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Communication Dans Un Congrès Année : 2019

Distributed and Parallel Programming Paradigms on the K computer and a Cluster

Résumé

In this paper, we focus on a distributed and parallel programming paradigm for massively multi-core supercomputers. We introduce YML, a development and execution environment for parallel and distributed applications based on a graph of task components scheduled at runtime and optimized for several middlewares. Then we show why YML may be well adapted to applications running on a lot of cores. The tasks are developed with the PGAS language XMP based on directives. We use YML/XMP to implement the block-wise Gaussian elimination to solve linear systems. We also implemented it with XMP and MPI without blocks. ScaLAPACK was also used to created an non-block implementation of the resolution of a dense linear system through LU factorization. Furthermore, we run it with different amount of blocks and number of processes per task. We find out that a good compromise between the number of blocks and the number of processes per task gives interesting results. YM-L/XMP obtains results faster than XMP on the K computer and close to XMP, MPI and ScaLAPACK on clusters of CPUs. We conclude that parallel and distributed multi-level programming paradigms like YML/XMP may be interesting solutions for extreme scale computing .
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Dates et versions

hal-02050930 , version 1 (26-03-2019)

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Jérôme Gurhem, Miwako Tsuji, Serge Petiton, Mitsuhisa Sato. Distributed and Parallel Programming Paradigms on the K computer and a Cluster. HPCAsia 2019 International Conference on High Performance Computing in Asia-Pacific Region, Jan 2019, Guangzhou, China. pp.9-17, ⟨10.1145/3293320.3293330⟩. ⟨hal-02050930⟩
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