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Challenges of Computing with FLASH on Largest HPC Platforms

机译:在最大的HPC平台上使用Flash计算的挑战

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FLASH is a highly capable multiphysics multiscale modular extensible code, originally designed for simulating reactive flows. FLASH consists of interoperable modules that can be combined to generate different applications such as simulations of novae, supernovae, X-Ray bursts, galaxy clusters, weakly compressible turbulence, and many other problems in astrophysics and other fields. FLASH has a wide user base, both within and outside the Flash Center, and is regularly used on largest available HPC platforms. With each new platform we encounter a new set of challenges, because the multiscale multiphysics nature of FLASH simulations exercise the machine's hardware and system software greatly. The increase in the degree of concurrency with each new hardware generation has imposed changes on some of FLASH's parallel algorithms. The pace of change has accelerated with the move towards petascale, and then to exascale. In this work we present some of our scaling hurdles and their solutions. In addition we discuss a more fundamental transition in the code to incorporate a hybrid shared and distributed memory model in preparation for the future million- to billion-way parallelism.
机译:Flash是一种高度的多体式多尺度模块化可扩展代码,最初为模拟反应流设计。 Flash由可互操作的模块组成,可以组合以产生不同的应用,例如Novae,Supernovae,X射线突发,星系集群,弱可压缩湍流以及天体物理学和其他领域的许多其他问题。 Flash在Flash Center内外都有一个宽的用户群,并经常在最大可用的HPC平台上使用。通过每个新平台,我们遇到了一系列新的挑战,因为Flash模拟的MultiScale Multiphysics性质大大锻炼机器的硬件和系统软件。每个新硬件生​​成的并发程度的增加对一些Flash的并行算法强加了改变。变化的步伐加速了迈向彭莱斯的举动,然后加速了Exascale。在这项工作中,我们展示了我们的一些缩减障碍及其解决方案。此外,我们讨论了代码中的更基本的过渡,以纳入混合共享和分布式内存模型,以准备未来百万到亿到十亿路行信。

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