Distributed task migration for thermal management in many-core systems

Yang Ge, Parth Malani, Qinru Qiu

Research output: Chapter in Book/Entry/PoemConference contribution

100 Scopus citations


In the deep submicron era, thermal hot spots and large temperature gradients significantly impact system reliability, performance, cost and leakage power. As the system complexity increases, it is more and more difficult to perform thermal management in a centralized manner because of state explosion and the overhead of monitoring the entire chip. In this paper, we propose a framework for distributed thermal management for many-core systems where balanced thermal profile can be achieved by proactive task migration among neighboring cores. The framework has a low cost agent residing in each core that observes the local workload and temperature and communicates with its nearest neighbor for task migration/exchange. By choosing only those migration requests that will result balanced workload without generating thermal emergency, the proposed framework maintains workload balance across the system and avoids unnecessary migration. Experimental results show that, compared with existing proactive task migration technique, our approach generates less hotspots and smoother thermal gradient with less migration overhead and higher processing throughput

Original languageEnglish (US)
Title of host publicationProceedings of the 47th Design Automation Conference, DAC '10
Number of pages6
StatePublished - 2010
Externally publishedYes
Event47th Design Automation Conference, DAC '10 - Anaheim, CA, United States
Duration: Jun 13 2010Jun 18 2010

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X


Other47th Design Automation Conference, DAC '10
Country/TerritoryUnited States
CityAnaheim, CA


  • Distributed control
  • Dynamic thermal management
  • Prediction

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation


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