A Collaborative Scheduling-Based Parallel Solution for HEVC Encoding on Multicore Platforms

Hanli WANG, Bo XIAO, Jun WU, Sam KWONG, C.-C. Jay KUO

Research output: Journal PublicationsJournal Article (refereed)peer-review

10 Citations (Scopus)


In order to meet the high computational demand to achieve superior coding efficiency and to explore the parallelism of parallel processing architectures, the emerging High Efficiency Video Coding (HEVC) standard has been designed to be more parallelizable than previous video coding standards. However, it is still desirable to design an efficient parallel HEVC encoder to fully exploit the parallelism of the increasingly powerful multicore platforms, especially when considering the amount of parallelism, the scalability of parallelization and the coding efficiency. In this work, a performance model of HEVC encoding is firstly introduced to investigate the speedup and the limitations of the technique of Wavefront Parallel Processing (WPP) under various conditions. Then, a Collaborative Scheduling-based Parallel Solution (CSPS) for HEVC encoding is proposed, which includes adaptive parallel mode decision, asynchronous frame-level pixel interpolation and multi-grained task scheduling. The goal of the proposed CSPS aims to defeat the disadvantages of WPP and further improve the parallelization of HEVC encoding on multicore platforms. Extensive experimental results demonstrate the efficiency of the proposed CSPS for parallelizing HEVC encoding as the computing resources of multicore architectures can be fully utilized.
Original languageEnglish
Pages (from-to)2935-2948
JournalIEEE Transactions on Multimedia
Issue number11
Early online date27 Apr 2018
Publication statusPublished - Nov 2018
Externally publishedYes

Bibliographical note

This work was supported in part by the National Natural Science Foundation of China under Grants 61622115 and 61472281, in part by the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning (No. GZ2015005), in part by the Shanghai Engineering Research Center of Industrial Vision Perception and Intelligent Computing (17DZ2251600), and in part by the IBM Shared University Research Awards Program.


  • collaborative scheduling
  • High efficiency video coding
  • multicore platform
  • parallelization scalability
  • wavefront parallel processing


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