Document Type
Conference Proceeding
Publication Date
8-1-2012
Abstract
The scalability and efficiency of graph applications are significantly constrained by conventional systems and their supporting programming models. Technology trends such as multicore, manycore, and heterogeneous system architectures are introducing further challenges and possibilities for emerging application domains such as graph applications. This paper explores the parallel execution of graphs that are generated using the Barnes-Hut algorithm to exemplify dynamic workloads. The workloads are expressed using the semantics of an exascale computing execution model called ParalleX. For comparison, results using conventional execution model semantics are also presented. We find improved load balancing during runtime and automatic parallelism discovery by using the advanced semantics for exascale computing. © The Author(s) 2012.
Publication Source (Journal or Book title)
International Journal of High Performance Computing Applications
First Page
319
Last Page
332
Recommended Citation
Dekate, C., Anderson, M., Brodowicz, M., Kaiser, H., Adelstein-Lelbach, B., & Sterling, T. (2012). Improving the scalability of parallel N-body applications with an event-driven constraint-based execution model. International Journal of High Performance Computing Applications, 26 (3), 319-332. https://doi.org/10.1177/1094342012440585