Abstract
The paper proposes an approach for efficient and flexible parallelization of divide-and-conquer computations using the modern Intel Xeon Phi accelerators. Many real-life problems follow the divide-and-conquer paradigm and consequently generate either balanced or imbalanced trees. The paper proposes an OpenMP multi-threaded implementation of a general framework that requires coding basic divide-and-conquer constructs such as data partitioning, computations and result integration. Mapping computations onto threads is handled by the underlying runtime layer. The paper presents performance results for a parallel adaptive quadrature integration resulting in an irregular and imbalanced tree. It is shown that speed-ups obtained reach around 90 for parallelization of an irregular adaptive integration code compared to maximum speed-ups of 98 for code without thread management at various levels of the divide-and-conquer tree. Results for various thread affinities are shown. The framework, for which the source code is presented, can be easily reused for any other divide-and-conquer application.
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Acknowledgments
The work was supported by Intel within grant “Intel Phi Parallel Processing Lab”. The author wishes to thank Intel, especially Marek Zmuda, Marek Piosik and Robert Bard from Intel for provision of Xeon Phi equipment, literature and needed support.
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Czarnul, P. (2016). Parallelization of Divide-and-Conquer Applications on Intel Xeon Phi with an OpenMP Based Framework. In: Świątek, J., Borzemski, L., Grzech, A., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems Architecture and Technology – ISAT 2015 – Part III. Advances in Intelligent Systems and Computing, vol 431. Springer, Cham. https://doi.org/10.1007/978-3-319-28564-1_9
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