Zhiqiang Que

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 48

Top Topics

High Energy Physics

Reconfigurable Hardware

Top Venues

Publications

Zhiqiang Que, Minghao Zhang, Hongxiang Fan, He Li, Ce Guo, Wayne Luk
Low Latency Variational Autoencoder on FPGAs. IEEE J. Emerg. Sel. Topics Circuits Syst. 14 (2) (2024)
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
Sets are all you need: Ultrafast jet classification on FPGAs for HL-LHC. CoRR (2024)
Zhiqiang Que, Hongxiang Fan, Marcus Loo, He Li, Michaela Blott, Maurizio Pierini, Alexander D. Tapper, Wayne Luk
LL-GNN: Low Latency Graph Neural Networks on FPGAs for High Energy Physics. ACM Trans. Embed. Comput. Syst. 23 (2) (2024)
Hongxiang Fan, Mark Chen, Liam Castelli, Zhiqiang Que, He Li, Kenneth Long, Wayne Luk
When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA. DAC (2023)
Zhiqiang Que, Shuo Liu, Markus Rognlien, Ce Guo, José Gabriel F. Coutinho, Wayne Luk
MetaML: Automating Customizable Cross-Stage Design-Flow for Deep Learning Acceleration. FPL (2023)
Philippos Papaphilippou, Zhiqiang Que, Wayne Luk
Efficiently Removing Sparsity for High-Throughput Stream Processing. ICFPT (2023)
Zhiqiang Que, Shuo Liu, Markus Rognlien, Ce Guo, José Gabriel F. Coutinho, Wayne Luk
MetaML: Automating Customizable Cross-Stage Design-Flow for Deep Learning Acceleration. CoRR (2023)
Hongxiang Fan, Hao Chen, Liam Castelli, Zhiqiang Que, He Li, Kenneth Long, Wayne Luk
When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA. CoRR (2023)
Hongxiang Fan, Shuanglong Liu, Zhiqiang Que, Xinyu Niu, Wayne Luk
High-Performance Acceleration of 2-D and 3-D CNNs on FPGAs Using Static Block Floating Point. IEEE Trans. Neural Networks Learn. Syst. 34 (8) (2023)
Zhiqiang Que, Hiroki Nakahara, Hongxiang Fan, He Li, Jiuxi Meng, Kuen Hung Tsoi, Xinyu Niu, Eriko Nurvitadhi, Wayne Luk
Remarn: A Reconfigurable Multi-threaded Multi-core Accelerator for Recurrent Neural Networks. ACM Trans. Reconfigurable Technol. Syst. 16 (1) (2023)
Zhiqiang Que, Hiroki Nakahara, Eriko Nurvitadhi, Andrew Boutros, Hongxiang Fan, Chenglong Zeng, Jiuxi Meng, Kuen Hung Tsoi, Xinyu Niu, Wayne Luk
Recurrent Neural Networks With Column-Wise Matrix-Vector Multiplication on FPGAs. IEEE Trans. Very Large Scale Integr. Syst. 30 (2) (2022)
Filip Wojcicki, Zhiqiang Que, Alexander D. Tapper, Wayne Luk
Accelerating Transformer Neural Networks on FPGAs for High Energy Physics Experiments. FPT (2022)
Hongxiang Fan, Martin Ferianc, Zhiqiang Que, He Li, Shuanglong Liu, Xinyu Niu, Wayne Luk
Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator. ASP-DAC (2022)
Hongxiang Fan, Martin Ferianc, Zhiqiang Que, Xinyu Niu, Miguel R. D. Rodrigues, Wayne Luk
Accelerating Bayesian Neural Networks via Algorithmic and Hardware Optimizations. IEEE Trans. Parallel Distributed Syst. 33 (12) (2022)
Zhiqiang Que, Marcus Loo, Wayne Luk
Reconfigurable Acceleration of Graph Neural Networks for Jet Identification in Particle Physics. AICAS (2022)
Hongxiang Fan, Martin Ferianc, Zhiqiang Que, Shuanglong Liu, Xinyu Niu, Miguel R. D. Rodrigues, Wayne Luk
FPGA-Based Acceleration for Bayesian Convolutional Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41 (12) (2022)
Zhiqiang Que, Marcus Loo, Hongxiang Fan, Michaela Blott, Maurizio Pierini, Alexander D. Tapper, Wayne Luk
LL-GNN: Low Latency Graph Neural Networks on FPGAs for Particle Detectors. CoRR (2022)
Qianzhou Wang, Yat Wong, Zhiqiang Que, Wayne Luk
Verifying Hardware Optimizations for Efficient Acceleration. HEART (2022)
Ziwei Wang, Zhiqiang Que, Wayne Luk, Hongxiang Fan
Customizable FPGA-based Accelerator for Binarized Graph Neural Networks. ISCAS (2022)
Markus Rognlien, Zhiqiang Que, José Gabriel F. Coutinho, Wayne Luk
Hardware-Aware Optimizations for Deep Learning Inference on Edge Devices. ARC (2022)
Zhiqiang Que, Marcus Loo, Hongxiang Fan, Maurizio Pierini, Alexander D. Tapper, Wayne Luk
Optimizing Graph Neural Networks for Jet Tagging in Particle Physics on FPGAs. FPL (2022)
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, Tomas E. Muller 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 Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng
Applications and Techniques for Fast Machine Learning in Science. CoRR (2021)
Martin Ferianc, Zhiqiang Que, Hongxiang Fan, Wayne Luk, Miguel Rodrigues
Optimizing Bayesian Recurrent Neural Networks on an FPGA-based Accelerator. FPT (2021)
Zhiqiang Que, Daniel Holanda Noronha, Ruizhe Zhao, Xinyu Niu, Steven J. E. Wilton, Wayne Luk
In-circuit tuning of deep learning designs. J. Syst. Archit. 118 (2021)
Hongxiang Fan, Martin Ferianc, Zhiqiang Que, He Li, Shuanglong Liu, Xinyu Niu, Wayne Luk
Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator. CoRR (2021)
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
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments. ASAP (2021)
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
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments. CoRR (2021)
Daniel Holanda Noronha, Zhiqiang Que, Wayne Luk, Steven J. E. Wilton
Flexible Instrumentation for Live On-Chip Debug of Machine Learning Training on FPGAs. FCCM (2021)
Martin Ferianc, Zhiqiang Que, Hongxiang Fan, Wayne Luk, Miguel Rodrigues
High-Performance FPGA-based Accelerator for Bayesian Recurrent Neural Networks. CoRR (2021)
Hongxiang Fan, Martin Ferianc, Shuanglong Liu, Zhiqiang Que, Xinyu Niu, Wayne Luk
Optimizing FPGA-Based CNN Accelerator Using Differentiable Neural Architecture Search. ICCD (2020)
Zhiqiang Que, Yongxin Zhu, Hongxiang Fan, Jiuxi Meng, Xinyu Niu, Wayne Luk
Mapping Large LSTMs to FPGAs with Weight Reuse. J. Signal Process. Syst. 92 (9) (2020)
Zhiqiang Que, Hiroki Nakahara, Hongxiang Fan, Jiuxi Meng, Kuen Hung Tsoi, Xinyu Niu, Eriko Nurvitadhi, Wayne Luk
A Reconfigurable Multithreaded Accelerator for Recurrent Neural Networks. FPT (2020)
Hiroki Nakahara, Zhiqiang Que, Wayne Luk
High-Throughput Convolutional Neural Network on an FPGA by Customized JPEG Compression. FCCM (2020)
Zhiqiang Que, Daniel Holanda Noronha, Ruizhe Zhao, Xinyu Niu, Steven J. E. Wilton, Wayne Luk
Towards Overlay-based Rapid In-Circuit Tuning of Deep Learning Designs. FPT (2020)
Hiroki Nakahara, Zhiqiang Que, Akira Jinguji, Wayne Luk
R2CNN: Recurrent Residual Convolutional Neural Network on FPGA. FPGA (2020)
Zhiqiang Que, Hiroki Nakahara, Eriko Nurvitadhi, Hongxiang Fan, Chenglong Zeng, Jiuxi Meng, Xinyu Niu, Wayne Luk
Optimizing Reconfigurable Recurrent Neural Networks. FCCM (2020)
Zhiqiang Que, Thomas Nugent, Shuanglong Liu, Li Tian, Xinyu Niu, Yongxin Zhu, Wayne Luk
Efficient Weight Reuse for Large LSTMs. ASAP (2019)
Hongxiang Fan, Cheng Luo, Chenglong Zeng, Martin Ferianc, Zhiqiang Que, Shuanglong Liu, Xinyu Niu, Wayne Luk
F-E3D: FPGA-based Acceleration of an Efficient 3D Convolutional Neural Network for Human Action Recognition. ASAP (2019)
Shijin Song, Zhiqiang Que, Junjie Hou, Sen Du, Yuefeng Song
An efficient convolutional neural network for small traffic sign detection. J. Syst. Archit. 97 (2019)
Zhiqiang Que, Daniel Holanda Noronha, Ruizhe Zhao, Steven J. E. Wilton, Wayne Luk
Towards In-Circuit Tuning of Deep Learning Designs. ICCAD (2019)
Zhiqiang Que, Yanyang Liu, Ce Guo, Xinyu Niu, Yongxin Zhu, Wayne Luk
Real-Time Anomaly Detection for Flight Testing Using AutoEncoder and LSTM. FPT (2019)
Daniel Holanda Noronha, Ruizhe Zhao, Zhiqiang Que, Jeffrey Goeders, Wayne Luk, Steven J. E. Wilton
An Overlay for Rapid FPGA Debug of Machine Learning Applications. FPT (2019)
Peng Xiong, Yonxin Zhu, Zhanrui Sun, Zihao Cao, Menglin Wang, Yu Zheng, Junjie Hou, Tian Huang, Zhiqiang Que
Application of Transfer Learning in Continuous Time Series for Anomaly Detection in Commercial Aircraft Flight Data. SmartCloud (2018)
Zhanrui Sun, Yongxin Zhu, Yu Zheng, Hao Wu, Zihao Cao, Peng Xiong, Junjie Hou, Tian Huang, Zhiqiang Que
FPGA Acceleration of LSTM Based on Data for Test Flight. SmartCloud (2018)
Hongxiang Fan, Ho-Cheung Ng, Shuanglong Liu, Zhiqiang Que, Xinyu Niu, Wayne Luk
Reconfigurable Acceleration of 3D-CNNs for Human Action Recognition with Block Floating-Point Representation. FPL (2018)
Hongxiang Fan, Shuanglong Liu, Martin Ferianc, Ho-Cheung Ng, Zhiqiang Que, Shen Liu, Xinyu Niu, Wayne Luk
A Real-Time Object Detection Accelerator with Compressed SSDLite on FPGA. FPT (2018)
Shuanglong Liu, Chenglong Zeng, Hongxiang Fan, Ho-Cheung Ng, Jiuxi Meng, Zhiqiang Que, Xinyu Niu, Wayne Luk
Memory-Efficient Architecture for Accelerating Generative Networks on FPGA. FPT (2018)
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
Reconfigurable Hardware Generation for Tensor Flow Models of CNN Algorithms on a Heterogeneous Acceleration Platform. SmartCom (2018)
Zhiqiang Que, Yongxin Zhu, Xuan Wang, Jibo Yu, Tian Huang, Zhe Zheng, Li Yang, Feng Zhao, Yuzhuo Fu
Implementing Medical CT Algorithms on Stand-alone FPGA Based Systems Using an Efficient Workflow with SysGen and Simulink. CIT (2010)
Zhe Zheng, Yongxin Zhu, Xu Wang, Zhiqiang Que, Tian Huang, Xiaojing Yin, Hui Wang, Guoguang Rong, Meikang Qiu
Revealing Feasibility of FMM on ASIC: Efficient Implementation of N-Body Problem on FPGA. CSE (2010)
Zhiqiang Que, Yongxin Zhu, Tingting Mo, Bin Chen, Zhijun Li
Design and Implementation of a Cordless Power Supply System for Pervasive Medical Devices. ICESS (2009)