SHE-MTJ based ReLU-max pooling functions for on-chip training of neural networks

SHE-MTJ based ReLU-max pooling functions for on-chip training of neural networks

We present a detailed investigation of various routes to optimize the power consumption of the spintronic-based devices for implementing rectified linear activation (ReLU) and max-pooling functions. We examine the influence of various spin Hall effect layers, and their input resistances on the power...

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Bibliographic Details
Main Authors:	Venkatesh Vadde, Bhaskaran Muralidharan, Abhishek Sharma
Format:	Article
Language:	English
Published:	AIP Publishing LLC 2024-02-01
Series:	AIP Advances
Online Access:	http://dx.doi.org/10.1063/9.0000685

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