Learning-Based Power Management for Multicore Processors via Idle Period Manipulation

Learning-based dynamic power management (DPM) techniques, being able to adapt to varying system conditions and workloads, have attracted a lot of research attention recently. To the best of our knowledge, however, none of the existing learning-based DPM solutions are dedicated to power reduction in multicore processors, although they can be utilized by treating each processor core as a standalone entity and conducting DPM for them separately. In this paper, by including task allocation into our learning-based DPM framework for multicore processors, we are able to manipulate idle periods on processor cores to achieve a better tradeoff between power consumption and system performance. Experimental results show that the proposed solution significantly outperforms existing DPM techniques.

[1]  Saibal Mukhopadhyay,et al.  Leakage current mechanisms and leakage reduction techniques in deep-submicrometer CMOS circuits , 2003, Proc. IEEE.

[2]  Petru Eles,et al.  On-line thermal aware dynamic voltage scaling for energy optimization with frequency/temperature dependency consideration , 2009, 2009 46th ACM/IEEE Design Automation Conference.

[3]  Mani B. Srivastava,et al.  Predictive system shutdown and other architectural techniques for energy efficient programmable computation , 1996, IEEE Trans. Very Large Scale Integr. Syst..

[4]  Massoud Pedram,et al.  Supervised Learning Based Power Management for Multicore Processors , 2010, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[5]  Massoud Pedram,et al.  Minimizing the power consumption of a Chip Multiprocessor under an average throughput constraint , 2010, 2010 11th International Symposium on Quality Electronic Design (ISQED).

[6]  Evangeline F. Y. Young,et al.  Multivoltage Floorplan Design , 2010, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[7]  George Theocharous,et al.  Machine Learning for Adaptive Power Management , 2006 .

[8]  Massoud Pedram,et al.  Improving the Efficiency of Power Management Techniques by Using Bayesian Classification , 2008, 9th International Symposium on Quality Electronic Design (isqed 2008).

[9]  Margaret Martonosi,et al.  Techniques for Multicore Thermal Management: Classification and New Exploration , 2006, 33rd International Symposium on Computer Architecture (ISCA'06).

[10]  Chita R. Das,et al.  A Fast and Efficient Processor Allocation Scheme for Mesh-Connected Multicomputers , 2002, IEEE Trans. Computers.

[11]  Luca Benini,et al.  Dynamic power management for nonstationary service requests , 1999, Design, Automation and Test in Europe Conference and Exhibition, 1999. Proceedings (Cat. No. PR00078).

[12]  Luca Benini,et al.  Event-driven power management of portable systems , 1999, Proceedings 12th International Symposium on System Synthesis.

[13]  G. Dhiman,et al.  Dynamic Power Management Using Machine Learning , 2006, 2006 IEEE/ACM International Conference on Computer Aided Design.

[14]  Kevin Skadron,et al.  Temperature-aware microarchitecture: Modeling and implementation , 2004, TACO.

[15]  Margaret Martonosi,et al.  An Analysis of Efficient Multi-Core Global Power Management Policies: Maximizing Performance for a Given Power Budget , 2006, 2006 39th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO'06).

[16]  Kevin Skadron,et al.  Temperature-aware microarchitecture , 2003, ISCA '03.

[17]  Kishor S. Trivedi.  Probability and Statistics with Reliability, Queuing, and Computer Science Applications , 1984 .

[18]  Stephen R. Marsland,et al.  Machine Learning - An Algorithmic Perspective , 2009, Chapman and Hall / CRC machine learning and pattern recognition series.

[19]  Li Shang,et al.  Thermal vs Energy Optimization for DVFS-Enabled Processors in Embedded Systems , 2007, 8th International Symposium on Quality Electronic Design (ISQED'07).

[20]  Luca Benini,et al.  Policy optimization for dynamic power management , 1998, Proceedings 1998 Design and Automation Conference. 35th DAC. (Cat. No.98CH36175).

[21]  Wei Liu,et al.  Adaptive power management using reinforcement learning , 2009, 2009 IEEE/ACM International Conference on Computer-Aided Design - Digest of Technical Papers.

[22]  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.

[23]  Kevin Skadron,et al.  A Novel Software Solution for Localized Thermal Problems , 2006, ISPA.

[24]  Shin'ichiro Mutoh,et al.  1-V power supply high-speed digital circuit technology with multithreshold-voltage CMOS , 1995, IEEE J. Solid State Circuits.

[25]  Anna R. Karlin,et al.  Competitive randomized algorithms for non-uniform problems , 1990, SODA '90.

[26]  Resve A. Saleh,et al.  Application-Driven Voltage-Island Partitioning for Low-Power System-on-Chip Design , 2009, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[27]  Ron Kohavi,et al.  A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.

[28]  Diana Marculescu,et al.  Analysis of dynamic voltage/frequency scaling in chip-multiprocessors , 2007, Proceedings of the 2007 international symposium on Low power electronics and design (ISLPED '07).

[29]  Qinru Qiu,et al.  Dynamic thermal management for multimedia applications using machine learning , 2011, 2011 48th ACM/EDAC/IEEE Design Automation Conference (DAC).

[30]  Allen C.-H. Wu,et al.  A predictive system shutdown method for energy saving of event-driven computation , 1997, 1997 Proceedings of IEEE International Conference on Computer Aided Design (ICCAD).

[31]  Luca Benini,et al.  Optimization and Controlled Systems: A Case Study on Thermal Aware Workload Dispatching , 2012, AAAI.

[32]  Luca Benini,et al.  Dynamic power management using adaptive learning tree , 1999, 1999 IEEE/ACM International Conference on Computer-Aided Design. Digest of Technical Papers (Cat. No.99CH37051).

[33]  Carl W. Steinbach.  A Reinforcement-Learning Approach to Power Management , 2002 .