HybDTM: a coordinated hardware-software approach for dynamic thermal management
Proceedings of the 43rd annual Design Automation Conference
Complexity-based program phase analysis and classification
Proceedings of the 15th international conference on Parallel architectures and compilation techniques
Proceedings of the 39th Annual IEEE/ACM International Symposium on Microarchitecture
Physical aware frequency selection for dynamic thermal management in multi-core systems
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
Efficient power modeling and software thermal sensing for runtime temperature monitoring
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Analysis of dynamic voltage/frequency scaling in chip-multiprocessors
ISLPED '07 Proceedings of the 2007 international symposium on Low power electronics and design
Predictive dynamic thermal management for multicore systems
Proceedings of the 45th annual Design Automation Conference
Hybrid dynamic thermal management based on statistical characteristics of multimedia applications
Proceedings of the 13th international symposium on Low power electronics and design
Discovering and Exploiting Program Phases
IEEE Micro
Proactive temperature balancing for low cost thermal management in MPSoCs
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
A control theory approach for thermal balancing of MPSoC
Proceedings of the 2009 Asia and South Pacific Design Automation Conference
Temperature-constrained power control for chip multiprocessors with online model estimation
Proceedings of the 36th annual international symposium on Computer architecture
Predictive Temperature-Aware DVFS
IEEE Transactions on Computers
Utilizing predictors for efficient thermal management in multiprocessor SoCs
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Consistent runtime thermal prediction and control through workload phase detection
Proceedings of the 47th Design Automation Conference
Energy-efficient variable-flow liquid cooling in 3D stacked architectures
Proceedings of the Conference on Design, Automation and Test in Europe
Fast thermal simulation of 2D/3D integrated circuits exploiting neural networks and GPUs
Proceedings of the 17th IEEE/ACM international symposium on Low-power electronics and design
System-Level Dynamic Thermal Management for High-Performance Microprocessors
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Energy-Efficient Multiobjective Thermal Control for Liquid-Cooled 3-D Stacked Architectures
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IEEE Transactions on Parallel and Distributed Systems
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Elevated die temperature is a true limiter to the scalability of modern processors. With continued technology scaling in order to meet ever-increasing performance demands, it is no longer cost effective to design cooling systems that handle the worst-case thermal behaviors. Instead, cooling systems are designed to handle typical chip operation, while processors must detect and handle rare thermal emergencies. Most processors rely on measurements from integrated thermal sensors and dynamic thermal management (DTM) techniques in order to manage the trade-off between performance and thermal risk. Optimal management requires advanced knowledge of the thermal trajectory based on the current workload behaviors and operating conditions. In this work, we devise novel workload phase classification strategies that automatically discriminate among workload behaviors with respect to the thermal control response. We incorporate workload phase-detection and thermal models into a dynamic voltage and frequency scaling (DVFS) technique that can optimally control temperature during runtime based on thermal predictions. We demonstrate the effectiveness of our proposed techniques in predicting and adaptively controlling the thermal behavior of a real quad-core processor in response to a wide range of workloads. In comparison with state-of-the-art model predictive control (MPC) techniques in previous works on thermal prediction, we demonstrate a 5.8% improvement in instruction throughput with the same number of thermal violations. In comparison with simple proportional-integral (PI) feedback control techniques, we improve instruction throughput by 3.9%, while significantly reducing the number of thermal violations.