LI Gezi, CHEN Xiaogang, LI Shunfen, et al., “FPGA-Enhanced Data Processing System Using PCM Technology,” Chinese Journal of Electronics, vol. 29, no. 4, pp. 766-771, 2020, doi: 10.1049/cje.2020.06.004
Citation: LI Gezi, CHEN Xiaogang, LI Shunfen, et al., “FPGA-Enhanced Data Processing System Using PCM Technology,” Chinese Journal of Electronics, vol. 29, no. 4, pp. 766-771, 2020, doi: 10.1049/cje.2020.06.004

FPGA-Enhanced Data Processing System Using PCM Technology

doi: 10.1049/cje.2020.06.004
Funds:  This work is supported by the the Strategic Priority Research Program of the Chinese Academy of Sciences (No.XDA09020402), the National Integrate Circuit Research Program of China (No.2009ZX02023- 003), Pudong New Area science and Technology Development Fund (No.PKJ2015-Z06), the National Natural Science Foundation of China (No.61376006, No.61401444, No.61504157, No.61622408), and Science and Technology Council of Shanghai (No.14ZR1447500, No.15DZ2270900).
  • Received Date: 2017-02-22
  • Rev Recd Date: 2017-06-08
  • Publish Date: 2020-07-10
  • Due to unique features, Storage class memory (SCM) technologies such as Phase change memory (PCM) open up new opportunities for architect engineers. In such a scenario, we present a true PCM storage system with an FPGA storage controller to explore ISP benefits. Our contributions are summarized as follows. 1) Propose a heterogeneous ISP architecture which uses FPGA working as storage controller and accelerator; 2) Offer a new research direction for designing storage devices which inherently support ISP; 3) Present a novel storage system which eliminate data transfer; 4) The first evaluation of ISP on a real SCM device; 5) Demonstrate significant performance gains by using efficient data flow and consuming extremely small amounts of host resources. Besides, the proposed system can be extended to handle other kinds of data applications by adding corresponding accelerator and data conversion module in FPGA. Multinode system can be realized for more aggressive results.
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  • E. Riedel, C. Faloutsos, G.A. Gibson, et al., “Active disks for large-scale data processing”, Computer, Vol.34, No.6, pp. 68-74, 2001.
    K. Keeton, D.A. Patterson and J.M. Hellerstein, “A case for intelligent disks (IDISKs)”, Acm Sigmod Record, Vol.27, No.3, pp.42-52, 1998.
    J. Do, Y.S. Kee, J.M. Patel, et al., “Query processing on smart SSDs: Opportunities and challenges”, ACM SIGMOD Int. Conf. on Management of Data, New York, USA, pp.1221-1230, 2013.
    Y. Kang, Y. Kee, E.L. Miller, et al., “Enabling cost-effective data processing with smart SSD”, Mass Storage Systems and Technologies, Long Beach, California, USA, pp.1-12, 2013.
    E. Doller, A. Akel, J. Wang, et al., “Datacenter 2020: Nearmemory acceleration for data-oriented applications”, VLSI Circuits Digest of Technical, Honolulu, Hawaii, USA, pp.1-4, 2014.
    Q.M. Yang, N. Wu, M. Wen, et al., “TISA: Reconfigurable system for template-based stream computing”, Chinese Journal of Electronics, Vol.21, No.4, pp.594-598, 2012.
    M. Singh and B. Leonhardi, “Introduction to the IBM netezza warehouse appliance”, Conference of the Center for Advanced Studies on Collaborative Research, Toronto, Ontario, Canada, pp.385-386, 2011.
    Oracle, “Exadata database machine”, https://www.oracle.com/engineered-systems/exadata/index.html, 2014-12-18.
    O. Kocberber, B. Grot, J. Picorel, et al., “Meet the walkers: Accelerating index traversals for in-memory databases”, IEEE/ACM International Symposium on Microarchitecture, Davis, California, United States, pp.468-479, 2013.
    L. Woods, Z. Istvan and G. Alonso, “Hybrid FPGAaccelerated SQL query processing”, International Conf. on Field Programmable Logic and Applications, Porto, Portugal, pp:1-4, 2013.
    S.W. Jun, M. Liu, K.E. Fleming, et al., “Scalable multiaccess flash store for big data analytics”, ACM/SIGDA International Sym. on Field-programmable Gate Arrays, Monterey, California, USA, pp.55-64, 2014.
    Z. Zhou, W.L. Fu, T. Song, et al., “Fast URL lookup using parallel bloom filters”, Chinese Journal of Electronics, Vol.43, No.9, pp.1833-1840, 2015.
    B. Sukhwani, M. Thoennes, H. Min, et al., “A hardware/software approach for database query acceleration with FPGAs”, International Journal of Parallel Programming, Vol.43, No.6, pp.1129-1159, 2015.
    D. Diamantopoulos and C. Kachris: “High-level synthesizable dataflow MapReduce accelerator for FPGA-coupled data centers”, Int. Conf. on Embedded Computer Systems: Architectures, Modeling, and Simulation, Agios Konstantinos, Samos, Greece, pp.26-33, 2015.
    W.L. Fu, P. Guo and Z. Zhou, “A hardware-accelerated L7-filter method for 100Gbps networks”, Acta Electronica Sinica, Vol.44, No.11, pp.2561-2568, 2016. (in Chinese)
    S.Y. Liu, Y.X. Wu, B.W. Zhang, et al. “Research of parallel hardware architecture for matrix triangularization decomposition based on reconfigurable computing system”, Chinese Journal of Electronics, Vol.43, No.8, pp.1642-1650, 2015.
    R.F. Freitas and W.W. Wilcke, “Storage-class memory: The next storage system technology”, IBM Journal of Research and Development, Vol.52, No.4, pp.439-447, 2008.
    G.W. Burr, B.N. Kurdi, J.C. Scott, et al., “Overview of candidate device technologies for storage-class memory”, IBM Journal of Research and Development, Vol.52, No.4.5, pp.449-464, 2010.
    S. Eilert, M. Leinwander and G. Crisenza, “Phase change memory: A new memory enables new memory usage models”, IEEE Int. Memory Workshop, Monterey, California, USA, pp.1-2, 2009.
    Z.Q. Li, R.J. Zhou and T. Li, “Exploring high-performance and energy proportional interface for phase change memory systems”, International Symposium on High Performance Computer Architecture, Shenzhen, China, pp.210-221, 2013.
    JEDEC, “Low power double data rate 2(LPDDR2)”, http://www.jedec.org/sites/default/files/docs/JESD209-2F.pdf, 2011-8-30.
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