Abstract
In this paper, we present techniques for translating and optimizing realistic OpenMP applications on distributed systems. The goal of our project is to quantify the degree to which OpenMP can be extended to distributed systems and to develop supporting compiler techniques. Our present compiler techniques translate OpenMP programs into a form suitable for execution on a Software DSM system. We have implemented a compiler that performs this basic translation, and we have proposed optimization techniques that improve the baseline performance of OpenMP applications on distributed computer systems. Our results show that, while kernel benchmarks can show high efficiency for OpenMP programs on distributed systems, full applications need careful consideration of shared data access patterns. A naive translation (similar to the basic translation done by OpenMP compilers for SMPs) leads to acceptable performance in very few applications. We propose optimizations such as computation repartitioning, page-aware optimizations, and access privatization that result in average 70% performance improvement on the SPEC OMPM2001 benchmark applications.
This material is based upon work supported in part by the National Science Foundation under Grant No. 9703180, 9975275, 9986020, and 9974976. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Min, S.J., Basumallik, A., Eigenmann, R. (2003). Supporting Realistic OpenMP Applications on a Commodity Cluster of Workstations. In: Voss, M.J. (eds) OpenMP Shared Memory Parallel Programming. WOMPAT 2003. Lecture Notes in Computer Science, vol 2716. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45009-2_14
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DOI: https://doi.org/10.1007/3-540-45009-2_14
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