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首页> 外文期刊>Computers and Electrical Engineering >Manycore challenge in particle-in-cell simulation: How to exploit 1 TFlops peak performance for simulation codes with irregular computation
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Manycore challenge in particle-in-cell simulation: How to exploit 1 TFlops peak performance for simulation codes with irregular computation

机译:单元格粒子模拟中的Manycore挑战:如何利用不规则计算的1 TFlops峰值性能来模拟代码

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This paper discusses the challenge in post-Peta and Exascale era especially that brought by manycore processors of ordinary (i.e., non-GPU type) CPU cores. Though such a processor like Intel Xeon Phi gives us TFlops-class computational power and may lead us to Exascale computing, full exploitation of its potential is far from an easy job due to its source of high performance, namely a large scale multithreading and a wide SIMD mechanism. In fact, in the three-tier parallelism namely inter-node, intra-node and intra-core ones, we found their order does not represent the toughness in HPC programming but the order should be reversed to do that. Our case study with a particle-in-cell plasma simulation code supports our observation revealing that a simple porting of an existing code to Xeon Phi is infeasible from the viewpoint of performance and we have to make a significant change of the code structure so that it conforms with the features of the processor. However the study also confirms that the recoding effort is well rewarded achieving a good single-node performance higher than that obtained from an execution on four dual-socket nodes of Cray XE6. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文讨论了后Peta和Exascale时代的挑战,特别是普通(即非GPU类型)CPU内核的许多内核处理器带来的挑战。尽管像Intel Xeon Phi这样的处理器为我们提供了TFlops级的计算能力,并可能使我们进入Exascale计算,但是由于其高性能的来源,即大规模多线程和广泛的应用,充分利用其潜力并非易事。 SIMD机制。实际上,在三层并行性中,即节点间,节点内和内核内并行性,我们发现它们的顺序并不代表HPC编程的难度,但应该颠倒顺序。我们的案例研究采用了粒子在细胞内的等离子体模拟代码,这支持了我们的观察,即从性能的角度来看,将现有代码简单移植到至强融核是不可行的,我们必须对代码结构进行重大更改,以便符合处理器的功能。但是,该研究还证实,与在Cray XE6的四个双插槽节点上执行时获得的单节点性能相比,实现较高的单节点性能得到了很好的回报。 (C)2015 Elsevier Ltd.保留所有权利。

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