ZCluster: A Zynq-based Hadoop cluster

Zhongduo Lin, P. Chow
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引用次数: 48

Abstract

ARM-based servers are garnering increasing interest in big data processing for their low power consumption. However, they are ill-suited for compute-intensive tasks due to their poor processing capability compared to the CPUs used in a traditional server. This paper describes our early efforts to integrate the processing power of the FPGA with the ARM processor inside the Xilinx Zynq SoC. An eight-slave Zynq-based Hadoop cluster is built and a customized hardware accelerator for a standard FIR filter is implemented to demonstrate the effectiveness of hardware acceleration. The Xillybus is used for communication between the ARM processor and the FPGA fabric, achieving a bandwidth of 103MB/s. The Hadoop cluster is proved to be linearly scalable with different input sizes and numbers of slaves. Overall, the cluster achieves a 3.3-fold speedup compared to a native pure software implementation on a single ARM processor and about a 20% improvement compared to an ARM-based cluster without hardware accelerators.
ZCluster:基于zynq的Hadoop集群
基于arm的服务器因其低功耗而在大数据处理领域引起了越来越多的兴趣。然而,它们不适合计算密集型任务,因为与传统服务器中使用的cpu相比,它们的处理能力较差。本文介绍了我们将FPGA的处理能力与ARM处理器集成到Xilinx Zynq SoC中的早期工作。构建了一个基于zynq的8 slave Hadoop集群,并实现了针对标准FIR滤波器的定制硬件加速器,以验证硬件加速的有效性。Xillybus用于ARM处理器和FPGA结构之间的通信,实现103MB/s的带宽。Hadoop集群被证明可以在不同的输入大小和slave数量下进行线性扩展。总体而言,与单个ARM处理器上的本机纯软件实现相比,集群的速度提高了3.3倍,与没有硬件加速器的基于ARM的集群相比,集群的速度提高了约20%。
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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