A communications simulation methodology for AMR codes using task dependency analysis

Authors:
Cy P. Chan;Joseph P. Kenny;Gilbert Hendry;Vincent E. Beckner;John B. Bell;John M. Shalf
Affiliations:
Lawrence Berkeley National Laboratory, Berkeley, CA;Sandia National Laboratory, Livermore, CA;Sandia National Laboratory, Livermore, CA;Lawrence Berkeley National Laboratory, Berkeley, CA;Lawrence Berkeley National Laboratory, Berkeley, CA;Lawrence Berkeley National Laboratory, Berkeley, CA
Venue:
IA^3 '13 Proceedings of the 3rd Workshop on Irregular Applications: Architectures and Algorithms
Year:
2013

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Abstract

The ability to predict the performance of irregular, asynchronous applications on future hardware is essential to the exascale co-design process. Adaptive Mesh Refinement (AMR) applications are inherently irregular and dynamic in their computation and communication patterns, resulting in complex hardware/software interactions. We have developed a methodology to use architectural simulators to assess the performance of different AMR data placement strategies on a selection of potential hardware interconnect topologies for exascale-class supercomputers. We use our framework to study the CASTRO AMR compressible astrophysics code for the simulation of supernovae. The results show a performance improvement of up to 18 percent may be obtained through the use of locality-aware data distributions for some network topologies on an exascale-class supercomputer.