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HACC: Extreme scaling and performance across diverse architectures

机译:HACC:跨多种架构的极高扩展性和性能

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Supercomputing is evolving towards hybrid and acceleratorbased architectures with millions of cores. The HACC (Hardware/Hybrid Accelerated Cosmology Code) framework exploits this diverse landscape at the largest scales of problem size, obtaining high scalability and sustained performance. Developed to satisfy the science requirements of cosmological surveys, HACC melds particle and grid methods using a novel algorithmic structure that flexibly maps across architectures, including CPU/GPU, multi/many-core, and Blue Gene systems. We demonstrate the success of HACC on two very different machines, the CPU/GPU system Titan and the BG/Q systems Sequoia and Mira, attaining unprecedented levels of scalable performance. We demonstrate strong and weak scaling on Titan, obtaining up to 99.2% parallel efficiency, evolving 1.1 trillion particles. On Sequoia, we reach 13.94 PFlops (69.2% of peak) and 90% parallel efficiency on 1,572,864 cores, with 3.6 trillion particles, the largest cosmological benchmark yet performed. HACC design concepts are applicable to several other supercomputer applications.
机译:超级计算正在向具有数百万个内核的混合和基于加速器的架构发展。 HACC(硬件/混合加速宇宙论代码)框架在最大的问题规模上利用了这种多样化的格局,从而获得了高可扩展性和持续的性能。 HACC的开发旨在满足宇宙学调查的科学要求,它使用一种新颖的算法结构将粒子和网格方法融合在一起,该结构可灵活地跨体系结构进行映射,包括CPU / GPU,多核/多核和Blue Gene系统。我们展示了HACC在两种截然不同的机器(CPU / GPU系统Titan和BG / Q系统Sequoia和Mira)上的成功,它们实现了前所未有的可扩展性能。我们在Titan上显示了强而弱的缩放比例,获得了高达99.2%的并行效率,演化了1.1万亿个粒子。在红杉上,我们在1,572,864个核上拥有13.94 PFlops(峰值的69.2%)和90%的并行效率,其中有3.6万亿个粒子,这是迄今为止执行的最大的宇宙学基准。 HACC设计概念适用于其他几种超级计算机应用程序。

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