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Dynamic adaptations in ab-initio nuclear physics calculations on multicore computer architectures

机译:AB-Initio核物理计算的动态调整在多核计算机架构上

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Computational resource availability often changes during the course of execution of an application. This is especially true in modern multi-user cluster environments where users can run many high-performance applications simultaneously which share resources such as Processing Elements (PEs), I/O, main memory, network. In such a scenario, it would be greatly advantageous to have applications augmented with adaptive capabilities, particularly during runtime. This involves targeting a computationally intensive part of the application and invoking appropriate adaptations so as to be able to adjust to the dynamically changing system conditions, to prevent drastic performance loss. In this paper, the parallel application MFDn (Many Fermion Dynamics for nuclear structure) used for ab-initio nuclear physics calculations is integrated with a middleware tool for invoking such adaptations. In particular, the multi-threaded Lanczos diagonalization procedure in MFDn is targeted to observe the effect on performance of dynamically changing the number of threads during the iterative process. Performance gains between two to seven times were observed in the presence of competing applications by incorporating these adaptation strategies.
机译:计算资源可用性通常在执行应用程序期间更改。这在现代多用户群环境中尤其如此,用户可以同时运行许多高性能应用程序,其中共享资源,例如处理元素(PES),I / O,主内存,网络。在这样的场景中,使应用程序具有增强的自适应能力,特别是在运行时存在大大有利的。这涉及针对应用的计算密集部分,并调用适当的适应,以便能够调整到动态变化的系统条件,以防止剧烈性能损失。在本文中,用于AB-Initio核物理计算的并行应用MFDN(用于核结构的许多费用动力学)与用于调用此类适应的中间件工具集成。特别地,MFDN中的多线程LanczoS对角化过程旨在观察对动态改变迭代过程中线程数的性能的影响。通过纳入这些适应策略,在竞争应用程序存在下观察到两到七次的性能提升。

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