Energy-optimal dynamic thermal management: Computation and cooling power co-optimization

Donghwa Shin, Sung Woo Chung, Eui Young Chung, Naehyuck Chang

Research output: Contribution to journalArticlepeer-review

58 Citations (Scopus)


Conventional dynamic thermal management (DTM) assumes that the thermal resistance of a heat-sink is a given constant determined at design time. However, the thermal resistance of a common forced-convection heat sink is inversely proportional to the flow rate of the air or coolant at the expense of the cooling power consumption. The die temperature of the silicon devices strongly affects its leakage power consumption and reliability, and it can be changed by adjusting the thermal resistance of the cooling devices. Different from conventional DTM which aims to avoid the thermal emergency, our proposed DTM regards the thermal resistance of a forced-convection heat sink as a control variable, and minimize the total power consumption both for computation and cooling. We control the cooling power consumption together with the microprocessor clock frequency and supply voltage, and track the energy-optimal die temperature. Consequently, we reduce a significant amount of the temperature-dependent leakage power consumption of the microprocessor while spending a bit higher cooling power than conventional DTM, and eventually consume less total power. Experimental results show the proposed DTM saves up to 8.2% of the total energy compared with a baseline DTM approach. Our proposed DTM also enhances the Failures in Time (FIT) up to 80% in terms of the electromigration lifetime reliability.

Original languageEnglish
Article number5497141
Pages (from-to)340-351
Number of pages12
JournalIEEE Transactions on Industrial Informatics
Issue number3
Publication statusPublished - 2010 Aug


  • Dynamic thermal management (DTM)
  • heat sink
  • liquid cooling
  • reliability
  • temperature-dependent leakage power

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering


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