Paper Info
Title
Stage-based frame-partitioned parallelization of H.264/AVC decoding
Abstract
Strong demands for high resolution video services lead to active studies on high speed video processing. Especially, widespread deployment of multi-core systems accelerates researches on high resolution video processing based on parallelization of multimedia software. In this paper, we propose a novel parallel H.264/AVC decoding scheme on a homogeneous multi-core platform. Parallelization of H.264/AVC decoding is challenging not only because parallelization may incur significant synchronization overhead but also because software may have complicated dependencies. To overcome such issues, we propose a novel approach called Stage-based Frame-Partitioned Parallelization (SFPP). In SFPP, we divide a frame into multiple partitions, and execute them in a pipelined fashion. To reduce synchronization overhead, a separate thread is allocated to each stage in the pipeline. In addition, an efficient memory reuse technique is used to reduce the memory requirement. To verify the effectiveness of the proposed approach, we parallelized FFmpeg H.264/AVC decoder with the proposed technique using OpenMP, and carried out experiments on an Intel Quad-Core platform. The proposed design performs better than FFmpeg H.264/AVC decoder before parallelization by 53%. We also reduced the amount of memory usage by 65% and 81% for a high-definition (HD) and a full high-definition (FHD) video, respectively compared with that of a popular existing method.
Year
DOI
Venue
2010
10.1109/TCE.2010.5506043
IEEE Trans. Consumer Electronics
Keywords
Field
DocType
h.264/avc,parallelized ffmpeg h.264/avc decoder,high resolution video service,parallel processing,memory usage,quadcore platform,high speed video processing,homogeneous multicore platform,data compression,overhead synchronization,memory reuse technique,avc decoding,memory requirement,ffmpeg h.264,avc decoding scheme,openmp technique,video coding,decoding,efficient memory reuse technique,multimedia software,avc decoder,high resolution video service processing,stage-based frame-partitioned parallelization,full high-definition video,high resolution video processing,synchronisation,acceleration,high resolution,pipelines,video compression,video processing,high performance computing
High-definition video,Video processing,Synchronization,Supercomputer,Computer science,Parallel computing,Thread (computing),Decoding methods,Data compression,Automatic parallelization
Journal
Volume
Issue
ISSN
56
2
0098-3063
Citations 
PageRank 
References 
5
0.47
11
Authors
3
Name
Order
Citations
PageRank
Won-Jin Kim1213.81
Keol Cho292.17
Ki-seok Chung318918.76