基于最大误差的热传感器数量分配方法

上海交通大学学报（自然版） ›› 2013, Vol. 47 ›› Issue (04): 626-629.

• 自动化技术、计算机技术 • 上一篇下一篇

基于最大误差的热传感器数量分配方法

邱赓，李鑫，戎蒙恬，刘涛

（上海交通大学电子信息与电气工程学院，上海 200240）

收稿日期:2012-04-10 出版日期:2013-04-28 发布日期:2013-04-28
基金资助:
国家重点基础研究发展规划（973）项目（2009CB320206），国家自然科学基金委创新研究群体（60821062）

Sensor Allocation Based on the Maximum Error in Thermal Monitoring for Microprocessors

QIU Geng, LI Xin, RONG Meng-Tian, LIU Tao

(School of Electronic, Information and Electrical Engineering， Shanghai Jiaotong University，Shanghai 200240， China)

Received:2012-04-10 Online:2013-04-28 Published:2013-04-28

摘要/Abstract

摘要： 为了更好地监控微处理器的运行温度，提出了一种考虑奇异点的改进聚类求解策略和新颖的热传感器数量分配方案.该方案分析了在给定最大热点监控误差下所需要的热传感器数量，并且在满足工程上所需要求的情况下，使热传感器数量尽可能地少.实验结果表明，所提出的方法能够在广泛应用的微处理器架构上计算出给定误差要求下所需的热传感器数量，并且与现有的k-means聚类算法相比，所使用的传感器数量明显减少.

关键词: 双重聚类, 热点监控, 热传感器, 分配数量

Abstract: A new singular value-awared method of solving and sensor allocation strategy were proposed for the temperature sensors embedded in microprocessors as to monitor the thermal behavior. The strategy discussed how many temperature sensors we need at least to satisfy the max error to be allowed by using of improved dual clustering algorithm. The experimental results indicate the superiority of the technique and confirm that it can calculate the minimum number of sensors with the max error allowed in widely used microprocessor architecture. Much less sensors are used compared with the k-means cluster algorithm.

Key words: dual clustering, thermal monitoring, temperature sensor, allocation

中图分类号:

TP 212

邱赓, 李鑫, 戎蒙恬, 刘涛. 基于最大误差的热传感器数量分配方法[J]. 上海交通大学学报（自然版）, 2013, 47(04): 626-629.

QIU Geng, LI Xin, RONG Meng-Tian, LIU Tao. Sensor Allocation Based on the Maximum Error in Thermal Monitoring for Microprocessors [J]. Journal of Shanghai Jiaotong University, 2013, 47(04): 626-629.

参考文献

［1］Lin S C, Banerjee K. Cool chips: Opportunities and implications for power and thermal management ［J］. IEEE Transactions on Electron Devices, 2008, 55(1):245255.
［2］Jayaseelan R, Mitra T. Dynamic thermal management via architectural adaptation ［C］∥ Proceedings of the 46th Design Automation Conference. New York: ACM, 2009: 484489.
［3］Coskun A K, Rosing T S, Gross K C. Proactive temperature management in MPSoCs ［C］∥ International Symposium on Low Power Electronics and Design. New York: ACM, 2008: 213218.［4］Ryan C, Sherief R. Spectral techniques for highresolution thermal characterization with limited sensor data ［C］∥ Proceedings of ACM/IEEE Design Automation Conference. New York: ACM, 2009: 478483.
［5］Abdullah N N, Ryan C, Sherief R. Thermal monitoring of real processors: Techniques for sensor allocation and full characterization ［C］∥ Proceedings of the 47th Design Automation Conference. New York: ACM, 2010: 5661.
［6］Li X, Rong M, Liu T, et al. Inverse distance weighting method based on a dynamic voronoi diagram for thermal reconstruction with limited sensor data on multiprocessors ［J］. IEICE Transactions on Electronics, 2011, E94C(8): 12951301.
［7］Mukherjee R, Memik S O. Systematic temperature sensor allocation and placement for microprocessors ［C］∥ 43rd Design Automation Conference. New York: ACM, 2006: 542547.
［8］Memik S O, Mukherjee R. Optimizing thermal sensor allocation for microprocessors ［J］. IEEE Transactions on ComputerAided Design of Integrated Circuits，2008, 27(3): 516527.
［9］Long J, Memik S O, Memik G, et al. Thermal monitoring mechanisms for chip multiprocessors ［J］. ACM Transactions on Architecture and Code Optimization, 2008, 5(2): 9:19:33.
［10］Lin C R, Liu K H , Chen M S. Dual clustering: Integrating data clustering over optimization and constraint domains ［J］. IEEE Trans Knowledge and Data Engineering, 2005, 17(5): 628637.

基于最大误差的热传感器数量分配方法

Sensor Allocation Based on the Maximum Error in Thermal Monitoring for Microprocessors

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics

本文评价