现场可编程门阵列的高性能谱元方法:实现、评估和未来预测

Martin Karp, Artur Podobas, Niclas Jansson, Tobias Kenter, Christian Plessl, P. Schlatter, S. Markidis
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引用次数: 9

摘要

从历史上看,计算机系统的改进依赖于两个著名的观察:摩尔定律和登纳德缩放定律。今天,这两种观察都结束了,迫使计算机用户、研究人员和实践者放弃通用架构的舒适,转而支持新兴的后摩尔系统。在这些后摩尔系统中,最突出的是现场可编程门阵列(FPGA),它在复杂性和性能之间取得了方便的平衡。本文研究了现代fpga在加速谱元法(SEM)核心在许多计算流体动力学(CFD)应用中的适用性。我们设计了一个定制的SEM硬件加速器,以双精度运行,我们对最新的Stratix 10 gx系列fpga进行了经验评估,并将其性能(和功率效率)与最先进的系统(如ARM ThunderX2, NVIDIA Pascal/Volta/Ampere Teslaseries卡和通用多核cpu)进行了比较。最后,我们为我们的sem加速器开发了一个性能模型,我们用它来预测未来FPGA的性能和作用,以加速CFD应用,最终回答了这个问题:一个完美的FPGA应该具有哪些特性?
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High-Performance Spectral Element Methods on Field-Programmable Gate Arrays : Implementation, Evaluation, and Future Projection
Improvements in computer systems have historically relied on two well-known observations: Moore’s law and Dennard’s scaling. Today, both these observations are ending, forcing computer users, researchers, and practitioners to abandon the general-purpose architectures’ comforts in favor of emerging post-Moore systems. Among the most salient of these post-Moore systems is the Field-Programmable Gate Array (FPGA), which strikes a convenient balance between complexity and performance. In this paper, we study modern FPGAs’ applicability in accelerating the Spectral Element Method (SEM) core to many computational fluid dynamics (CFD) applications. We design a custom SEM hardware accelerator operating in double-precision that we empirically evaluate on the latest Stratix 10 GX-series FPGAs and position its performance (and power-efficiency) against state-of-the-art systems such as ARM ThunderX2, NVIDIA Pascal/Volta/Ampere Teslaseries cards, and general-purpose manycore CPUs. Finally, we develop a performance model for our SEM-accelerator, which we use to project future FPGAs’ performance and role to accelerate CFD applications, ultimately answering the question: what characteristics would a perfect FPGA for CFD applications have?
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