Title :
ZCluster: A Zynq-based Hadoop cluster
Author :
Zhongduo Lin ; Chow, Peter
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Toronto, Toronto, ON, Canada
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.
Keywords :
FIR filters; field programmable gate arrays; low-power electronics; microprocessor chips; system-on-chip; ARM-based cluster; ARM-based servers; CPU; FIR filter; FPGA fabric; Xilinx Zynq SoC; Xillybus; ZCluster; Zynq-based Hadoop cluster; big data processing; customized hardware accelerator; hardware acceleration; low power consumption; processing capability; single ARM processor; software implementation; Field programmable gate arrays; Finite impulse response filters; Hardware; IP networks; Servers; Software; System-on-chip;
Conference_Titel :
Field-Programmable Technology (FPT), 2013 International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4799-2199-7
DOI :
10.1109/FPT.2013.6718411