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A Mixed-Grained Reconfigurable Computing Platform for Multiple-Standard Video Decoding (Abstract Only)

Published:22 February 2015Publication History

ABSTRACT

A mixed-grained reconfigurable computing platform targeting multiple-standard video decoding is proposed in this paper. The platform integrates eight coarse-grained Reconfigurable Processing Units (RPUs), each of which consists of 16×16 multi-functional Processing Elements (PEs) and are implemented in TSMC 65 nm technology and two Altera Stratix IV EP4SE820 FPGAs. By exploiting dynamic reconfiguration of the RPUs and static reconfiguration of the FPGAs, the proposed platform achieves scalable performances and cost trade-offs to support a variety of video coding standards, including H.264, MPEG-2, AVS and HEVC. Two types of platform configuration are tested in this work. One configuration utilizes two RPUs and targets multiple-standard high-definition (HD) video decoding, while the other utilizes only one RPU, which works under a lower frequency and targets at standard resolution (SD) decoding. The HD configuration can decode 1920×1080 H.264 video streams at 30 frames per second (fps) under 200 MHz and 1920×1080 HEVC video streams at 30 fps under 236 MHz. It achieves a 25% performance gain over an industrial coarse-grained reconfigurable processor for H.264 decoding, and a 3.85× performance boosts over the Intel i5 general-purpose CPU for HEVC decoding.

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  1. A Mixed-Grained Reconfigurable Computing Platform for Multiple-Standard Video Decoding (Abstract Only)

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      • Published in

        cover image ACM Conferences
        FPGA '15: Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays
        February 2015
        292 pages
        ISBN:9781450333153
        DOI:10.1145/2684746

        Copyright © 2015 Owner/Author

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 22 February 2015

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        Acceptance Rates

        FPGA '15 Paper Acceptance Rate20of102submissions,20%Overall Acceptance Rate125of627submissions,20%