Publication Date:
2017-12-16
Description:
Author(s): Chamika M. Liyanagedera, Abhronil Sengupta, Akhilesh Jaiswal, and Kaushik Roy Artificial neural networks built around nanoelectronic components are a means to realizing compact, energy-efficient cognitive intelligence. The authors use the inherent device physics of nanomagnets to emulate the computational primitives of a neural network, reducing the energy and area requirements of the underlying hardware. They analyze the performance of stochastic neuromorphic computing platforms with magnets of different barrier heights, and show how the core network architecture must be modified as the magnets scale down to the superparamagnetic regime. [Phys. Rev. Applied 8, 064017] Published Fri Dec 15, 2017
Electronic ISSN:
2331-7019
Topics:
Physics
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