Power-Efficient Workload Balancing for Video Applications

Muhammad Usman Karim Khan, Muhammad Shafique, Jorg Henkel

Research output: Contribution to journalArticlepeer-review


High workload and throughput requirements of image and video processing applications can be sustained on a many-core system. However, inefficient parallelization and processing assignments to the cores result in reduced system efficiency. Eliminating them necessitates a power-efficient and balanced workload distribution among the cores. This paper addresses these challenges by introducing a novel workload-balancing and adaptation scheme. Our scheme accounts for the application characteristics and the underlying hardware, and the variation of load. Automatic selection of the number of cores and distribution of workload to each core depends on the throughput requirements, available number of cores, allowable voltage-frequency settings, and data content. Moreover, runtime derivation and fine-tuning of the workload-dependent frequency estimation models of each core are achieved using a closed-loop feedback mechanism. Furthermore, we propose an optional feedback control-based workload-tuning scheme that can further reduce the total power consumption. A case study of an advanced multithreaded video application demonstrates up to ∼ 42 % power savings (average ∼ 39%) with negligible video quality degradation, using our proposed power-efficient workload-balancing and tuning.

Original languageEnglish (US)
Article number7362225
Pages (from-to)2089-2102
Number of pages14
JournalIEEE Transactions on Very Large Scale Integration (VLSI) Systems
Issue number6
StatePublished - Jun 2016


  • Dynamic voltage frequency scaling
  • many core
  • multithreading
  • parallel High Efficiency Video Coding (HEVC)
  • power efficiency
  • resource allocation
  • video processing
  • Workload balancing

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Electrical and Electronic Engineering


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