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Parallelization of Computing-Intensive Tasks of the H.264 High Profile Decoding Algorithm on a Reconfigurable Multimedia System

Tongsheng GENG, Leibo LIU, Shouyi YIN, Min ZHU, Shaojun WEI

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Summary :

This paper proposes approaches to perform HW/SW (Hardware/Software) partition and parallelization of computing-intensive tasks of the H.264 HiP (High Profile) decoding algorithm on an embedded coarse-grained reconfigurable multimedia system, called REMUS (REconfigurable MUltimedia System). Several techniques, such as MB (Macro-Block) based parallelization, unfixed sub-block operation etc., are utilized to speed up the decoding process, satisfying the requirements of real-time and high quality H.264 applications. Tests show that the execution performance of MC (Motion Compensation), deblocking, and IDCT-IQ (Inverse Discrete Cosine Transform-Inverse Quantization) on REMUS is improved by 60%, 73%, 88.5% in the typical case and 60%, 69%, 88.5% in the worst case, respectively compared with that on XPP PACT (a commercial reconfigurable processor). Compared with ASIC solutions, the performance of MC is improved by 70%, 74% in the typical and in the worst case, respectively, while those of Deblocking remain the same. As for IDCT_IQ, the performance is improved by 17% no matter in the typical or worst case. Relying on the proposed techniques, 1080p@30 fps of H.264 HiP@ Level 4 decoding could be achieved on REMUS when utilizing a 200 MHz working frequency.

Publication
IEICE TRANSACTIONS on Information Vol.E93-D No.12 pp.3223-3231
Publication Date
2010/12/01
Publicized
Online ISSN
1745-1361
DOI
10.1587/transinf.E93.D.3223
Type of Manuscript
Special Section PAPER (Special Section on Parallel and Distributed Computing and Networking)
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