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Synaptic electronics and neuromorphic computing
Science China Information Sciences, 2016In order to map the computing architecture and intelligent functions of the human brain on hardware, we need electronic devices that can emulate biological synapses and even neurons, preferably at the physical level. Beginning with the history of neuromorphic computation, in this article, we will briefly review the architecture of the brain and the ...
Navnidhi K. Upadhyay +2 more
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A VLSI Design for Neuromorphic Computing
2016 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 2016Dynamic Adaptive Neural Network Arrays (DANNAs) are neuromorphic systems that exhibit spiking behaviors and can be designed using evolutionary optimization. Array elements are rapidly reconfigurable and can function as either neurons, synapses or fan-out elements with programmable interconnections and parameters. Currently, DANNAs are implemented using
Mark E. Dean, Christopher Daffron
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Neuromorphic computing with memristive devices
Science China Information Sciences, 2018Technology advances in the last a few decades have resulted in profound changes in our society, from workplaces to living rooms to how we socialize with each other. These changes in turn drive further technology developments, as the exponential growth of data demands ever increasing computing power.
Wen Ma, Mohammed Affan Zidan, Wei D. Lu
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VCSEL Based Neuromorphic Computing
2023 Optical Fiber Communications Conference and Exhibition (OFC), 2023We report on Vertical-Cavity Surface-Emitting Lasers (VCSELs) for high-speed and energy-efficiency systems for photonic neuromorphic computing, yielding excellent performance in complex processing tasks whilst benefitting from hardware-friendly implementations and full compatibility with optical communication technologies.
Dafydd Owen-Newns +3 more
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Neuromorphic sensory computing
Science China Information Sciences, 2021Tianqing Wan +4 more
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A study on neuromorphic quantum computation
2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541), 2005A quantum computer employing a single quantum as a qubit executes real parallel computation. Several algorithms have been proposed for quantum computation. However, these algorithms are applicable only to a limited number of applications. Therefore, a general purpose algorithm should be studied and developed for practical use in the near future.
Shigeo Sato +4 more
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Benchmarks for progress in neuromorphic computing
Nature Machine Intelligence, 2019In order for the neuromorphic research field to advance into the mainstream of computing, it needs to start quantifying gains, standardize on benchmarks and focus on feasible application challenges.
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Technology considerations for neuromorphic computing
2016 IEEE International Conference on Rebooting Computing (ICRC), 2016The use of neural nets has been growing rapidly. A variety of computing architectures, such as CPUs, GPUs, FPGAs, and analog designs have been proposed. This paper will explore how technology options affect design choices, using both digital and analog circuit designs suitable for neural nets.
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Reconfigurable Neuromorphic Computing: Materials, Devices, and Integration
Advanced Materials, 2023Minyi Xu, Cui Yi, Xianfu Wang
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2D Material Based Synaptic Devices for Neuromorphic Computing
Advanced Functional Materials, 2021Chao Zhu, Fucai Liu, Zheng Liu
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