Impact of process variations on multicore performance symmetry
Proceedings of the conference on Design, automation and test in Europe
On process variation tolerant low cost thermal sensor design in 32nm CMOS technology
Proceedings of the 19th ACM Great Lakes symposium on VLSI
Accurate temperature estimation using noisy thermal sensors
Proceedings of the 46th Annual Design Automation Conference
Proceedings of the 20th symposium on Great lakes symposium on VLSI
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
SCC thermal model identification via advanced bias-compensated least-squares
Proceedings of the Conference on Design, Automation and Test in Europe
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
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Many-cores systems on chip provide the highest performance scaling potential due to the massive parallelism, but they suffer from thermal issues due to their high power densities. Thermal sensors and feedback strategies are used to reduce these threats but sensor accuracy directly impact control performance. In this paper we propose a novel technique to calibrate thermal sensors. Our approach can be applied to general multi-core platforms since it combines stress patterns and least-square fitting to perform thermal sensor characterization directly on the target device. We experimentally validate our approach on the Single Chip Cloud (SCC) prototype by Intel.