LOW-OVERHEAD ERROR PREDICTION AND PREEMPTION IN DEEP NEURAL NETWORK USING APRIORI NETWORK STATISTICS
Abstract:
A coarse error correction system for detecting, predicting, and correcting errors in neural networks is provided. The coarse error correction system receives a first set of statistics that are computed from values collected from a neural network during a training phase of the neural network. The coarse error correction system computes a second set of statistics based on values collected from the neural network during a run-time phase of the neural network. The coarse error correction system detects an error in the neural network during the run-time phase of the neural network by comparing the first set of statistics with the second set of statistics. The coarse error correction system increases a voltage setting to the neural network based on the detected error.
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