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.
Patents
-
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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