Locality-aware Connection Management and Rank Assignment forWide-area MPI

  • Authors:
  • Hideo Saito;Kenjiro Taura

  • Affiliations:
  • University of Tokyo;University of Tokyo

  • Venue:
  • CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
  • Year:
  • 2007

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Abstract

We propose a connection management scheme that limits the number of inter-cluster connections and forwards messages for processes that cannot communicate directly. We also propose a rank assignment scheme that finds rankprocess mappings with low communication overhead by solving the Quadratic Assignment Problem. Our proposed methods perform locality-aware communication optimizations, and do so without tedious manual configuration by obtaining latency and traffic information from a short profiling run of the environment and the application. Using these methods, we implemented a wide-area-enabled MPI library called MC-MPI, and evaluated its performance by running the NAS Parallel Benchmarks on 256 real nodes distributed across 4 clusters. MC-MPI was able to limit the number of process pairs that established connections to just 10% without suffering a performance penalty. Moreover, MC-MPI was able to find rank assignments that resulted in up to 160% better performance than locality-unaware assignments.