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Title: Fine-grained task-level parallel and low power H.264 decoding in multi-core systems
Authors: Liu, Wenyang
Liu, Weichen
Li, Mengquan
Chen, Peng
Yang, Lei
Xiao, Chunhua
Ye, Yaoyao
Keywords: Engineering::Computer science and engineering
Issue Date: 2019
Source: Liu, W., Liu, W., Li, M., Chen, P., Yang, L., Xiao, C., & Ye, Y. (2018). Fine-grained task-level parallel and low power H.264 decoding in multi-core systems. Proceedings of 2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS), 307-314. doi:10.1109/PADSW.2018.8644865
Project: NAP M4082282
SUG M4082087
Abstract: In the past few years, the extinction of Moore's Law makes people reconsider the solutions for dealing with the low computing resource utilization of applications on multicore processor systems. However, making good use of computing resources in multi-core processors systems is not easy due to the differences between single-core and multi-core architecture. Nowadays short video apps like Instagram and Tik Tok have successfully caught people's eyes by fascinating short videos, typically just 10 to 30 seconds long, uploaded by the users of apps. And almost all of these videos are recorded by their mobile devices, which are typically HD (High Definition) or FHD (Full High Definition) videos, which prefer to be encoded/decoded by H.264/AVC rather then HEVC (High Efficiency Video Coding) on mobile devices in view of the energy consumption and decoding speed. How to dive the huge potential of the computing resource on multi-core mobile devices to speed up decoding these videos while consuming low energy, is a big challenge. In our previous work [1], a relatively simple parallel framework was proposed to implement a parallel H.264/ AV C decoder. This work further proposes a more detailed systematic task-level parallel framework, together with an energy saving strategy based on this framework, to research a new H.264/AVC decoder on multi-core processor systems. The proposed parallel method is composed of a set of rules to guide parallel software programming (PSPR) and a software parallelization framework (SPF). The PSPR is applied in pre-processing steps to address the potential issues limiting the inherent parallelism, and the SPF is applied to parallelize the original serial programs. After the parallelization is successfully deployed, DVFS technique would be applied to decrease the power dissipation based on the SPF. Results show that proposed solutions make a significant improvement in decoding speed of 32% at 720p, 27% at 1080p and 29% at 2160p, and in energy savings o...
ISBN: 978-1-5386-7308-9
DOI: 10.1109/PADSW.2018.8644865
Rights: © 2018 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Conference Papers

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