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Abstract: Fast, accurate, and detailed Soft Error Rate (SER) estimation of digital circuits is essential for cost-efficient reliable design. A major step to accurately estimate a circuit SER is the computation of failure probability, which requires the computation of three derating factors, namely logical, electrical, and timing derating. The unified treatment of these derating factors is crucial to obtain accurate failure probability. Existing SER estimation techniques are either unscalable to large circuits or inaccurate due to lack of unified treatment of all derating factors. In this paper, we present fast and efficient algorithms to estimate SERs of circuit components in the presence of single event transients by unified computation of all derating factors. The proposed algorithms, based on propagation of error probabilities and shape of erroneous waveforms, are scalable to very large circuits. The experimental results and comparisons with Statistical Fault Injections (SFIs) using Monte-Carlo simulations confirm the accuracy (only 2% difference) and speedup (5–6 orders of magnitudes) of the proposed technique. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]

Highlights: [•] Our RAP model enables systematic CMOS fault abstraction and error propagation. [•] RAP assumes that physically induced faults eventually manifest as bit flips. [•] Higher layer error models can be derived from probabilistic bit flip functions. [•] SoC designers can optimize system resilience across multiple abstraction levels. [•] Real-world case studies with SRAM soft-errors in CPU cache and MIMO detector are shown. [Copyright &y& Elsevier]