Weng-Fai Wong

Weng-Fai Wong

National University of Singapore

H-index: 38

Asia-Singapore

About Weng-Fai Wong

Weng-Fai Wong, With an exceptional h-index of 38 and a recent h-index of 20 (since 2020), a distinguished researcher at National University of Singapore, specializes in the field of Computer architecture, compilers, high performance computing, embedded systems, parallel processing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-terminal Coding Sequences

Table-Lookup MAC: Scalable Processing of Quantised Neural Networks in FPGA Soft Logic

Towards a Better 16-Bit Number Representation for Training Neural Networks

Simeuro: A Hybrid CPU-GPU Parallel Simulator for Neuromorphic Computing Chips

DeepFire2: A Convolutional Spiking Neural Network Accelerator on FPGAs

Optimizing for In-Memory Deep Learning With Emerging Memory Technology

HongTu: Scalable Full-Graph GNN Training on Multiple GPUs

OpenEmbedding: A Distributed Parameter Server for Deep Learning Recommendation Models using Persistent Memory

Weng-Fai Wong Information

University

Position

Associate Professor of Computer Science

Citations(all)

4997

Citations(since 2020)

1654

Cited By

3863

hIndex(all)

38

hIndex(since 2020)

20

i10Index(all)

98

i10Index(since 2020)

45

Email

University Profile Page

National University of Singapore

Google Scholar

View Google Scholar Profile

Weng-Fai Wong Skills & Research Interests

Computer architecture

compilers

high performance computing

embedded systems

parallel processing

Top articles of Weng-Fai Wong

Title

Journal

Author(s)

Publication Date

Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-terminal Coding Sequences

arXiv preprint arXiv:2402.13297

Zhanglu Yan

Weiran Chu

Yuhua Sheng

Kaiwen Tang

Shida Wang

...

2024/2/20

Table-Lookup MAC: Scalable Processing of Quantised Neural Networks in FPGA Soft Logic

Daniel Gerlinghoff

Benjamin Chen Ming Choong

Rick Siow Mong Goh

Weng-Fai Wong

Tao Luo

2024/4/1

Towards a Better 16-Bit Number Representation for Training Neural Networks

Himeshi De Silva

Hongshi Tan

Nhut-Minh Ho

John L Gustafson

Weng-Fai Wong

2023/3/1

Simeuro: A Hybrid CPU-GPU Parallel Simulator for Neuromorphic Computing Chips

IEEE Transactions on Parallel and Distributed Systems

Huaipeng Zhang

Nhut-Minh Ho

Yigit Polat Dogukan

Peng Chen

Mohamed Wahib

...

2023/7/3

DeepFire2: A Convolutional Spiking Neural Network Accelerator on FPGAs

arXiv e-prints

Myat Thu Linn Aung

Daniel Gerlinghoff

Chuping Qu

Liwei Yang

Tian Huang

...

2023/5

Optimizing for In-Memory Deep Learning With Emerging Memory Technology

IEEE Transactions on Neural Networks and Learning Systems

Zhehui Wang

Tao Luo

Rick Siow Mong Goh

Wei Zhang

Weng-Fai Wong

2023/6/27

HongTu: Scalable Full-Graph GNN Training on Multiple GPUs

Proceedings of the ACM on Management of Data

Qiange Wang

Yao Chen

Weng-Fai Wong

Bingsheng He

2023/12/12

OpenEmbedding: A Distributed Parameter Server for Deep Learning Recommendation Models using Persistent Memory

Cheng Chen

Yilin Wang

Jun Yang

Yiming Liu

Mian Lu

...

2023/4/3

Achieving green ai with energy-efficient deep learning using neuromorphic computing

Communications of the ACM

Tao Luo

Weng-Fai Wong

Rick Siow Mong Goh

Anh Tuan Do

Zhixian Chen

...

2023/6/22

Desire backpropagation: A lightweight training algorithm for multi-layer spiking neural networks based on spike-timing-dependent plasticity

Neurocomputing

Daniel Gerlinghoff

Tao Luo

Rick Siow Mong Goh

Weng-Fai Wong

2023/12/1

Bedot: Bit Efficient Dot Product for Deep Generative Models

Nhut-Minh Ho

Duy-Thanh Nguyen

John L. Gustafson

Weng-Fai Wong

2023/2/27

LightRW: FPGA Accelerated Graph Dynamic Random Walks

Proceedings of the ACM on Management of Data

Hongshi Tan

Xinyu Chen

Yao Chen

Bingsheng He

Weng-Fai Wong

2023/5/30

CQ+ Training: Minimizing Accuracy Loss in Conversion From Convolutional Neural Networks to Spiking Neural Networks

IEEE Transactions on Pattern Analysis and Machine Intelligence

Zhanglu Yan

Jun Zhou

Weng-Fai Wong

2023/10

1.7 pJ/SOP Neuromorphic Processor with Integrated Partial Sum Routers for In-Network Computing

B Wang

MM Wong

D Li

YS Chong

J Zhou

...

2023/5/21

Efficient hyperdimensional computing

Zhanglu Yan

Shida Wang

Kaiwen Tang

Weng-Fai Wong

2023/9/17

Low Latency Conversion of Artificial Neural Network Models to Rate-encoded Spiking Neural Networks

arXiv preprint arXiv:2211.08410

Zhanglu Yan

Jun Zhou

Weng-Fai Wong

2022/10/27

React: a heterogeneous reconfigurable neural network accelerator with software-configurable nocs for training and inference on wearables

Mohit Upadhyay

Rohan Juneja

Bo Wang

Jun Zhou

Weng-Fai Wong

...

2022/7/10

Network-on-Chip-Centric Accelerator Architectures for Edge AI Computing

Bo Wang

Ke Dong

Nurul Akhira Binte Zakaria

Mohit Upadhyay

Weng-Fai Wong

...

2022/10/19

EEG classification with spiking neural network: Smaller, better, more energy efficient

Smart Health

Zhanglu Yan

Jun Zhou

Weng-Fai Wong

2022/6/1

Corrigendum to “Coreset:: Hierarchical neuromorphic computing supporting large-scale neural networks with improved resource efficiency”[Neurocomputing (2022) 128–140]

Liwei Yang

Huaipeng Zhang

Tao Luo

Chuping Qu

Myat Thu Linn Aung

...

2022/10/7

See List of Professors in Weng-Fai Wong University(National University of Singapore)

Co-Authors

H-index: 92
Beng Chin OOI

Beng Chin OOI

National University of Singapore

H-index: 83
Yiran Chen

Yiran Chen

Duke University

H-index: 74
Saman Amarasinghe

Saman Amarasinghe

Massachusetts Institute of Technology

H-index: 61
Bingsheng He, 何丙胜

Bingsheng He, 何丙胜

National University of Singapore

H-index: 57
Deming Chen

Deming Chen

University of Illinois at Urbana-Champaign

H-index: 50
Larry Rudolph

Larry Rudolph

Massachusetts Institute of Technology

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