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HACC: Extreme scaling and performance across diverse architectures

机译:HACC:各种架构的极端缩放和性能

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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:超级也在不断发展混合动力和acceleratorbased架构与内核数以百万计的。该HACC(硬件/混合加速宇宙学准则)框架利用在问题规模最大尺度这个多样化的景观,获得高可扩展性和持续性能。开发用于满足宇宙调查的科学要求,采用一种新颖的算法结构,其灵活地跨架构,包括CPU / GPU,多/众核,和蓝色基因系统映射HACC融合了粒子和网格方法。我们证明HACC对两个非常不同的机器上,CPU / GPU系统泰坦和BG / Q系统红杉和米拉,达到了前所未有的可扩展的性能水平的成功。我们证明土卫六上的强与弱的比例,获得高达99.2%的并行效率,不断发展的1.1万亿颗粒。在红杉,我们对1572864个核心达到13.94 PFlops(峰值的69.2%)和90%的并行效率,有3.6万亿的颗粒,但执行的最大的宇宙基准。 HACC的设计概念也适用于其他几个超级计算机应用程序。

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