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Neuromorphic 3D Integrated Circuit: A Hybrid, Reliable and Energy Efficient Approach for Next Generation Computing

Published: 10 May 2017 Publication History

Abstract

In this paper, we proposed to use 3D integration technology to create a neuromorphic hardware system that is compatible with current technology, provides high system speed, high density, massively parallel processing, low power consumption, and small footprint. The Through Silicon Vias (TSVs) used in the 3D neuromorphic structure provide high density integration and energy efficient links for transferring information through multiple neuron layers. This work details how a 3D neuromorphic system is benefited from the redundant TSV with substantial design-area reduction. We discussed the yield and reliability issues and explained the impact in neuromorphic 3D system design. A spiking neuron model is developed for the proposed 3D system. Furthermore, a new methodology have been proposed by introducing oxide around the bump that could significantly enhance the TSV capacitance in 3D Neuromorphic Computing (NC) system.

References

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Y. Yi and Y. Zhou, "A novel circuit model for multiple Through Silicon Vias (TSVs) in 3D IC, in Proc. IEEE Int. 3D Systems Integr. Conf., 2013, pp. 1--4.

Cited By

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  • (2024)The 3D Monolithically Integrated Hardware Based Neural System with Enhanced Memory Window of the Volatile and Non‐Volatile DevicesAdvanced Science10.1002/advs.20240266711:31Online publication date: 17-Jun-2024
  • (2023)An Electromagnetic Perspective of Artificial Intelligence Neuromorphic ChipsElectromagnetic Science10.23919/emsci.2023.00151:3(1-18)Online publication date: Sep-2023
  • (2021)A Genetic Algorithm-Based Metaheuristic Approach for Test Cost Optimization of 3D SICIEEE Access10.1109/ACCESS.2021.31313369(160987-161002)Online publication date: 2021
  • Show More Cited By

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cover image ACM Conferences
GLSVLSI '17: Proceedings of the Great Lakes Symposium on VLSI 2017
May 2017
516 pages
ISBN:9781450349727
DOI:10.1145/3060403
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 10 May 2017

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Author Tags

  1. 3d integration
  2. neuromorphic computing
  3. reliability
  4. spiking neuron
  5. tsv
  6. yield

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  • Research-article

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GLSVLSI '17
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GLSVLSI '17: Great Lakes Symposium on VLSI 2017
May 10 - 12, 2017
Alberta, Banff, Canada

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GLSVLSI '17 Paper Acceptance Rate 48 of 197 submissions, 24%;
Overall Acceptance Rate 312 of 1,156 submissions, 27%

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Cited By

View all
  • (2024)The 3D Monolithically Integrated Hardware Based Neural System with Enhanced Memory Window of the Volatile and Non‐Volatile DevicesAdvanced Science10.1002/advs.20240266711:31Online publication date: 17-Jun-2024
  • (2023)An Electromagnetic Perspective of Artificial Intelligence Neuromorphic ChipsElectromagnetic Science10.23919/emsci.2023.00151:3(1-18)Online publication date: Sep-2023
  • (2021)A Genetic Algorithm-Based Metaheuristic Approach for Test Cost Optimization of 3D SICIEEE Access10.1109/ACCESS.2021.31313369(160987-161002)Online publication date: 2021
  • (2020)Quantized Neural Networks and Neuromorphic Computing for Embedded SystemsIntelligent System and Computing10.5772/intechopen.91835Online publication date: 29-Apr-2020
  • (2019)Making BREAD: Biomimetic Strategies for Artificial Intelligence Now and in the FutureFrontiers in Neuroscience10.3389/fnins.2019.0066613Online publication date: 27-Jun-2019
  • (2019)Memristive Crossbar Mapping for Neuromorphic Computing Systems on 3D ICACM Transactions on Design Automation of Electronic Systems10.1145/336557625:1(1-19)Online publication date: 25-Nov-2019
  • (2019)Spiking Neural Networks Hardware Implementations and ChallengesACM Journal on Emerging Technologies in Computing Systems10.1145/330410315:2(1-35)Online publication date: 5-Apr-2019
  • (2018)Memristive Crossbar Mapping for Neuromorphic Computing Systems on 3D ICProceedings of the 2018 Great Lakes Symposium on VLSI10.1145/3194554.3194636(451-454)Online publication date: 30-May-2018

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