Abstract
Soft errors due to cosmic radiations are the main reliability threat during lifetime operation of digital systems. Fast and accurate estimation of soft error rate (SER) is essential in obtaining the reliability parameters of a digital system in order to balance reliability, performance, and cost of the system. Previous techniques for SER estimation are mainly based on fault injection and random simulations. In this paper, we present an analytical SER modeling technique for ASIC designs that can significantly reduce SER estimation time while achieving very high accuracy. This technique can be used for both combinational and sequential circuits. We also present an approach to obtain uncertainty bounds on estimated error propagation probability (EPP) values used in our SER modeling framework. Comparison of this method with the Monte-Carlo fault injection and simulation approach confirms the accuracy and speed-up of the presented technique for both the computed EPP values and uncertainty bounds. Based on our SER estimation framework, we also present efficient soft error hardening techniques based on selective gate resizing to maximize soft error suppression for the entire logic-level design while minimizing area and delay penalties. Experimental results confirm that these techniques are able to significantly reduce soft error rate with modest area and delay overhead.
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