Download e-book for iPad: Beyond Loop Level Parallelism in OpenMP: Accelerators, by Patrick Carribault, Marc Pérache, Hervé Jourdren (auth.),

By Patrick Carribault, Marc Pérache, Hervé Jourdren (auth.), Mitsuhisa Sato, Toshihiro Hanawa, Matthias S. Müller, Barbara M. Chapman, Bronis R. de Supinski (eds.)

This ebook constitutes the refereed complaints of the sixth overseas Workshop on OpenMP, IWOMP 2010, held in Tsukuba urban, Japan, in June 2010. The papers are geared up in topical sections on Runtime and Optimization, Proposed Extensions to OpenMP, Scheduling and function, in addition to Hybrid Programming and Accelerators with OpenMP.

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Extra info for Beyond Loop Level Parallelism in OpenMP: Accelerators, Tasking and More: 6th Internationan Workshop on OpenMP, IWOMP 2010, Tsukuba, Japan, June 14-16, 2010 Proceedings

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0 of the for loop (lines 18–22). After executing the loop, each thread stores its partial results in the temporary arrays (line 23 and 24). After the parallel region, the master thread iterates over all partial results in the temporary arrays and produces the final result of the computation (lines 26–29). Although this implementation performs well for small thread counts, larger thread counts might benefit from a tree-based reduction. Tree-based reductions are significantly more complicated and require a much higher coding effort.

IWOMP 2007. LNCS, vol. 4935, pp. 161–172. Springer, Heidelberg (2008) 11. : Extending the OpenMP Standard for Thread Mapping and Grouping. , Voss, M. ) IWOMP 2005 and IWOMP 2006. LNCS, vol. 4315, pp. 435–446. Springer, Heidelberg (2008) A Proposal for User-Defined Reductions in OpenMP Alejandro Duran1, Roger Ferrer1 , Michael Klemm2 , Bronis R. gov 4 Universitat Polit`ecnica de Catalunya Abstract. Reductions are commonly used in parallel programs to produce a global result from partial results computed in parallel.

2 Nested EPCC Syncbench Benchmark The second kernel benchmark is a modification of the syncbench benchmark from the EPCC microbenchmarks [2]. It measures the overhead of OpenMP synchronisation constructs. We want to investigate the overhead of nested OpenMP constructs, so we modify the benchmark in the same way we modify the stream benchmark. Our benchmark opens a parallel region and starts the EPCC syncbench for each of the inner teams. Our assumption is that synchronization is more efficient when the inner teams run close together.

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