Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Compact thermal modeling for temperature-aware design
Proceedings of the 41st annual Design Automation Conference
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
The M5 Simulator: Modeling Networked Systems
IEEE Micro
Voltage-frequency island partitioning for GALS-based networks-on-chip
Proceedings of the 44th annual Design Automation Conference
Thousand core chips: a technology perspective
Proceedings of the 44th annual Design Automation Conference
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
Temperature management in multiprocessor SoCs using online learning
Proceedings of the 45th annual Design Automation Conference
TAPE: thermal-aware agent-based power economy for multi/many-core architectures
Proceedings of the 2009 International Conference on Computer-Aided Design
Utilizing predictors for efficient thermal management in multiprocessor SoCs
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Challenges and methodologies for efficient power budgeting across the die
Proceedings of the 20th symposium on Great lakes symposium on VLSI
Design and architectures for dependable embedded systems
CODES+ISSS '11 Proceedings of the seventh IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Mapping on multi/many-core systems: survey of current and emerging trends
Proceedings of the 50th Annual Design Automation Conference
Reliable on-chip systems in the nano-era: lessons learnt and future trends
Proceedings of the 50th Annual Design Automation Conference
Price theory based power management for heterogeneous multi-cores
Proceedings of the 19th international conference on Architectural support for programming languages and operating systems
Formal verification of distributed dynamic thermal management
Proceedings of the International Conference on Computer-Aided Design
| Hi-index | 0.00 |
One of the key challenges for multi-core processors in the nano-CMOS era is dealing with the increased temperatures. It is imperative that peak temperatures are reduced and that heat is spread as evenly on the chip as possible to avoid mutual heating and high thermal gradients between processor cores. Approaches have emerged which share a global power budget among multiple cores in order to meet these objectives. However, while these approaches act proactively in distributing power across the chip before thermal problems arise, changes in the respective strategies remain reactive to a temperature threshold. Our approach uses reinforcement learning in order to dynamically change what we call power trading strategies before thermal thresholds are hit based on past recorded observations. Through learning, our hierarchical approach is also able to distribute so-called multiple power budgets at once thereby making power trading more effective, reaching a decrease in peak temperatures of around 4 compared to a fully distributed approach - which can be critical at near-threshold temperatures in terms of transient errors - while also decreasing the number of deadline misses by a factor of 7. Our technique has been verified by deploying a thermal camera.