Wattch: a framework for architectural-level power analysis and optimizations
Proceedings of the 27th annual international symposium on Computer architecture
The Alpha 21264 Microprocessor Architecture
ICCD '98 Proceedings of the International Conference on Computer Design
Hybrid Architectural Dynamic Thermal Management
Proceedings of the conference on Design, automation and test in Europe - Volume 1
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
Systematic temperature sensor allocation and placement for microprocessors
Proceedings of the 43rd annual Design Automation Conference
A general framework for spatial correlation modeling in VLSI design
Proceedings of the 44th annual Design Automation Conference
Approximation algorithm for the temperature-aware scheduling problem
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Thermal monitoring mechanisms for chip multiprocessors
ACM Transactions on Architecture and Code Optimization (TACO)
Hotspot: acompact thermal modeling methodology for early-stage VLSI design
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Temperature and supply Voltage aware performance and power modeling at microarchitecture level
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Optimizing Thermal Sensor Allocation for Microprocessors
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Thermal monitoring of real processors: techniques for sensor allocation and full characterization
Proceedings of the 47th Design Automation Conference
Adaptive and autonomous thermal tracking for high performance computing systems
Proceedings of the 47th Design Automation Conference
Accurate direct and indirect on-chip temperature sensing for efficient dynamic thermal management
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems - Special section on the ACM IEEE international conference on formal methods and models for codesign (MEMOCODE) 2009
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
Proceedings of the 49th Annual Design Automation Conference
Collaborative calibration of on-chip thermal sensors using performance counters
Proceedings of the International Conference on Computer-Aided Design
Run-time probabilistic detection of miscalibrated thermal sensors in many-core systems
Proceedings of the Conference on Design, Automation and Test in Europe
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Elevated chip temperatures are true limiters to the scalability of computing systems. Excessive runtime thermal variations compromise the performance and reliability of integrated circuits. To address these thermal issues, state-of-the-art chips have integrated thermal sensors that monitor temperatures at a few selected die locations. These temperature measurements are then used by thermal management techniques to appropriately manage chip performance. Thermal sensors and their support circuitry incur design overheads, die area, and manufacturing costs. In this paper, we propose a new direction for full thermal characterization of integrated circuits based on spectral Fourier analysis techniques. Application of these techniques to temperature sensing is based on the observation that die temperature is simply a space-varying signal, and that space-varying signals are treated identically to time-varying signals in signal analysis. We utilize Nyquist-Shannon sampling theory to devise methods that can almost fully reconstruct the thermal status of an integrated circuit during runtime using a minimal number of thermal sensors. We propose methods that can handle uniform and non-uniform thermal sensor placements. We develop an extensive experimental setup and demonstrate the effectiveness of our methods by thermally characterizing a 16-core processor. Our method produces full thermal characterization with an average absolute error of 0.6% using a limited number of sensors.