Accelerated motion estimation of h.264 on imagine stream processor

Authors:
Haiyan Li;Mei Wen;Chunyuan Zhang;Nan Wu;Li Li;Changqing Xun
Affiliations:
School of Computer Science, National University of Defense Technology, Chang Sha, Hu Nan, P. R. of China;School of Computer Science, National University of Defense Technology, Chang Sha, Hu Nan, P. R. of China;School of Computer Science, National University of Defense Technology, Chang Sha, Hu Nan, P. R. of China;School of Computer Science, National University of Defense Technology, Chang Sha, Hu Nan, P. R. of China;School of Computer Science, National University of Defense Technology, Chang Sha, Hu Nan, P. R. of China;School of Computer Science, National University of Defense Technology, Chang Sha, Hu Nan, P. R. of China
Venue:
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Year:
2005

Citing 4
Cited 1

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MICRO 31 Proceedings of the 31st annual ACM/IEEE international symposium on Microarchitecture
Imagine: Media Processing with Streams

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Media Processing Applications on the Imagine Stream Processor

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A parallel reed-solomon decoder on the imagine stream processor

ISPA'04 Proceedings of the Second international conference on Parallel and Distributed Processing and Applications

A stream architecture supporting multiple stream execution models

ACSAC'05 Proceedings of the 10th Asia-Pacific conference on Advances in Computer Systems Architecture

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Abstract

Imagine is a stream-based prototype processor designed for media processing. It uses a three-level bandwidth hierarchy to exploit parallelism and data locality. It has good performance in media processing. H.264 is the newest digital video coding standard. It can achieve high coding efficiency at the cost of complex computation. In addition, video pictures have natural stream features, such as good special locality and limited temporal dependency. This paper presents an accelerated implementation of motion estimation, which is the most time-consuming part in H.264 coding framework, on Imagine stream processor. Experimental results show that the coding efficiency for QCIF format can be up to 372fps and surpass real-time requirement. The acceleration of stream processing is significant. It proves that H.264 coding is suited for implementation on Imagine.