Abstract

In sequential logic circuits the transient errors that occur in a particular time frame will propagate to consecutive time frames thereby making the device more vulnerable. In this work we propose a probabilistic error model for sequential logic that can measure the expected output error probability, given a probabilistic input space, that account for both spatial dependencies and temporal correlations across the logic, using a time evolving causal network. We demonstrate our error model using MCNC and ISCAS benchmark circuits and validate it with HSpice simulations. Our observations show that, significantly low individual gate error probabilities produce at least 5 fold higher output error probabilities. The average error percentage of our results with reference to HSpice simulation results is only 4.43%. Our observations show that the order of temporal dependency of error varies for different sequential circuits.

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