Fine-Grained Task-Level Parallel and Low Power H.264 Decoding in Multi-Core Systems

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 of 25% at 720p, 25% at 1080p and 23% at 2160p on a four-core workstation running Linux, compared to the original serial H.264/ AV C decoder. The results demonstrate our methods are effective and scalable, served as a reference for future parallel software development.