Low Communication Overhead Dynamic Mapping of Multiple HEVC Video Stream Decoding on NoCs
H. R. Mendis and L. S. Indrusiak
The High Effifficiency Video Coding (HEVC) standard offers several parallelisation tools such as wave-front parallel processing (WPP) and Tiles (independent frame regions) to better manage the computationally expensive workloads on modern multicore/many-core platforms. However, poor allocation of tile-level HEVC decoding tasks to processing elements may result in increased latency and energy consumption due to data communication overhead between dependent tiles. In this work, we discuss the diffifficulties in decoding multiple HEVC bitstreams with highly varying resolutions and data-dependency characteristics as seen in HEVC coded video streams with random-access, adaptive group of pictures (GoP) structures. Secondly, in order to address the above challenges, we introduce a runtime tile allocation scheme that help to reduce the energy usage during HEVC decoding. Evaluations against a bin-packing algorithm, show that the proposed workload mapping technique is able to maintain reasonably acceptable latency results, whilst reducing communication overhead (8-10
BibTex Entry
@inproceedings{Mendis2016,
author = {H. R. Mendis and L. S. Indrusiak},
booktitle = {Proc. 7th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures (PARMA-DITAM) - HiPEAC Conference},
pages = {19-24},
title = {Low Communication Overhead Dynamic Mapping of Multiple HEVC Video Stream Decoding on NoCs},
year = {2016}
}