Revealing Feasibility of FMM on ASIC: Efficient Implementation of N-Body Problem on FPGA

Zhe Zheng, Yongxin Zhu, Xu Wang, Zhiqiang Que, Tian Huang, X. Yin, Hui Wang, G. Rong, Meikang Qiu
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引用次数: 6

Abstract

FPGAs have been improved significantly in terms of performance and capacity over the last 20 years. The scale of FPGA based design also sparked off the demands for high-level synthesis to handle complicated applications. A well known intricate application is the FMM (Fast Multipole Method) algorithm of N-body problem, which is so complicated that it was not implemented on FPGA as reported in literature. In this paper, we take high level modeling and design tools, i.e. Simulink and System Generator to implement major modules in FMM algorithm to solve the N-Body problem on FPGA. Besides the impressive performance speedup on FPGA, we improve the efficiency by merging the circuits for the common logic among modules in the algorithm. Our experience in efficiently implementing the FMM algorithm will be taken as a useful reference for researchers working on FPGA applications as well as high performance computing.
揭示FMM在ASIC上的可行性:n体问题在FPGA上的高效实现
在过去的20年里,fpga在性能和容量方面都有了显著的改进。基于FPGA的设计规模也引发了对高级综合的需求,以处理复杂的应用。一个众所周知的复杂应用是n体问题的FMM (Fast Multipole Method)算法,由于其复杂性,目前文献中尚未在FPGA上实现。本文采用高级建模和设计工具Simulink和System Generator实现FMM算法中的主要模块,在FPGA上解决n体问题。除了在FPGA上有显著的性能加速外,我们还通过合并算法中模块之间的公共逻辑电路来提高效率。我们在有效实现FMM算法方面的经验将为FPGA应用和高性能计算的研究人员提供有用的参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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