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.
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 (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
|
|
|
