Reconfigurable and Efficient Implementation of 16 Boolean Logics and Full‐Adder Functions with Memristor Crossbar for Beyond von Neumann In‐Memory Computing
Source abstract
Abstract
Abstract The rise of emerging technologies such as Big Data, the Internet of Things, and artificial intelligence, which requires efficient power schemes, is driving brainstorming in data computing and storage technologies. In this study, merely relying on the fundamental structure of two memristors and a resistor, arbitrary Boolean logic can be reconfigured and calculated in two steps, while no additional voltage sources are needed beyond “±VP” and 0, and all state reversals are based on memristor set switching. Utilizing the proposed logic scheme in an elegant form of unity structure and minimum cost, the implementation of a 1‐bit adder is demonstrated economically, and a promising circuit scheme for the N‐bit adder is exhibited. Some critical issues including the crosstalk problem, energy consumption, and peripheral circuits are further simulated and discussed. Compared with existing works on memristive logic, such methods support building a memristor‐based digital in‐memory calculation system with high functional reconfigurability, simple voltage sources, and low power and area consumption.
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Research context
OpenAlex topics: Advanced Memory and Neural Computing · Neuroscience and Neural Engineering · Photoreceptor and optogenetics research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan 430074 China
Hubei Yangtze Memory Laboratories Wuhan 430205 China
School of Integrated Circuits Huazhong University of Science and Technology Wuhan 430074 China
Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan 430074 China
Funding
National Natural Science Foundation of China
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