Temperature-aware microarchitecture
Proceedings of the 30th annual international symposium on Computer architecture
HPCA '02 Proceedings of the 8th International Symposium on High-Performance Computer Architecture
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RTSS '04 Proceedings of the 25th IEEE International Real-Time Systems Symposium
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Speed scaling to manage energy and temperature
Journal of the ACM (JACM)
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ISQED '07 Proceedings of the 8th International Symposium on Quality Electronic Design
Approximation algorithm for the temperature-aware scheduling problem
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Guaranteed scheduling for repetitive hard real-time tasks under the maximal temperature constraint
CODES+ISSS '08 Proceedings of the 6th IEEE/ACM/IFIP international conference on Hardware/Software codesign and system synthesis
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RTAS '09 Proceedings of the 2009 15th IEEE Symposium on Real-Time and Embedded Technology and Applications
Proactive Speed Scheduling for Real-Time Tasks under Thermal Constraints
RTAS '09 Proceedings of the 2009 15th IEEE Symposium on Real-Time and Embedded Technology and Applications
Proceedings of the 46th Annual Design Automation Conference
Temperature and supply Voltage aware performance and power modeling at microarchitecture level
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Leakage conscious DVS scheduling for peak temperature minimization
Proceedings of the 16th Asia and South Pacific Design Automation Conference
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Thermal management problem has become a prominent issue as power consumption continues to grow exponentially. The leakage/temperature dependency becomes critical in power and thermal aware design as the processor continues to evolve into the the deep sub-micron domain. This paper seeks to explore fundamental principles in thermal aware design when taking the leakage/temperature dependency into considerations. We show and formally prove that, under certain realistic conditions, using the lowest constant processor speed that can guarantee deadlines of all real-time tasks is an optimal method to minimize the maximal temperature for a real-time system. We also use empirical results to justify the validation of this conclusion. We then discuss the possible future extension of this work.