Supervised Learning Based Model for Predicting Variability-Induced Timing Errors

Provided by: Institute of Electrical & Electronic Engineers
Topic: Hardware
Format: PDF
Circuit designers typically combat variations in hardware and workload by increasing conservative guardbanding that leads to operational inefficiency. Reducing this excessive guardband is highly desirable, but causes timing errors in synchronous circuits. The authors propose a methodology for supervised learning based models to predict timing errors at bit-level. They show that a logistic regression based model can effectively predict timing errors, for a given amount of guardband reduction. The proposed methodology enables a model-based rule method to reduce guardband subject to a required bit-level reliability specification.

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