Accelerating Image Algorithm Development using Soft Co-Processors on FPGAS

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    FPGAS can offer high performance with low power and low hardware usage. However, with current software, FPGAS are hard to program, and lengthy re-synthesis times make them unsuitable for the algorithm experimentation which is typical of developing image processing applications. In this paper, we present a system model based on a set of Soft Co-Processors, each of which implements a basic image-level operation (or a common combination of such operations) based on the high-level operators in Image Algebra. Both 'debug' (generic but unoptimised) and 'release' (specific and optimised) versions of the Soft Co-Processors can be used. The advantage of debug mode is that no re-synthesis is required during algorithm experimentation. For release mode, a novel macro-based transformation tool enables the creation of a set of reusable HLS skeleton co-processors which require the user only to write a C function to obtain a new, special-purpose Soft Co-Processor.Initial experiments with several algorithms show that the area and speed overheads for using debug (rather than release) mode are both around 25-30%, thus enabling algorithm development to take place on the FPGA itself. For creating function-specific Co-processors using our macro-based tool, the overheads compared with an expert hardware design are around 20%.

    Original languageEnglish
    Title of host publication29th Irish Signals and Systems Conference (ISSC 2018): Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Number of pages6
    ISBN (Electronic)9781538660461
    ISBN (Print)978-1-5386-6047-8
    DOIs
    Publication statusPublished - 24 Dec 2018
    Event29th Irish Signals and Systems Conference, ISSC 2018 - Belfast, United Kingdom
    Duration: 21 Jun 201822 Jun 2018

    Conference

    Conference29th Irish Signals and Systems Conference, ISSC 2018
    CountryUnited Kingdom
    CityBelfast
    Period21/06/201822/06/2018

      Research areas

    • FPGA, Image Algebra, Image Processing

    ID: 164937748