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HARP(2): An X-Scale Reconfigurable Accelerator-Rich Platform for Massively-Parallel Signal Processing Algorithms

机译:HARP(2):适用于大规模并行信号处理算法的X规模可重配置加速器丰富平台

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This paper presents design, development and evaluation of an eXtra-large Scale, Homogeneous and a Heterogeneous Accelerator-Rich Platform (HARP(2)) for massively parallel signal processing algorithms. HARP is an integrated platform of multiple Coarse-Grained Reconfigurable Arrays (CGRAs) over a Network-on-Chip (NoC) where each CGRA is scaled and tailored for a specific application. The architecture of the NoC consists of nine nodes in a topology of 3-rowsx3-columns and acts as backbone of communication between different CGRAs. In this experimental work, the HARP template is used to instantiate a homogeneous (HARP-hom) and a heterogeneous (HARP-het) platform. The HARP-het is generated for a proof-of-concept test to verify the design and functionality of HARP. It also provides insight to many features of the design and evaluation in terms of different performance metrics. The other version (HARP-hom) is instantiated for a relatively realistic design problem, i.e., satisfying the execution-time constraints imposed on Fast Fourier Transform processing in IEEE-802.11n demodulators. Both of the versions of HARP are treated for comparative analysis using different performance metrics against some of the existing state-of-the-art platforms. The HARP versions are designed to illustrate large-scale homogeneous/heterogeneous multicore architectures while presenting the advantages of maximizing the number of reconfigurable processing resources on a single chip.
机译:本文介绍了针对大规模并行信号处理算法的超大型,同质和异构加速器丰富平台(HARP(2))的设计,开发和评估。 HARP是片上网络(NoC)上的多个粗粒度可重配置阵列(CGRA)的集成平台,其中每个CGRA都针对特定应用进行了缩放和定制。 NoC的体系结构由3行x3列的拓扑结构中的9个节点组成,并充当不同CGRA之间通信的骨干。在此实验工作中,HARP模板用于实例化同构(HARP-hom)和异构(HARP-het)平台。生成HARP-het用于概念验证测试,以验证HARP的设计和功能。它还可以根据不同的性能指标洞察设计和评估的许多功能。针对相对现实的设计问题实例化了另一个版本(HARP-hom),即满足在IEEE-802.11n解调器中对快速傅立叶变换处理施加的执行时间约束。针对某些现有的最新平台,使用了不同的性能指标来对这两个版本的HARP进行比较分析。 HARP版本旨在说明大规模的同质/异质多核体系结构,同时具有最大限度地提高单个芯片上可重配置处理资源数量的优势。

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