ダン ナム カイン

DANG Nam Khanh

Associate Professor

Affiliation
Department of Computer Science and Engineering/Division of Computer Engineering
Title
Associate Professor
E-Mail
khanh@u-aizu.ac.jp
Web site
https://u-aizu.ac.jp/~khanh/

Education

Courses - Undergraduate
PL03: JAVA Programming I (Ex.), Q1.
FU05: Computer Architecture (Ex.), Q1.
SE08: Introduction of Big Data Analytics (Ex.), Q3.
FU06: Operating Systems (Ex.), Q4.
Courses - Graduate
SYA14: Neuromorphic Computing, Q2.
RPW1: Research Paper Writing I, Q3+Q4.

Research

Specialization
Control and system engineering
Electron device and electronic equipment
Computer system
High performance computing
Computational science
Intelligent informatics
- Neuromorphic Computing
- Machine Learning
- Fault-tolerance
- Generative AI
Educational Background, Biography
Educational Background
- Ph.D. in Computer Science and Engineering, The University of Aizu, Japan, 2017
- M.Sc. in Information Systems & Technology, University of Paris-XI, France, 2014
- B.Sc. in Electronics & Telecommunications, VNU University of Engineering and Technology, Vietnam, 2011

Work Experience
- Associate Professor, The University of Aizu, 2022 April - now.
- Assistant Professor, VNU University of Engineering and Technology, Vietnam National University, Hanoi, 2017 November - 2022 March.
- Visiting Researcher, The University of Aizu, 2020 November - 2021 March.
- Visiting Researcher, The University of Aizu, 2019 May - 2019 September.
- Researcher, SISLAB, Vietnam National University, Hanoi, 2011-2014.
- RTL Designer, Dolphin Inc., 2010-2011.
Current Research Theme
- Neuromorphic engineering
- Generative AI
- Edge Intelligence for Disasters
Key Topic
Neuromorphic Computing, Faul-tolerance, VLSI, 3D Integrated Circuits, Generative AI
Affiliated Academic Society

Others

Hobbies
Football, Chess, Photography
School days' Dream
Be a person that can change the world!
Current Dream
Be a good teacher & change the world!
Motto
Master the Basics, Build the Future—Life's a Marathon, Not a Sprint.
Favorite Books
The Fountainhead - Ayn Rand
Messages for Students
I firmly believe in mastering the fundamentals before tackling advanced topics. Take the time to read, study, and practice essential subjects like mathematics, English, and programming. This solid foundation will serve you well throughout your career. Remember, it’s better to build a strong base than a fragile structure.

It’s okay to progress slower than your peers for now; with a deep understanding of the basics, you’ll eventually surpass them. Life isn’t a sprint—it’s a marathon. Focus on steady, meaningful growth that will carry you far in the long run.

Main research

Brain-Inspired Architectures (energy efficiency, scalability, learning algorithms, FPGA/VLSI implementation, applications exploration)

Brain-inspired (Neuromorphic) computing uses spiking neuron network models to solve machine learning problems in a more power/energy-efficient way when compared to the conventional artificial neural networks.We research adaptive low-power spiking neuromorphic systems and SoCs empowered with our earlier developed fault-tolerant three-dimensional on-chip interconnect technology. In particular, we investigate innovative algorithms and neuromorphic systems, including adaptive configuration methods to enable the reconfiguration of different network parameters (spike weights, routing, hidden layers, topology, etc.), fault-tolerance, thermal-aware mapping methods, and on-line learning algorithms. The target applications include anthropomorphic robotics and edge computing.


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Processor interconnection networks (3D-NoC, 3D-TSV, SiPh-2D/3D-NoC, Hybrid)

Complex SoCs contain dozens of components made of processor cores, DSPs, memory, accelerators, and I/O, all integrated into a single die area of just a few square millimeters. Such complex systems will be interconnected via a complex on-chip interconnect closer to a sophisticated network than current bus-based solutions. This network must provide high throughput and low latency while keeping area and power consumption low. Our research effort is about solving several design challenges to enable such new paradigm in massively parallel many-core systems. In particular, we are investigating fault-tolerance, 3D-TSV integration, photonic communication, low-power mapping techniques, and low-latency adaptive routing.

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Dissertation and Published Works

Patent:

- A. Ben Abdallah, Khanh N. Dang, An on-chip 3D system in which TSV groups containing multiple TSVs connect layers together [複数のTSVを含むTSVグループが層間を接続するオンチップの3次元システム], 特許第7488989号, Japan patent.

- A. Ben Abdallah, Khanh N. Dang, Masayuki Hisada, TSV Error Tolerant Router Device for 3D Network On Chip, 特許第7239099号, Japan patent,

Selected Publication:

- Ngo-Doanh Nguyen1, Khanh N. Dang, Akram Ben Ahmed, Abderazek Ben Abdallah, Xuan-Tu Tran, ''NOMA: A Novel Reliability Improvement Methodology for 3-D IC-based Neuromorphic Systems'', IEEE Transactions on Components, Packaging and Manufacturing Technology, 2024 (accepted).

- Ngo-Doanh Nguyen, Akram Ben Ahmed, Abderazek Ben Abdallah, Khanh N. Dang, “Power-aware Neuromorphic Architecture with Partial Voltage Scaling 3D Stacking Synaptic Memory“, IEEE Transactions on Very Large Scale Integration Systems (TVLSI), vol. 31, no. 12, pp. 2016-2029, Dec. 2023.


- 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), [DOI: 10.1109/TETC.2021.3136028].

- Khanh N. Dang, Akram Ben Ahmed, Abderazek Ben Abdallah, Xuan-Tu Tran, “HotCluster: A thermal-aware defect recovery method for Through-Silicon-Vias Towards Reliable 3-D ICs systems”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE, Volume 41, No. 4, pp. 799-812, April 2022. [DOI: 10.1109/TCAD.2021.3069370].

- Khanh N. Dang, Akram Ben Ahmed, Ben Abdallah Abderrazak and Xuan-Tu Tran, “TSV-OCT: A Scalable Online Multiple-TSV Defects Localization for Real-Time 3-D-IC Systems”, IEEE Transactions on Very Large Scale Integration Systems (TVLSI), IEEE, Volume 28, Issue 3, pp. 672 - 685, 2020. [DOI: 10.1109/TVLSI.2019.2948878].

- Khanh N. Dang, Akram Ben Ahmed, Yuichi Okuyama, Abderazek Ben Abdallah, “Scalable design methodology and online algorithm for TSV-cluster defects recovery in highly reliable 3D-NoC systems”, IEEE Transactions on Emerging Topics in Computing (TETC), IEEE, Volume 8, Issue 3, pp. 577-590, 2020. [DOI: 10.1109/TETC.2017.2762407].

- Khanh N. Dang, Akram Ben Ahmed, Xuan-Tu Tran, Yuichi Okuyama, Abderazek Ben Abdallah, “A Comprehensive Reliability Assessment of Fault-Resilient Network-on-Chip Using Analytical Model”, IEEE Transactions on Very Large Scale Integration Systems (TVLSI), IEEE, Volume 25, Issue 11, pp. 3099-3112, 2017. [DOI: 10.1109/TVLSI.2017.2736004].


For more details, please visit: https://u-aizu.ac.jp/~khanh/