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|Adaptive Power Blurring Techniques to Calculate IC Temperature Profile under Large Temperature Variations|
|Keywords: Temperature Distribution of ICs, Adaptive Power Blurring Method, Large Temperature Variation Effect|
|Power Blurring (PB) methods enable fast and accurate calculation of IC temperature profiles, through convolution of Power map of the device under investigation and a thermal mask (the impulse response of the system to a point heat source). Both static and transient distributions can be obtained. Extensions to 3D chips and to the inverse problem, i.e. estimating the power map from the temperature field, are available. So far however, the temperature dependence of the material parameters has been neglected. Temperature rises of 40-50°C on the chip will reduce the thermal conductivity of the silicon by 10-20%. In this work, we extend the PB approach to account for this effect. We propose two Adaptive Power Blurring (APB) techniques based on iterative procedures. In both techniques, the PB method provides an initial temperature distribution guess using room temperature Si thermal conductivity. The key difference between the two APB methods is the way thermal masks are selected from a look-up table. The first variant uses one single mask based on the average temperature increase in the silicon, while the second approach employs a different mask for each point to account for the spatial variation of the temperature and according non-uniform thermal conductivity. In either case, the new estimate of temperature profile is acquired from convolution of the thermal masks and IC Power map. These schemes are then applied iteratively until a final, self-consistent solution is reached. Good convergence is achieved in both techniques because PB method, proven to give quick and accurate temperature estimates, is used as initial guess. We will demonstrate that these APB techniques substantially improve the accuracy under high temperature rise regime, in particular for hot spots, while still being much faster than traditional FEM techniques. We will also provide a comparison between the two methods proposed here.|
|Amirkoushyar Ziabari, Student
University of California - Santa Cruz
Santa Cruz, CA