Energy-optimal dynamic thermal management for green computing

Existing thermal management systems for microprocessors assume that the thermal resistance of the heat-sink is constant and that the objective of the cooling system is simply to avoid thermal emergencies. But in fact the thermal resistance of the usual forced-convection heat-sink is inversely proportional to the fan speed, and a more rational objective is to minimize the total power consumption of both processor and cooling system. Our new method of dynamic thermal management uses both the fan speed and the voltage/frequency of the microprocessor as control variables. Experiments show that tracking the energy-optimal steady-state temperature can saves up to 17.6% of the overall energy, when compared with a conventional approach that merely avoids overheating.

[1]  Rajesh K. Gupta,et al.  Leakage aware dynamic voltage scaling for real-time embedded systems , 2004, Proceedings. 41st Design Automation Conference, 2004..

[2]  M. Yovanovich,et al.  Analytical forced convection modeling of plate fin heat sinks , 1999, Fifteenth Annual IEEE Semiconductor Thermal Measurement and Management Symposium (Cat. No.99CH36306).

[3]  Margaret Martonosi,et al.  Runtime Power Monitoring in High-End Processors: Methodology and Empirical Data , 2003, MICRO.

[4]  Li Shang,et al.  Accurate Temperature-Dependent Integrated Circuit Leakage Power Estimation is Easy , 2007, 2007 Design, Automation & Test in Europe Conference & Exhibition.

[5]  Frank Bellosa,et al.  Event-Driven Thermal Management in SMP Systems , 2005 .

[6]  Margaret Martonosi,et al.  Dynamic thermal management for high-performance microprocessors , 2001, Proceedings HPCA Seventh International Symposium on High-Performance Computer Architecture.

[7]  Kevin Skadron,et al.  HotSpot: a compact thermal modeling methodology for early-stage VLSI design , 2006, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[8]  Kevin Skadron,et al.  Control-theoretic techniques and thermal-RC modeling for accurate and localized dynamic thermal management , 2002, Proceedings Eighth International Symposium on High Performance Computer Architecture.

[9]  Karam S. Chatha,et al.  Approximation algorithm for the temperature-aware scheduling problem , 2007, 2007 IEEE/ACM International Conference on Computer-Aided Design.

[10]  Kevin Skadron,et al.  Using performance counters for runtime temperature sensing in high-performance processors , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[11]  Gang Qu,et al.  Temperature-Aware Leakage Minimization Technique for Real-Time Systems , 2006, 2006 IEEE/ACM International Conference on Computer Aided Design.

[12]  Lei He,et al.  Temperature and supply Voltage aware performance and power modeling at microarchitecture level , 2005, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[13]  Leee/acm International Conference On Computer-aided Design Digest Of Technical Papers , 1993, Proceedings of 1993 International Conference on Computer Aided Design (ICCAD).

[14]  R.J. Moffat.  Modeling Air-Cooled Heat Sinks as Heat Exchangers , 2007, Twenty-Third Annual IEEE Semiconductor Thermal Measurement and Management Symposium.

[15]  Margaret Martonosi,et al.  Wattch: a framework for architectural-level power analysis and optimizations , 2000, Proceedings of 27th International Symposium on Computer Architecture (IEEE Cat. No.RS00201).

[16]  Kevin Skadron,et al.  Accurate, Pre-RTL Temperature-Aware Design Using a Parameterized, Geometric Thermal Model , 2008, IEEE Transactions on Computers.

[17]  Sarita V. Adve,et al.  Predictive dynamic thermal management for multimedia applications , 2003, ICS '03.

[18]  Sarma B. K. Vrudhula,et al.  Performance optimal processor throttling under thermal constraints , 2007, CASES '07.

[19]  Shahin Nazarian,et al.  Thermal Modeling, Analysis, and Management in VLSI Circuits: Principles and Methods , 2006, Proceedings of the IEEE.