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Published, Version of Record (VoR)CC BY V4.0, Open
Journal article
Nonvolatile Memories in Spiking Neural Network Architectures: Current and Emerging Trends
Electronics (Basel), v 11(10), p1610
18 May 2022
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
A sustainable computing scenario demands more energy-efficient processors. Neuromorphic systems mimic biological functions by employing spiking neural networks for achieving brain-like efficiency, speed, adaptability, and intelligence. Current trends in neuromorphic technologies address the challenges of investigating novel materials, systems, and architectures for enabling high-integration and extreme low-power brain-inspired computing. This review collects the most recent trends in exploiting the physical properties of nonvolatile memory technologies for implementing efficient in-memory and in-device computing with spike-based neuromorphic architectures.
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Details
- Title
- Nonvolatile Memories in Spiking Neural Network Architectures: Current and Emerging Trends
- Creators
- M. Lakshmi VarshikaFederico CorradiAnup Das
- Publication Details
- Electronics (Basel), v 11(10), p1610
- Publisher
- MDPI
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000801954500001
- Scopus ID
- 2-s2.0-85130118319
- Other Identifier
- 991019238708404721
UN Sustainable Development Goals (SDGs)
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Information Systems
- Engineering, Electrical & Electronic
- Physics, Applied