high performance computing on graphics processing units: hgpu.org

Despite recent advances in FPGA, GPU, and general purpose processor technologies, the challenges posed by real-time digital image processing at high resolutions cannot be fully overcome due to insufficient processing capability, inadequate data transport and control mechanisms, and often prohibitively high costs. To address these issues, we proposed a two-phase solution for a real-time film grain noise reduction application. The first phase is based on a state-of-the-art FPGA platform used as a reference design. The second phase is based on a novel heterogeneous reconfigurable computing platform that offers flexibility not available from other computing paradigms. This paper introduces the heterogeneous platform and briefly reviews our previous work with the application in question, as well as its implementation on the FPGA demonstration board during the first phase. Then we present a decomposition of the application, which allows an efficient mapping to the new heterogeneous computing platform through the use of its diverse reconfigurable computing units and run-time reconfiguration.