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Exploring SIMD for Molecular Dynamics, Using Intel® Xeon® Processors and Intel® Xeon Phi Coprocessors

机译:使用英特尔®至强®处理器和英特尔®至强融核协处理器探索分子动力学的SIMD

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We analyse gather-scatter performance bottlenecks in molecular dynamics codes and the challenges that they pose for obtaining benefits from SIMD execution. This analysis informs a number of novel code-level and algorithmic improvements to Sandia's miniMD benchmark, which we demonstrate using three SIMD widths (128-, 256- and 512-bit). The applicability of these optimisations to wider SIMD is discussed, and we show that the conventional approach of exposing more parallelism through redundant computation is not necessarily best. In single precision, our optimised implementation is up to 5x faster than the original scalar code running on Intel Xeon processors with 256-bit SIMD, and adding a single Intel Xeon Phi coprocessor provides up to an additional 2x performance increase. These results demonstrate: (i) the importance of effective SIMD utilisation for molecular dynamics codes on current and future hardware, and (ii) the considerable performance increase afforded by the use of Intel Xeon Phi coprocessors for highly parallel workloads
机译:我们分析了分子动力学代码中的聚集-散射性能瓶颈,以及它们从SIMD执行中获得收益所带来的挑战。该分析为Sandia的miniMD基准测试提供了许多新颖的代码级和算法改进,我们使用三种SIMD宽度(128位,256位和512位)进行了演示。讨论了这些优化方法对更广泛的SIMD的适用性,并且我们证明了通过冗余计算公开更多并行性的常规方法不一定是最好的。就单精度而言,我们优化的实现比运行在具有256位SIMD的Intel Xeon处理器上的原始标量代码快5倍,并且添加单个Intel Xeon Phi协处理器可将性能提高2倍。这些结果证明:(i)有效利用SIMD对于当前和将来的硬件上的分子动力学代码的重要性,以及(ii)通过使用英特尔至强融核协处理器处理高度并行的工作负载,可以显着提高性能。

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