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SOCA-DOM: A Mobile System-on-Chip Array System for Analyzing Big Data on the Move

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Abstract

Recently, analyzing big data on the move is booming. It requires that the hardware resource should be low volume, low power, light in weight, high-performance, and highly scalable whereas the management software should be flexible and consume little hardware resource. To meet these requirements, we present a system named SOCA-DOM that encompasses a mobile system-on-chip array architecture and a two-tier “software-defined” resource manager named Chameleon. First, we design an Ethernet communication board to support an array of mobile system-on-chips. Second, we propose a two-tier software architecture for Chameleon to make it flexible. Third, we devise data, configuration, and control planes for Chameleon to make it “software-defined” and in turn consume hardware resources on demand. Fourth, we design an accurate synthetic metric that represents the computational power of a computing node. We employ 12 Apache Spark benchmarks to evaluate SOCA-DOM. Surprisingly, SOCA-DOM consumes up to 9:4x less CPU resources and 13.5x less memory than Mesos which is an existing resource manager. In addition, we show that a 16-node SOCA-DOM consumes up to 4x less energy than two standard Xeon servers. Based on the results, we conclude that an array architecture with fine-grained hardware resources and a software-defined resource manager works well for analyzing big data on the move.

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Authors and Affiliations

  1. Center for Heterogeneous and Intelligent Computing, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China

    Le-Le Li, Jiang-Yi Liu & Zhi-Bin Yu

  2. School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Shenzhen, 518172, China

    Le-Le Li

  3. Center for High Performance Computing, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China

    Jian-Ping Fan

  4. Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, 90089-0001, USA

    Xue-Hai Qian

  5. Department of Computer Science, University of Southern California, Los Angeles, CA, 90089-0001, USA

    Xue-Hai Qian

  6. School of Data and Science, The Chinese University of Hong Kong, Shenzhen, Shenzhen, 518172, China

    Kai Hwang & Yeh-Ching Chung

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  1. Le-Le Li
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Li, LL., Liu, JY., Fan, JP. et al. SOCA-DOM: A Mobile System-on-Chip Array System for Analyzing Big Data on the Move. J. Comput. Sci. Technol. 37, 1271–1289 (2022). https://doi.org/10.1007/s11390-022-1087-z

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