并行FFT算法在SmartCell粗粒度可重构架构上的映射

C. Liang, Xinming Huang
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引用次数: 31

摘要

本文提出了一种新的并行FFT算法在SmartCell上的实现,这是一种针对数据流应用的粗粒度可重构架构。提出的FFT算法实现了计算单元之间的负载和内存需求平衡,同时以较低的配置和通信成本保持优化的数据流。然后将所提出的并行FFT算法映射到具有64个处理单元的SmartCell原型设备上。结果表明,在SmartCell上实现并行FFT的速度分别比片上网络(NoC)和Morphosys快14.9倍和2.7倍。与FPGA上的流水线FFT实现相比,该实现的能效提高了约3.6倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mapping Parallel FFT Algorithm onto SmartCell Coarse-Grained Reconfigurable Architecture
This paper presents the implementation of a novel parallel FFT algorithm on SmartCell, a coarse-grained reconfigurable architecture, which is targeted on data streaming applications. The proposed FFT algorithm achieves balanced workload and memory requirement among the computational units, while maintaining optimized data flow at low configuration and communication cost. The proposed parallel FFT algorithm is then mapped onto the SmartCell prototype device with 64 processing elements. Results show that the parallel FFT implementation on SmartCell is about 14.9 and 2.7 times faster than network-on-chip (NoC) and Morphosys, respectively. The implementation also shows about 3.6 times better energy efficiency when comparing with the pipelined FFT implementations on FPGA.
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