ZCluster: A Zynq-based Hadoop cluster
Zhongduo Lin, Paul Chow · 2013
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.