Efficient Parallel Video Processing Techniques on GPU: From Framework to Implementation
Joint Authors
Zhang, Chunyuan
Su, Huayou
Wen, Mei
Wu, Nan
Ren, Ju
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-16
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Through reorganizing the execution order and optimizing the data structure, we proposed an efficient parallel framework for H.264/AVC encoder based on massively parallel architecture.
We implemented the proposed framework by CUDA on NVIDIA’s GPU.
Not only the compute intensive components of the H.264 encoder are parallelized but also the control intensive components are realized effectively, such as CAVLC and deblocking filter.
In addition, we proposed serial optimization methods, including the multiresolution multiwindow for motion estimation, multilevel parallel strategy to enhance the parallelism of intracoding as much as possible, component-based parallel CAVLC, and direction-priority deblocking filter.
More than 96% of workload of H.264 encoder is offloaded to GPU.
Experimental results show that the parallel implementation outperforms the serial program by 20 times of speedup ratio and satisfies the requirement of the real-time HD encoding of 30 fps.
The loss of PSNR is from 0.14 dB to 0.77 dB, when keeping the same bitrate.
Through the analysis to the kernels, we found that speedup ratios of the compute intensive algorithms are proportional with the computation power of the GPU.
However, the performance of the control intensive parts (CAVLC) is much related to the memory bandwidth, which gives an insight for new architecture design.
American Psychological Association (APA)
Su, Huayou& Wen, Mei& Wu, Nan& Ren, Ju& Zhang, Chunyuan. 2014. Efficient Parallel Video Processing Techniques on GPU: From Framework to Implementation. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-19.
https://search.emarefa.net/detail/BIM-1050733
Modern Language Association (MLA)
Su, Huayou…[et al.]. Efficient Parallel Video Processing Techniques on GPU: From Framework to Implementation. The Scientific World Journal No. 2014 (2014), pp.1-19.
https://search.emarefa.net/detail/BIM-1050733
American Medical Association (AMA)
Su, Huayou& Wen, Mei& Wu, Nan& Ren, Ju& Zhang, Chunyuan. Efficient Parallel Video Processing Techniques on GPU: From Framework to Implementation. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-19.
https://search.emarefa.net/detail/BIM-1050733
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1050733