programming and execution as applied to streamline integration on a large, multicore platform. With multicore processors now prevalent in clusters and supercomputers, there is a need to understand the impact of these hybrid systems in order to make the best implementation choice. We use two MPI-based distribution approaches based on established parallelization paradigms, parallelize over seeds and parallelize over blocks, and present a novel MPI-hybrid algorithm for each approach to compute streamlines. Our findings indicate that the work sharing between cores in the proposed MPI-hybrid parallel implementation results in much improved performance and consumes less communication and I/O bandwidth than a traditional, nonhybrid distributed implementation.
authors: Lawrence Berkeley National Laboratory, Berkeley and University of California, Davis, Davis, CA 95616, USA. dcamp@lbl.gov
authors: David
authors: D
authors: Camp
authors: Christoph
authors: C
authors: Garth
authors: Hank
authors: H
authors: Childs
authors: Dave
authors: D
authors: Pugmire
authors: Kenneth I
authors: KI
authors: Joy