Temperature Sensor Distribution, Measurement Uncertainty, and Data Interpretation for Microprocessor Hotspots

Miler, J., Etessam-Yazdani, K., Asheghi, M., Touzelbaev, M., and Goodson, K.E., 2012, "Temperature Sensor Distribution, Measurement Uncertainty, and Data Interpretation for Microprocessor Hotspots,"  IEEE Transactions on Components, Packaging, and Manufacturing Technology, under review.

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Microprocessor hotspots are a major reliability concern with heat fluxes as much as 20 times greater than those found elsewhere on the chip. Chip hotspots also augment thermo-mechanical stress at chip-package interfaces which can lead to failure during cycling. Because highly localized, transient chip cooling is both technically challenging and costly, chip manufacturers are using dynamic thermal management (DTM) techniques that reduce hotspots by throttling chip power. While much attention has focused on methods for throttling power, relatively little research has considered the uncertainty inherent in measuring hotspots. The current work introduces a method to determine the accuracy and resolution at which the hotspot heat flux profile can be measured using distributed temperature sensors. The model is based on a novel, computationally-efficient, inverse heat transfer solution. The uncertainties in the hotspot location and intensity are computed for randomized chip heat flux profiles for varying sensor spacing, sensor vertical proximity, sensor error, and chip thermal properties. For certain cases the inverse solution method decreases mean absolute error in the heat flux profile by more than 30%. These results and simulation methods can be used to determine the optimal spacing of distributed temperature sensor arrays for hotspot management in chips.

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