Monolithic 3D neuromorphic computing system with hybrid CMOS and memristor-based synapses and neurons
| Autor: | Zhen Zhou, Fangyang Shen, Yang Yi, Hongyu An, M. Amimul Ehsan |
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| Rok vydání: | 2019 |
| Předmět: |
Computer science
020208 electrical & electronic engineering 02 engineering and technology Integrated circuit Memristor 020202 computer hardware & architecture law.invention Analog signal CMOS Neuromorphic engineering Hardware and Architecture law 0202 electrical engineering electronic engineering information engineering Electronic engineering Waveform Equivalent circuit Electrical and Electronic Engineering Massively parallel Software |
| Zdroj: | Integration. 65:273-281 |
| ISSN: | 0167-9260 |
| Popis: | Because of fabrication compatibility to current semiconductor technology, three-dimensional integrated circuits (3D-ICs) offer promising near-term solutions for maintaining Moore’s Law. 3D-ICs proffer high system speeds, massively parallel processing, low power consumption, and their high densities result in small footprints. In this paper, a novel 3D neuromorphic IC architecture which combines monolithic 3D integration and a synaptic array based on vertical resistive random-access memory structure (V-RRAM) is proposed. To analyze the electrical characteristics of the proposed synaptic array, a concise equivalent circuit model of the system is developed, and analytical calculations for each parameter of the equivalent circuit are provided. Moreover, a novel signal intensity encoding neuron design that can directly convert analog signal into a spiking waveform sequence is proposed and analyzed. A feasible 3D neuromorphic computing architecture is demonstrated. Applying the monolithic 3D integration technology on neuromorphic computing system hardware implementation can reduce the power consumption by 50%, and shrink die areas by 35%. |
| Databáze: | OpenAIRE |
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