Dynamic Task Remapping for Reliable CNN Training on ReRAM Crossbars

Chung-Hsuan Tung, Biresh Kumar Joardar, Partha Pratim Pande, Janardhan Rao Doppa, Hai Helen Li, Krishnendu Chakrabarty · 2023

A ReRAM crossbar-based computing system (RCS) can accelerate CNN training. However, hardware faults due to manufacturing defects and limited endurance impede the widespread adoption of RCS. We propose a dynamic task remapping-based technique for reliable CNN training on faulty RCS. Experimental results demonstrate that the proposed low-overhead method incurs only 0.85% accuracy loss on average while training popular CNNs such as VGGs, ResNets, and SqueezeNet with the CIFAR-IO, CIFAR-100, and SVHN datasets in the presence of faults.

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