Abstract
With the growth of packet-switch networks in the mobile consumer electronics market, fountain codes are coming to play an increasingly important role as they allow high packet loss rates while still supporting high QoS. This is particularly critical for video streaming in multimedia delivery on moving handheld mobile consumer devices. A powerful forward error-correction mechanism is the fountain coding scheme implemented by RaptorQ codes, defined over GF(256), whose decoding algorithms are very complex from a computational perspective, but highly suitable for parallelization. With multimedia delivery for handheld consumer electronics in mind, this paper proposes several decoding schemes for embedded mobile SoCs, exploiting both the parallel potential of the GPU and CPU, sharing a common memory space. The OpenCL and OpenMP frameworks are used to exploit both accelerators for the roles of matrix multiplication and inversion that comprise the bulk of computation in RaptorQ decoding. Reported results indicate low-power requirements within the range of typical handheld consumer devices (1.5~2.4W) for data processing rates of dozens of Mbit/s that are fully within the real-time requirements of HD, 2K and 4K coded video streaming resolutions and beyond.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
