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Fast Data Analytics with FPGAs

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    Publication properties
    Title: Fast Data Analytics with FPGAs
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    Discussion: 1 comment
    Date: 2011
    Publication type: Conference paper
    Authors:
    No. First name Last name Show
    1. Louis Woods
    2. Gustavo Alonso
    Download (from PubZone): Download
    Download (by DOI): 10.1109/ICDEW.2011.5767669
    BibTeX: conf/icde/WoodsA11
    DBLP: db/conf/icde/icdew2011.html#WoodsA11
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    Conference
    Name: Workshops Proceedings of the 27th International Conference on Data Engineering, ICDE 2011, April 11-16, 2011, Hannover, Germany 2011
    URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5765044
    DBLP: db/conf/icde/icdew2011.html

    Abstract

    The rapidly increasing amount of data available for real-time analysis (i.e., so-called operational business intelligence) is creating an interesting opportunity for creative approaches to speeding up data processing algorithms. One such approach that is starting to become more common is using hardware accelerators for stream processing. Typically these accelerators are implemented on top of reconfigurable hardware, known as fieldprogrammable gate arrays (FPGAs). Though the value of FPGAs for data warehouses is gradually recognized by the database community, their true potential for various business analytic tasks is yet unexplored. In this line of research, we investigate FPGA technology in the context of extreme data processing looking for opportunities where FPGAs can be exploited to improve over classical CPU-based architectures. We introduce a framework for FPGA-accelerated (real-time) analytics including a query-tohardware compiler for static complex event detection, an XPath engine for dynamic query workloads, and templates for highspeed data mining operators in hardware.