Hongxiang Fan

According to our database, Hongxiang Fan authored at least 60 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

DESA: Dataflow Efficient Systolic Array for Acceleration of Transformers.

Zhican Wang, Hongxiang Fan, Guanghui He

IEEE Trans. Computers, June, 2025

Accelerating 3D Gaussian Splatting with Neural Sorting and Axis-Oriented Rasterization.

Zhican Wang, Guanghui He, Dantong Liu, Lingjun Gao, Shell Xu Hu, Chen Zhang, Zhuoran Song, Nicholas D. Lane, Wayne Luk, Hongxiang Fan

CoRR, June, 2025

Advancing AI-assisted Hardware Design with Hierarchical Decentralized Training and Personalized Inference-Time Optimization.

Hao Mark Chen, Zehuan Zhang, Wanru Zhao, Nicholas D. Lane, Hongxiang Fan

CoRR, June, 2025

Rethinking Optimal Verification Granularity for Compute-Efficient Test-Time Scaling.

Hao Mark Chen, Guanxi Lu, Yasuyuki Okoshi, Zhiwen Mo, Masato Motomura, Hongxiang Fan

CoRR, May, 2025

Enhancing LLM-based Quantum Code Generation with Multi-Agent Optimization and Quantum Error Correction.

Charlie Campbell, Hao Mark Chen, Wayne Luk, Hongxiang Fan

CoRR, April, 2025

Versatile Cross-platform Compilation Toolchain for Schrödinger-style Quantum Circuit Simulation.

Yuncheng Lu, Shuang Liang, Hongxiang Fan, Ce Guo, Wayne Luk, Paul H. J. Kelly

CoRR, March, 2025

FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization.

Hao Mark Chen, Shell Xu Hu, Wayne Luk, Timothy M. Hospedales, Hongxiang Fan

CoRR, March, 2025

MetaML-Pro: Cross-Stage Design Flow Automation for Efficient Deep Learning Acceleration.

Zhiqiang Que, José Gabriel F. Coutinho, Ce Guo, Hongxiang Fan, Wayne Luk

CoRR, February, 2025

Progressive Mixed-Precision Decoding for Efficient LLM Inference.

Hao Mark Chen, Fuwen Tan, Alexandros Kouris, Royson Lee, Hongxiang Fan, Stylianos I. Venieris

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Trustworthy Deep Learning Acceleration with Customizable Design Flow Automation.

Zhiqiang Que, Hongxiang Fan, Gabriel F. Figueiredo, Ce Guo, Wayne Luk, Ryota Yasudo, Masato Motomura

Proceedings of the 15th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies, 2025

Exploring Code Language Models for Automated HLS-based Hardware Generation: Benchmark, Infrastructure and Analysis.

Jiahao Gai, Hao Chen, Zhican Wang, Hongyu Zhou, Wanru Zhao, Nicholas D. Lane, Hongxiang Fan

Proceedings of the 30th Asia and South Pacific Design Automation Conference, 2025

2024

Design of Fully Spectral CNNs for Efficient FPGA-Based Acceleration.

Shuanglong Liu, Hongxiang Fan, Wayne Luk

IEEE Trans. Neural Networks Learn. Syst., June, 2024

Low Latency Variational Autoencoder on FPGAs.

Zhiqiang Que, Minghao Zhang, Hongxiang Fan, He Li, Ce Guo, Wayne Luk

IEEE J. Emerg. Sel. Topics Circuits Syst., June, 2024

LL-GNN: Low Latency Graph Neural Networks on FPGAs for High Energy Physics.

Zhiqiang Que, Hongxiang Fan, Marcus Loo, He Li, Michaela Blott, Maurizio Pierini, Alexander D. Tapper, Wayne Luk

ACM Trans. Embed. Comput. Syst., March, 2024

Enhancing Dropout-based Bayesian Neural Networks with Multi-Exit on FPGA.

Hao Mark Chen, Liam Castelli, Martin Ferianc, Hongyu Zhou, Shuanglong Liu, Wayne Luk, Hongxiang Fan

CoRR, 2024

Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inference.

Hao Mark Chen, Wayne Luk, Ka Fai Cedric Yiu, Rui Li, Konstantin Mishchenko, Stylianos I. Venieris, Hongxiang Fan

CoRR, 2024

CLUES: Collaborative Private-domain High-quality Data Selection for LLMs via Training Dynamics.

Wanru Zhao, Hongxiang Fan, Shell Xu Hu, Wangchunshu Zhou, Nicholas D. Lane

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Circular Reconfigurable Parallel Processor for Edge Computing : Industrial Product ✶.

Yuan Li, Jianbin Zhu, Yao Fu, Yu Lei, Toshio Nagata, Ryan Braidwood, Haohuan Fu, Juepeng Zheng, Wayne Luk, Hongxiang Fan

Proceedings of the 51st ACM/IEEE Annual International Symposium on Computer Architecture, 2024

Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages.

Wanru Zhao, Yihong Chen, Royson Lee, Xinchi Qiu, Yan Gao, Hongxiang Fan, Nicholas Donald Lane

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Hardware-Aware Neural Dropout Search for Reliable Uncertainty Prediction on FPGA.

Zehuan Zhang, Hongxiang Fan, Hao Mark Chen, Lukasz Dudziak, Wayne Luk

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

SAE: Single Architecture Ensemble Neural Networks.

Martin Ferianc, Hongxiang Fan, Miguel R. D. Rodrigues

Proceedings of the 35th British Machine Vision Conference, 2024

Accelerating MRI Uncertainty Estimation with Mask-Based Bayesian Neural Network.

Zehuan Zhang, Matej Genci, Hongxiang Fan, Andreas Wetscherek, Wayne Luk

Proceedings of the 35th IEEE International Conference on Application-specific Systems, 2024

2023

High-Performance Acceleration of 2-D and 3-D CNNs on FPGAs Using Static Block Floating Point.

Hongxiang Fan, Shuanglong Liu, Zhiqiang Que, Xinyu Niu, Wayne Luk

IEEE Trans. Neural Networks Learn. Syst., August, 2023

Design Space Exploration for Efficient Quantum Most-Significant Digit-First Arithmetic.

He Li, Jiawei Liang, Hongxiang Fan, Yongming Tang

IEEE Trans. Computers, June, 2023

Remarn: A Reconfigurable Multi-threaded Multi-core Accelerator for Recurrent Neural Networks.

Zhiqiang Que, Hiroki Nakahara, Hongxiang Fan, He Li, Jiuxi Meng, Kuen Hung Tsoi, Xinyu Niu, Eriko Nurvitadhi, Wayne Luk

ACM Trans. Reconfigurable Technol. Syst., March, 2023

When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA.

Hongxiang Fan, Hao Chen, Liam Castelli, Zhiqiang Que, He Li, Kenneth Long, Wayne Luk

CoRR, 2023

Sparse-DySta: Sparsity-Aware Dynamic and Static Scheduling for Sparse Multi-DNN Workloads.

Hongxiang Fan, Stylianos I. Venieris, Alexandros Kouris, Nicholas D. Lane

Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture, 2023

When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA.

Hongxiang Fan, Mark Chen, Liam Castelli, Zhiqiang Que, He Li, Kenneth Long, Wayne Luk

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022

Recurrent Neural Networks With Column-Wise Matrix-Vector Multiplication on FPGAs.

Zhiqiang Que, Hiroki Nakahara, Eriko Nurvitadhi, Andrew Boutros, Hongxiang Fan, Chenglong Zeng, Jiuxi Meng, Kuen Hung Tsoi, Xinyu Niu, Wayne Luk

IEEE Trans. Very Large Scale Integr. Syst., 2022

Accelerating Bayesian Neural Networks via Algorithmic and Hardware Optimizations.

Hongxiang Fan, Martin Ferianc, Zhiqiang Que, Xinyu Niu, Miguel R. D. Rodrigues, Wayne Luk

IEEE Trans. Parallel Distributed Syst., 2022

Toward Full-Stack Acceleration of Deep Convolutional Neural Networks on FPGAs.

Shuanglong Liu, Hongxiang Fan, Martin Ferianc, Xinyu Niu, Huifeng Shi, Wayne Luk

IEEE Trans. Neural Networks Learn. Syst., 2022

FPGA-Based Acceleration for Bayesian Convolutional Neural Networks.

Hongxiang Fan, Martin Ferianc, Zhiqiang Que, Shuanglong Liu, Xinyu Niu, Miguel R. D. Rodrigues, Wayne Luk

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

LL-GNN: Low Latency Graph Neural Networks on FPGAs for Particle Detectors.

Zhiqiang Que, Marcus Loo, Hongxiang Fan, Michaela Blott, Maurizio Pierini, Alexander D. Tapper, Wayne Luk

CoRR, 2022

Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design.

Hongxiang Fan, Thomas Chau, Stylianos I. Venieris, Royson Lee, Alexandros Kouris, Wayne Luk, Nicholas D. Lane, Mohamed S. Abdelfattah

Proceedings of the 55th IEEE/ACM International Symposium on Microarchitecture, 2022

Customizable FPGA-based Accelerator for Binarized Graph Neural Networks.

Ziwei Wang, Zhiqiang Que, Wayne Luk, Hongxiang Fan

Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

Optimizing Graph Neural Networks for Jet Tagging in Particle Physics on FPGAs.

Zhiqiang Que, Marcus Loo, Hongxiang Fan, Maurizio Pierini, Alexander D. Tapper, Wayne Luk

Proceedings of the 32nd International Conference on Field-Programmable Logic and Applications, 2022

Optimizing quantum circuit placement via machine learning.

Hongxiang Fan, Ce Guo, Wayne Luk

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

Enabling fast uncertainty estimation: accelerating bayesian transformers via algorithmic and hardware optimizations.

Hongxiang Fan, Martin Ferianc, Wayne Luk

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator.

Hongxiang Fan, Martin Ferianc, Zhiqiang Que, He Li, Shuanglong Liu, Xinyu Niu, Wayne Luk

Proceedings of the 27th Asia and South Pacific Design Automation Conference, 2022

2021

High-Performance FPGA-based Accelerator for Bayesian Recurrent Neural Networks.

Martin Ferianc, Zhiqiang Que, Hongxiang Fan, Wayne Luk, Miguel Rodrigues

CoRR, 2021

ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation.

Martin Ferianc, Divyansh Manocha, Hongxiang Fan, Miguel Rodrigues

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

Quantum Most-Significant Digit-First Addition.

He Li, Hongxiang Fan, Jiawei Liang

Proceedings of the 12th International Green and Sustainable Computing Workshops, 2021

Optimizing Bayesian Recurrent Neural Networks on an FPGA-based Accelerator.

Martin Ferianc, Zhiqiang Que, Hongxiang Fan, Wayne Luk, Miguel Rodrigues

Proceedings of the International Conference on Field-Programmable Technology, 2021

Accelerating Fully Spectral CNNs with Adaptive Activation Functions on FPGA.

Shuanglong Liu, Hongxiang Fan, Wayne Luk

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

High-Performance FPGA-based Accelerator for Bayesian Neural Networks.

Hongxiang Fan, Martin Ferianc, Miguel Rodrigues, Hongyu Zhou, Xinyu Niu, Wayne Luk

Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

2020

Mapping Large LSTMs to FPGAs with Weight Reuse.

Zhiqiang Que, Yongxin Zhu, Hongxiang Fan, Jiuxi Meng, Xinyu Niu, Wayne Luk

J. Signal Process. Syst., 2020

VINNAS: Variational Inference-based Neural Network Architecture Search.

Martin Ferianc, Hongxiang Fan, Miguel Rodrigues

CoRR, 2020

A Reconfigurable Multithreaded Accelerator for Recurrent Neural Networks.

Zhiqiang Que, Hiroki Nakahara, Hongxiang Fan, Jiuxi Meng, Kuen Hung Tsoi, Xinyu Niu, Eriko Nurvitadhi, Wayne Luk

Proceedings of the International Conference on Field-Programmable Technology, 2020

Optimizing FPGA-Based CNN Accelerator Using Differentiable Neural Architecture Search.

Hongxiang Fan, Martin Ferianc, Shuanglong Liu, Zhiqiang Que, Xinyu Niu, Wayne Luk

Proceedings of the 38th IEEE International Conference on Computer Design, 2020

Optimizing Reconfigurable Recurrent Neural Networks.

Zhiqiang Que, Hiroki Nakahara, Eriko Nurvitadhi, Hongxiang Fan, Chenglong Zeng, Jiuxi Meng, Xinyu Niu, Wayne Luk

Proceedings of the 28th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2020

Improving Performance Estimation for FPGA-Based Accelerators for Convolutional Neural Networks.

Martin Ferianc, Hongxiang Fan, Ringo S. W. Chu, Jakub Stano, Wayne Luk

Proceedings of the Applied Reconfigurable Computing. Architectures, Tools, and Applications, 2020

2019

Static Block Floating-Point Quantization for Convolutional Neural Networks on FPGA.

Hongxiang Fan, Gang Wang, Martin Ferianc, Xinyu Niu, Wayne Luk

Proceedings of the International Conference on Field-Programmable Technology, 2019

Towards Efficient Deep Neural Network Training by FPGA-Based Batch-Level Parallelism.

Cheng Luo, Man-Kit Sit, Hongxiang Fan, Shuanglong Liu, Wayne Luk, Ce Guo

Proceedings of the 27th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2019

F-E3D: FPGA-based Acceleration of an Efficient 3D Convolutional Neural Network for Human Action Recognition.

Hongxiang Fan, Cheng Luo, Chenglong Zeng, Martin Ferianc, Zhiqiang Que, Shuanglong Liu, Xinyu Niu, Wayne Luk

Proceedings of the 30th IEEE International Conference on Application-specific Systems, 2019

2018

Optimizing CNN-based Segmentation with Deeply Customized Convolutional and Deconvolutional Architectures on FPGA.

Shuanglong Liu, Hongxiang Fan, Xinyu Niu, Ho-Cheung Ng, Yang Chu, Wayne Luk

ACM Trans. Reconfigurable Technol. Syst., 2018

Memory-Efficient Architecture for Accelerating Generative Networks on FPGA.

Shuanglong Liu, Chenglong Zeng, Hongxiang Fan, Ho-Cheung Ng, Jiuxi Meng, Zhiqiang Que, Xinyu Niu, Wayne Luk

Proceedings of the International Conference on Field-Programmable Technology, 2018

A Real-Time Object Detection Accelerator with Compressed SSDLite on FPGA.

Hongxiang Fan, Shuanglong Liu, Martin Ferianc, Ho-Cheung Ng, Zhiqiang Que, Shen Liu, Xinyu Niu, Wayne Luk

Proceedings of the International Conference on Field-Programmable Technology, 2018

Reconfigurable Acceleration of 3D-CNNs for Human Action Recognition with Block Floating-Point Representation.

Hongxiang Fan, Ho-Cheung Ng, Shuanglong Liu, Zhiqiang Que, Xinyu Niu, Wayne Luk

Proceedings of the 28th International Conference on Field Programmable Logic and Applications, 2018

2017

F-C3D: FPGA-based 3-dimensional convolutional neural network.

Hongxiang Fan, Xinyu Niu, Qiang Liu, Wayne Luk

Proceedings of the 27th International Conference on Field Programmable Logic and Applications, 2017

2016

IC security evaluation against fault injection attack based on FPGA emulation.

Song Xu, Qiang Liu, Tao Li, Hongxiang Fan

Proceedings of the 2016 International Conference on Field-Programmable Technology, 2016