Event-Driven Low-power Three Dimensional Digital Spiking Neuromorphic System with On-line Learning

Spiking neurons communicate through discrete action potentials enabling energy-efficient and reliable information processing in neuromorphic systems. This project aims to research and develop an adaptive low-power spiking neural network system in hardware (NASH) empowered with our earlier developed fault-tolerant three-dimensional on-chip interconnect technology. The NASH system features the following: (1) An efficient adaptive configuration method to enable the reconfiguration of different SNN parameters (spike weights, routing, hidden layers, topology, etc.), (2) A mixture of different deep NN topologies, (3) An efficient fault-tolerant multicast spike routing algorithm, (4) An efficient on-chip learning mechanism. 
To demonstrate the performance of the NASH system, an FPGA implementation shall be developed, and a VLSI implementation shall also be established.


  • Patent: Abderazek Ben Abdallah, The H. Vu, Masayuki Hisada, ''Neural Computing Architecture, Fault-tolerant Algorithm, and Design M1ethod for Spiking Neural Networks,''  特 願2019-124541 (provisional)

Journal papers

  • Abderazek Ben Abdallah, Khanh N. Dang, ''Toward Robust Cognitive 3D Brain-inspired Cross-paradigm System,'' Frontier in Neuroscience 15:690208, doi: 10.3389/fnins.2021.690208

  • Khanh N. Dang, Nguyen Anh Vu Doan, Abderazek Ben Abdallah “MigSpike: A Migration Based Algorithm and Architecture for Scalable Robust Neuromorphic Systems,”  IEEE Transactions on Emerging Topics in Computing (TETC), 12/2021. DOI: 10.1109/TETC.2021.3136028

  •  O. M. Ikechukwu, K. N. Dang and A. Ben Abdallah, ''On the Design of a Fault-Tolerant Scalable Three Dimensional NoC-Based Digital Neuromorphic System With On-Chip Learning,'' IEEE Access, vol. 9, pp. 64331-64345, 2021, doi: 10.1109/ACCESS.2021.3071089 

  • The H. Vu,Yuichi Okuyama, Abderazek Ben Abdallah, '' Comprehensive Analytic Performance Assessment and K-means based Multicast Routing Algorithms and Architecture for 3D-NoC of Spiking Neurons.,'' ACM Journal on Emerging Technologies in Computing Systems (JETC), Vol. 15, No. 4, Article 34, October 2019. doi: 10.1145/3340963

  • The Vu, Ogbodo Mark Ikechukwu, Abderazek Ben Abdallah, ''Fault-tolerant Spike Routing Algorithm and Architecture for Three Dimensional NoC-Based Neuromorphic Systems'', IEEE Access, Vol 7, pp. 90436-90452, 2019, DOI: 10.1109/ACCESS.2019.2925085

Conference papers

  • Ogbodo Mark Ikechukwu, Khanh N. Dang and Abderazek Ben. Abdallah, “Energy-efficient Spike-based Scalable Architecture for Next-generation Cognitive AI Computing Systems,” Springer Lecture  Note in Computer Science (LNCS), International Symposium on Ubiquitous Networking 2021 (UNET21), May 19 – May 22, 2021, Marakesh, Morocco (Best Student Paper Award)

    Mark Ogbodo, The Vu, Khanh N. Dang and Abderazek Abdallah, “Light-weight Spiking Neuron Processing Core for Large-scale 3D-NoC based Spiking Neural Network Processing Systems”, The 7th IEEE International Conference on Big Data and Smart Computing, Feb 19, 2020 - Feb 22, 2020,  Pusan, South Korea

  • The H. Vu, Abderazek Ben Abdallah, “Low-Latency K-Means Based Multicast Routing Algorithm and Architecture for Three Dimensional Spiking Neuromorphic Chips”, Big Data and Smart Computing (BigComp) 2019 IEEE International Conference on, pp. 1-8, Kyoto, Fab. 2019, (Best Paper Award Runner-Up).

  • The H. Vu, Yuji Murakami, and Abderazek Ben Abdallah, “Graceful Fault-tolerant On-chip Spike Routing Algorithm for Mesh-based Spiking Neural Networks,” in Proceedings of the International Conference on Intelligent Autonomous Systems (ICoIAS’2019), Singapore, Feb. 2019.

  • The H. Vu and Abderazek Ben Abdallah, “A Low-latency Tree-based Multicast Spike Routing for Scalable Multicore Neuromorphic Chips”, ACM – 5th International Conference of Computing for Engineering and Sciences,  Hammamet, Tunisia, July 2019 (to appear).

  • The H. Vu, Yuji Murakami, Abderazek Ben Abdallah, "Graceful Fault-Tolerant On-Chip Spike Routing Algorithm for Mesh-Based Spiking Neural Networks", 2nd International Conference on Intelligent Autonomous Systems (ICoIAS) 2019 , pp. 76-80, 2019.

Members:Williams, Maatar , Nguyen

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