Device Variation Effects on Neural Network Inference Accuracy in Analog In‐Memory Computing Systems

In analog in‐memory computing systems based on nonvolatile memories such as resistive random‐access memory (RRAM), neural network models are often trained offline and then the weights are programmed onto memory devices as conductance values. The programmed weight values inevitably deviate from the t...

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Bibliographic Details

Published in:	Advanced Intelligent Systems
Main Authors:	Qiwen Wang, Yongmo Park, Wei D. Lu
Format:	Article
Language:	English
Published:	Wiley 2022-08-01
Subjects:	analog computing deep neural networks emerging memory in-memory computing process-in-memory RRAM
Online Access:	https://doi.org/10.1002/aisy.202100199