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

The goal of this project to research and implement an adaptive, low-power spiking neural network system in hardware (NASH) based on our earlier developed OASIS communication network. NASH implements the followings features (1) efficient adaptive configuration method which enables 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) Efficient on-chip learning mechanism. To demonstrate the performance of NASH system, an FPGA implementation shall be developed and  VLSI implementation shall be also 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 (pending)

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: Mark, Williams, Maatar