In-Memory Logic Operations and Neuromorphic Computing in Non-Volatile Random Access Memory

Recent progress in the development of artificial intelligence technologies, aided by deep learning algorithms, has led to an unprecedented revolution in neuromorphic circuits, bringing us ever closer to brain-like computers. However, the vast majority of advanced algorithms still have to run on conv...

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Bibliographic Details
Published in:Materials Vol. 13; no. 16; p. 3532
Main Authors: Ou, Qiao-Feng, Xiong, Bang-Shu, Yu, Lei, Wen, Jing, Wang, Lei, Tong, Yi
Format: Journal Article
Language:English
Published: Basel MDPI AG 10.08.2020
MDPI
Subjects:
Algorithms
Artificial intelligence
Boolean algebra
Brain
Central processing units
Circuit design
CMOS
Computation
CPUs
Data storage
Electric fields
Energy consumption
Ferroelectricity
Graphene
Logic
Machine learning
Neuromorphic computing
Performance measurement
Random access memory
Review
Transistors
ISSN:1996-1944, 1996-1944
Online Access:Get full text
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Summary:Recent progress in the development of artificial intelligence technologies, aided by deep learning algorithms, has led to an unprecedented revolution in neuromorphic circuits, bringing us ever closer to brain-like computers. However, the vast majority of advanced algorithms still have to run on conventional computers. Thus, their capacities are limited by what is known as the von-Neumann bottleneck, where the central processing unit for data computation and the main memory for data storage are separated. Emerging forms of non-volatile random access memory, such as ferroelectric random access memory, phase-change random access memory, magnetic random access memory, and resistive random access memory, are widely considered to offer the best prospect of circumventing the von-Neumann bottleneck. This is due to their ability to merge storage and computational operations, such as Boolean logic. This paper reviews the most common kinds of non-volatile random access memory and their physical principles, together with their relative pros and cons when compared with conventional CMOS-based circuits (Complementary Metal Oxide Semiconductor). Their potential application to Boolean logic computation is then considered in terms of their working mechanism, circuit design and performance metrics. The paper concludes by envisaging the prospects offered by non-volatile devices for future brain-inspired and neuromorphic computation.
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ISSN:1996-1944
1996-1944
DOI:10.3390/ma13163532