Dynamic Thermal Management for High-Performance Microprocessors
HPCA '01 Proceedings of the 7th International Symposium on High-Performance Computer Architecture
HPCA '02 Proceedings of the 8th International Symposium on High-Performance Computer Architecture
Adaptive multi-domain thermal modeling and analysis for integrated circuit synthesis and design
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
A stochastic local hot spot alerting technique
Proceedings of the 2008 Asia and South Pacific Design Automation Conference
Proactive temperature management in MPSoCs
Proceedings of the 13th international symposium on Low power electronics and design
Accurate Temperature Estimation for Efficient Thermal Management
ISQED '08 Proceedings of the 9th international symposium on Quality Electronic Design
Accurate temperature estimation using noisy thermal sensors
Proceedings of the 46th Annual Design Automation Conference
Spectral techniques for high-resolution thermal characterization with limited sensor data
Proceedings of the 46th Annual Design Automation Conference
Full-chip runtime error-tolerant thermal estimation and prediction for practical thermal management
Proceedings of the International Conference on Computer-Aided Design
Proceedings of the 49th Annual Design Automation Conference
Online thermal control methods for multiprocessor systems
ACM Transactions on Design Automation of Electronic Systems (TODAES) - Special section on adaptive power management for energy and temperature-aware computing systems
Collaborative calibration of on-chip thermal sensors using performance counters
Proceedings of the International Conference on Computer-Aided Design
Temperature tracking: an innovative run-time approach for hardware Trojan detection
Proceedings of the International Conference on Computer-Aided Design
Unified reliability estimation and management of NoC based chip multiprocessors
Microprocessors & Microsystems
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Many DTM schemes rely heavily on the accurate knowledge of the chip's dynamic thermal state to make optimal performance/temperature trade-off decisions. This information is typically generated using a combination of thermal sensor inputs and various estimation schemes such as Kalman filter. A basic assumption used by such schemes is that the statistical characteristics of the power consumption do not change. This is problematic since such characteristics are heavily application dependent. In this paper, we first present autonomous schemes for detecting the change in the statistical characteristics of power and then propose adaptive schemes for capturing such new statistical parameters dynamically. This could enable accurate temperature estimation during runtime given dynamically changing power statistical states. Our schemes use a combination of hypothesis testing and residual whitening methods and can improve the accuracy by 67% as compared to the traditional non-adaptive schemes.