Abstract
In contrast to the common belief that OpenMP requires data-parallel extensions to scale well on architectures with non-uniform memory access latency, recent work has shown that it is possible to develop OpenMP programs with good levels of memory access locality, without any extension of the OpenMP API. The vehicle for localizing memory accesses transparently to the programming model, is a runtime memory manager, which uses memory access tracing and dynamic page migration to implement automatic data distribution. This paper evaluates the effectiveness of using this runtime data distribution method in non embarrassingly parallel codes, such as the SPEC benchmarks. We investigate the extent up to which sophisticated management of physical memory in the runtime system can speedup programs for which the programmer has no knowledge of the memory access pattern. Our runtime memory management algorithms improve the speedup of five SPEC benchmarks by 20–25% on average. The speedups are close to the theoretical maximum speedups for the problem sizes used and they are obtained with a minimal programming effort of about a couple of hours per benchmark.
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Nikolopoulos, D.S., Ayguadé, E. (2001). A Study of Implicit Data Distribution Methods for OpenMP Using the SPEC Benchmarks. In: Eigenmann, R., Voss, M.J. (eds) OpenMP Shared Memory Parallel Programming. WOMPAT 2001. Lecture Notes in Computer Science, vol 2104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44587-0_11
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DOI: https://doi.org/10.1007/3-540-44587-0_11
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