Wattch: a framework for architectural-level power analysis and optimizations
Proceedings of the 27th annual international symposium on Computer architecture
Temperature-aware microarchitecture
Proceedings of the 30th annual international symposium on Computer architecture
Algorithmic problems in power management
ACM SIGACT News
Exploring "temperature-aware" design in low-power MPSoCs
Proceedings of the conference on Design, automation and test in Europe: Proceedings
Techniques for Multicore Thermal Management: Classification and New Exploration
Proceedings of the 33rd annual international symposium on Computer Architecture
Journal of VLSI Signal Processing Systems
Temperature aware task scheduling in MPSoCs
Proceedings of the conference on Design, automation and test in Europe
Thermal-aware scheduling for future chip multiprocessors
EURASIP Journal on Embedded Systems
Temperature-aware processor frequency assignment for MPSoCs using convex optimization
CODES+ISSS '07 Proceedings of the 5th IEEE/ACM international conference on Hardware/software codesign and system synthesis
Approximation algorithm for the temperature-aware scheduling problem
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Temperature-aware scheduling and assignment for hard real-time applications on MPSoCs
Proceedings of the conference on Design, automation and test in Europe
Power agnostic technique for efficient temperature estimation of multicore embedded systems
Proceedings of the 2012 international conference on Compilers, architectures and synthesis for embedded systems
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Thermal aware scheduling(TAS) is an important system level optimization for CMP and MPSoC. An event driven thermal estimation method which can assist dynamic TAS is proposed in this paper. The event driven thermal estimation is based upon a thermal map which is updated only when a high level event occurs. To minimize the overhead, while maintaining the estimation accuracy, the prebuilt look-up-tables and the superposition principle are used to speed up the solution of the thermal RC network. Experimental results show our method is accurate, producing thermal estimations of similar quality to existing thermal simulators, while having a considerably reduced computational complexity. Our event driven thermal estimation technique is significantly better, in terms of accuracy, than existing TAS schedulers, making it highly suitable for integration into the OS kernel.