Using and combining predictors that specialize
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Task scheduling and voltage selection for energy minimization
Proceedings of the 39th annual Design Automation Conference
Temperature-aware microarchitecture
Proceedings of the 30th annual international symposium on Computer architecture
Full chip leakage estimation considering power supply and temperature variations
Proceedings of the 2003 international symposium on Low power electronics and design
The Case for Lifetime Reliability-Aware Microprocessors
Proceedings of the 31st annual international symposium on Computer architecture
Heat-and-run: leveraging SMT and CMP to manage power density through the operating system
ASPLOS XI Proceedings of the 11th international conference on Architectural support for programming languages and operating systems
Proceedings of the conference on Design, automation and test in Europe: Proceedings
Techniques for Multicore Thermal Management: Classification and New Exploration
Proceedings of the 33rd annual international symposium on Computer Architecture
HybDTM: a coordinated hardware-software approach for dynamic thermal management
Proceedings of the 43rd annual Design Automation Conference
Temperature aware task scheduling in MPSoCs
Proceedings of the conference on Design, automation and test in Europe
Power and reliability management of SoCs
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Modeling and analysis of nonuniform substrate temperature effects on global ULSI interconnects
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
TAPE: thermal-aware agent-based power economy for multi/many-core architectures
Proceedings of the 2009 International Conference on Computer-Aided Design
Online convex optimization-based algorithm for thermal management of MPSoCs
Proceedings of the 20th symposium on Great lakes symposium on VLSI
Exploiting power budgeting in thermal-aware dynamic placement for reconfigurable systems
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
Dynamic thermal management for single and multicore processors under soft thermal constraints
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
Economic learning for thermal-aware power budgeting in many-core architectures
CODES+ISSS '11 Proceedings of the seventh IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Convex-based thermal management for 3D MPSoCs using DVFS and variable-flow liquid cooling
PATMOS'11 Proceedings of the 21st international conference on Integrated circuit and system design: power and timing modeling, optimization, and simulation
Recent thermal management techniques for microprocessors
ACM Computing Surveys (CSUR)
Integration, the VLSI Journal
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
Achieving autonomous power management using reinforcement learning
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Cooperative boosting: needy versus greedy power management
Proceedings of the 40th Annual International Symposium on Computer Architecture
Mapping on multi/many-core systems: survey of current and emerging trends
Proceedings of the 50th Annual Design Automation Conference
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In deep submicron circuits, thermal hot spots and high temperature gradients increase the cooling costs, and degrade reliability and performance. In this paper, we propose a low-cost temperature management strategy for multicore systems to reduce the adverse effects of hot spots and temperature variations. Our technique utilizes online learning to select the best policy for the current workload characteristics among a given set of expert policies. We achieve 20% and 60% average decrease in the frequency of hot spots and thermal cycles respectively in comparison to the best performing expert, and reduce the spatial gradients to below 5%.