Observation and analysis of the multicore performance impact on scientific applications
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Simon, Tyler A., and James McGalliard. “Observation and Analysis of the Multicore Performance Impact on Scientific Applications.” Concurrency and Computation: Practice and Experience 21, no. 17 (2009): 2213–31. https://doi.org/10.1002/cpe.1486.
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This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
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Abstract
With the proliferation of large multicore high-performance computing systems, application performance is often negatively affected. This paper provides benchmark results for a representative workload from the Department of Defense High-performance Computing Modernization Program. The tests were run on a Cray XT-3 and XT-4, which use dual- and quad-core AMD Opteron microprocessors. We use a combination of synthetic kernel and application benchmarks to examine the cache performance, MPI task placement strategies and compiler optimizations. Our benchmarks show performance behavior similar to that reported in other studies and sites. Dual- and quad-core tests show a run-time performance penalty compared with single-core runs on the same systems. We attribute this performance degradation to a combination of L1 to main memory contention and task placement within the application. Copyright © 2009 John Wiley & Sons, Ltd.