Zhiqiang Que

According to our database, Zhiqiang Que authored at least 50 papers between 2009 and 2024.

Collaborative distances:

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

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

Ultrafast jet classification at the HL-LHC.

Patrick Odagiu, Zhiqiang Que, Javier M. Duarte, Johannes Haller, Gregor Kasieczka, Artur Lobanov, Vladimir Loncar, Wayne Luk, Jennifer Ngadiuba, Maurizio Pierini, Philipp Rincke, Arpita Seksaria, Sioni Summers, Andre Sznajder, Alexander D. Tapper, Thea Klæboe Årrestad

Mach. Learn. Sci. Technol., 2024

Sets are all you need: Ultrafast jet classification on FPGAs for HL-LHC.

Patrick Odagiu, Zhiqiang Que, Javier M. Duarte, Johannes Haller, Gregor Kasieczka, Artur Lobanov, Vladimir Loncar, Wayne Luk, Jennifer Ngadiuba, Maurizio Pierini, Philipp Rincke, Arpita Seksaria, Sioni Summers, Andre Sznajder, Alexander D. Tapper, Thea Klæboe Årrestad

CoRR, 2024

Trustworthy Codesign by Verifiable Transformations.

Qianzhou Wang, Zhiqiang Que, Wayne Luk

Proceedings of the IEEE International Test Conference in Asia, 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

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

Efficiently Removing Sparsity for High-Throughput Stream Processing.

Philippos Papaphilippou, Zhiqiang Que, Wayne Luk

Proceedings of the International Conference on Field Programmable Technology, 2023

MetaML: Automating Customizable Cross-Stage Design-Flow for Deep Learning Acceleration.

Zhiqiang Que, Shuo Liu, Markus Rognlien, Ce Guo, José Gabriel F. Coutinho, Wayne Luk

Proceedings of the 33rd International Conference on Field-Programmable Logic and Applications, 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

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

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

Verifying Hardware Optimizations for Efficient Acceleration.

Qianzhou Wang, Yat Wong, Zhiqiang Que, Wayne Luk

Proceedings of the HEART 2022: International Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies, Tsukuba, Japan, June 9, 2022

Accelerating Transformer Neural Networks on FPGAs for High Energy Physics Experiments.

Filip Wojcicki, Zhiqiang Que, Alexander D. Tapper, Wayne Luk

Proceedings of the International Conference on Field-Programmable Technology, 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

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

Hardware-Aware Optimizations for Deep Learning Inference on Edge Devices.

Markus Rognlien, Zhiqiang Que, José Gabriel F. Coutinho, Wayne Luk

Proceedings of the Applied Reconfigurable Computing. Architectures, Tools, and Applications, 2022

Reconfigurable Acceleration of Graph Neural Networks for Jet Identification in Particle Physics.

Zhiqiang Que, Marcus Loo, Wayne Luk

Proceedings of the 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2022

2021

In-circuit tuning of deep learning designs.

Zhiqiang Que, Daniel Holanda Noronha, Ruizhe Zhao, Xinyu Niu, Steven J. E. Wilton, Wayne Luk

J. Syst. Archit., 2021

Applications and Techniques for Fast Machine Learning in Science.

Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller-Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Thomas K. Warburton, Maria Acosta Flechas, Anthony Aportela, Thomas Calvet, Leonardo Cristella, Daniel Diaz, Caterina Doglioni, Maria Domenica Galati, Elham E Khoda, Farah Fahim, Davide Giri, Benjamin Hawks, Duc Hoang, Burt Holzman, Shih-Chieh Hsu, Sergo Jindariani, Iris Johnson, Raghav Kansal, Ryan Kastner, Erik Katsavounidis, Jeffrey D. Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric A. Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan S. Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng

CoRR, 2021

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

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

CoRR, 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

Flexible Instrumentation for Live On-Chip Debug of Machine Learning Training on FPGAs.

Daniel Holanda Noronha, Zhiqiang Que, Wayne Luk, Steven J. E. Wilton

Proceedings of the 29th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2021

Accelerating Recurrent Neural Networks for Gravitational Wave Experiments.

Zhiqiang Que, Erwei Wang, Umar Marikar, Eric A. Moreno, Jennifer Ngadiuba, Hamza Javed, Bartlomiej Borzyszkowski, Thea Aarrestad, Vladimir Loncar, Sioni Summers, Maurizio Pierini, Peter Y. K. Cheung, Wayne Luk

Proceedings of the 32nd IEEE International Conference on Application-specific Systems, 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

Towards Overlay-based Rapid In-Circuit Tuning of Deep Learning Designs.

Zhiqiang Que, Daniel Holanda Noronha, Ruizhe Zhao, Xinyu Niu, Steven J. E. Wilton, Wayne Luk

Proceedings of the International Conference on Field-Programmable Technology, 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

R2CNN: Recurrent Residual Convolutional Neural Network on FPGA.

Hiroki Nakahara, Zhiqiang Que, Akira Jinguji, Wayne Luk

Proceedings of the FPGA '20: The 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 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

High-Throughput Convolutional Neural Network on an FPGA by Customized JPEG Compression.

Hiroki Nakahara, Zhiqiang Que, Wayne Luk

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

2019

An efficient convolutional neural network for small traffic sign detection.

Shijin Song, Zhiqiang Que, Junjie Hou, Sen Du, Yuefeng Song

J. Syst. Archit., 2019

Real-Time Anomaly Detection for Flight Testing Using AutoEncoder and LSTM.

Zhiqiang Que, Yanyang Liu, Ce Guo, Xinyu Niu, Yongxin Zhu, Wayne Luk

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

An Overlay for Rapid FPGA Debug of Machine Learning Applications.

Daniel Holanda Noronha, Ruizhe Zhao, Zhiqiang Que, Jeffrey Goeders, Wayne Luk, Steven J. E. Wilton

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

Towards In-Circuit Tuning of Deep Learning Designs.

Zhiqiang Que, Daniel Holanda Noronha, Ruizhe Zhao, Steven J. E. Wilton, Wayne Luk

Proceedings of the International Conference on Computer-Aided Design, 2019

Efficient Weight Reuse for Large LSTMs.

Zhiqiang Que, Thomas Nugent, Shuanglong Liu, Li Tian, Xinyu Niu, Yongxin Zhu, Wayne Luk

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

Reconfigurable Hardware Generation for Tensor Flow Models of CNN Algorithms on a Heterogeneous Acceleration Platform.

Jiajun Gao, Yongxin Zhu, Meikang Qiu, Kuen Hung Tsoi, Xinyu Niu, Wayne Luk, Ruizhe Zhao, Zhiqiang Que, Wei Mao, Can Feng, Xiaowen Zha, Guobao Deng, Jiayi Chen, Tao Liu

Proceedings of the Smart Computing and Communication - Third International Conference, 2018

Application of Transfer Learning in Continuous Time Series for Anomaly Detection in Commercial Aircraft Flight Data.

Peng Xiong, Yonxin Zhu, Zhanrui Sun, Zihao Cao, Menglin Wang, Yu Zheng, Junjie Hou, Tian Huang, Zhiqiang Que

Proceedings of the 2018 IEEE International Conference on Smart Cloud, 2018

FPGA Acceleration of LSTM Based on Data for Test Flight.

Zhanrui Sun, Yongxin Zhu, Yu Zheng, Hao Wu, Zihao Cao, Peng Xiong, Junjie Hou, Tian Huang, Zhiqiang Que

Proceedings of the 2018 IEEE International Conference on Smart Cloud, 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

2010

Revealing Feasibility of FMM on ASIC: Efficient Implementation of N-Body Problem on FPGA.

Zhe Zheng, Yongxin Zhu, Xu Wang, Zhiqiang Que, Tian Huang, Xiaojing Yin, Hui Wang, Guoguang Rong, Meikang Qiu

Proceedings of the 13th IEEE International Conference on Computational Science and Engineering, 2010

Implementing Medical CT Algorithms on Stand-alone FPGA Based Systems Using an Efficient Workflow with SysGen and Simulink.

Zhiqiang Que, Yongxin Zhu, Xuan Wang, Jibo Yu, Tian Huang, Zhe Zheng, Li Yang, Feng Zhao, Yuzhuo Fu

Proceedings of the 10th IEEE International Conference on Computer and Information Technology, 2010

2009

Design and Implementation of a Cordless Power Supply System for Pervasive Medical Devices.

Zhiqiang Que, Yongxin Zhu, Tingting Mo, Bin Chen, Zhijun Li

Proceedings of the International Conference on Embedded Software and Systems, 2009