Zhiqiang Que - RankMe

67 papers A* 1A 3B 3C 3Misc 3Journal 29Unranked 25

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Enhancing Trustworthiness with Mixed Precision: Benchmarks, Opportunities, and Challenges. ASP-DAC Guanxi Lu, Hao Mark Chen, Zhiqiang Que, Wayne Luk, Hongxiang Fan
2026	A	`conf`	HGQ: High Granularity Quantization for Real-time Neural Networks on FPGAs. FPGA Chang Sun, Zhiqiang Que, Thea Aarrestad, Vladimir Loncar, Jennifer Ngadiuba, Wayne Luk, Maria Spiropulu
2026	J	`jnl`	JetFormer: A Scalable and Efficient Transformer for Jet Tagging from Offline Analysis to FPGA Triggers. CoRR Ruoqing Zheng, Chang Sun, Qibin Liu, Lauri Laatu, Arianna Cox, Benedikt Maier, Alexander D. Tapper, José Gabriel F. Coutinho, Wayne Luk, Zhiqiang Que
2026	J	`jnl`	Memory-Efficient and Trustworthy Neural Networks via Random Seed-Based Design. IEEE Access Hiroaki Ito, Hikari Otsuka, Ryota Yasudo, Zhiqiang Que, José Gabriel F. Coutinho, Daichi Fujiki, Masato Motomura, Ce Guo, Wayne Luk
2026	J	`jnl`	da4ml: Distributed Arithmetic for Real-time Neural Networks on FPGAs. ACM Trans. Reconfigurable Technol. Syst. Chang Sun, Zhiqiang Que, Vladimir Loncar, Wayne Luk, Maria Spiropulu
2025	J	`jnl`	Enhancing Trustworthiness with Mixed Precision: Benchmarks, Opportunities, and Challenges. CoRR Guanxi Lu, Hao Mark Chen, Zhiqiang Que, Wayne Luk, Hongxiang Fan
2025	J	`jnl`	JEDI-linear: Fast and Efficient Graph Neural Networks for Jet Tagging on FPGAs. CoRR Zhiqiang Que, Chang Sun, Sudarshan Paramesvaran, Emyr John Clement, Katerina Karakoulaki, Christopher Brown, Lauri Laatu, Arianna Cox, Alexander D. Tapper, Wayne Luk, Maria Spiropulu
2025	J	`jnl`	Low-Latency FPGA Control System for Real-Time Neural Network Processing in CCD-Based Trapped-Ion Qubit Measurement. CoRR Binglei Lou, Gautham Duddi Krishnaswaroop, Filip Wojcicki, Ruilin Wu, Richard Rademacher, Zhiqiang Que, Wayne Luk, Philip H. W. Leong
2025	J	`jnl`	MetaML-Pro: Cross-Stage Design Flow Automation for Efficient Deep Learning Acceleration. CoRR Zhiqiang Que, José Gabriel F. Coutinho, Ce Guo, Hongxiang Fan, Wayne Luk
2025	J	`jnl`	Sub-microsecond Transformers for Jet Tagging on FPGAs. CoRR Lauri Laatu, Chang Sun, Arianna Cox, Abhijith Gandrakota, Benedikt Maier, Jennifer Ngadiuba, Zhiqiang Que, Wayne Luk, Maria Spiropulu, Alexander D. Tapper
2025	—	`conf`	Trustworthy Deep Learning Acceleration with Customizable Design Flow Automation. HEART Zhiqiang Que, Hongxiang Fan, Gabriel F. Figueiredo, Ce Guo, Wayne Luk, Ryota Yasudo, Masato Motomura
2025	J	`jnl`	da4ml: Distributed Arithmetic for Real-time Neural Networks on FPGAs. CoRR Chang Sun, Zhiqiang Que, Vladimir Loncar, Wayne Luk, Maria Spiropulu
2025	J	`jnl`	hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware. CoRR Jan-Frederik Schulte, Benjamin Ramhorst, Chang Sun, Jovan Mitrevski, Nicolò Ghielmetti, Enrico Lupi, Dimitrios Danopoulos, Vladimir Loncar, Javier M. Duarte, David Burnette, Lauri Laatu, Stylianos Tzelepis, Konstantinos Axiotis, Quentin Berthet, Haoyan Wang, Paul White, Suleyman Demirsoy, Marco Colombo, Thea Aarrestad, Sioni Summers, Maurizio Pierini, Giuseppe Di Guglielmo, Jennifer Ngadiuba, Javier Campos, Benjamin Hawks, Abhijith Gandrakota, Farah Fahim, Nhan Tran, George A. Constantinides, Zhiqiang Que, Wayne Luk, Alexander D. Tapper, Duc Hoang, Noah Paladino, Philip C. Harris, Bo-Cheng Lai, Manuel Blanco Valentin, Ryan F. Forelli, Seda Ogrenci, Lino Gerlach, Rian Flynn, Mia Liu, Daniel Diaz, Elham E Khoda, Melissa Quinnan, Russell Solares, Santosh Parajuli, Mark S. Neubauer, Christian Herwig, Ho Fung Tsoi, Dylan S. Rankin, Shih-Chieh Hsu, Scott Hauck
2024	J	`jnl`	LL-GNN: Low Latency Graph Neural Networks on FPGAs for High Energy Physics. ACM Trans. Embed. Comput. Syst. Zhiqiang Que, Hongxiang Fan, Marcus Loo, He Li, Michaela Blott, Maurizio Pierini, Alexander D. Tapper, Wayne Luk
2024	J	`jnl`	Low Latency Variational Autoencoder on FPGAs. IEEE J. Emerg. Sel. Topics Circuits Syst. Zhiqiang Que, Minghao Zhang, Hongxiang Fan, He Li, Ce Guo, Wayne Luk
2024	—	`conf`	Optimizing DNN Accelerator Compression Using Tolerable Accuracy Loss. ICFPT Zhiqiang Que, Anyan Zhao, José Gabriel F. Coutinho, Ce Guo, Wayne Luk
2024	J	`jnl`	Sets are all you need: Ultrafast jet classification on FPGAs for HL-LHC. CoRR 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
2024	—	`conf`	Trustworthy Codesign by Verifiable Transformations. ITC-Asia Qianzhou Wang, Zhiqiang Que, Wayne Luk
2024	J	`jnl`	Ultrafast jet classification at the HL-LHC. Mach. Learn. Sci. Technol. 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
2023	—	`conf`	Efficiently Removing Sparsity for High-Throughput Stream Processing. ICFPT Philippos Papaphilippou, Zhiqiang Que, Wayne Luk
2023	J	`jnl`	High-Performance Acceleration of 2-D and 3-D CNNs on FPGAs Using Static Block Floating Point. IEEE Trans. Neural Networks Learn. Syst. Hongxiang Fan, Shuanglong Liu, Zhiqiang Que, Xinyu Niu, Wayne Luk
2023	B	`conf`	MetaML: Automating Customizable Cross-Stage Design-Flow for Deep Learning Acceleration. FPL Zhiqiang Que, Shuo Liu, Markus Rognlien, Ce Guo, José Gabriel F. Coutinho, Wayne Luk
2023	J	`jnl`	MetaML: Automating Customizable Cross-Stage Design-Flow for Deep Learning Acceleration. CoRR Zhiqiang Que, Shuo Liu, Markus Rognlien, Ce Guo, José Gabriel F. Coutinho, Wayne Luk
2023	J	`jnl`	Remarn: A Reconfigurable Multi-threaded Multi-core Accelerator for Recurrent Neural Networks. ACM Trans. Reconfigurable Technol. Syst. Zhiqiang Que, Hiroki Nakahara, Hongxiang Fan, He Li, Jiuxi Meng, Kuen Hung Tsoi, Xinyu Niu, Eriko Nurvitadhi, Wayne Luk
2023	A*	`conf`	When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA. DAC Hongxiang Fan, Mark Chen, Liam Castelli, Zhiqiang Que, He Li, Kenneth Long, Wayne Luk
2023	J	`jnl`	When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA. CoRR Hongxiang Fan, Hao Chen, Liam Castelli, Zhiqiang Que, He Li, Kenneth Long, Wayne Luk
2022	J	`jnl`	Accelerating Bayesian Neural Networks via Algorithmic and Hardware Optimizations. IEEE Trans. Parallel Distributed Syst. Hongxiang Fan, Martin Ferianc, Zhiqiang Que, Xinyu Niu, Miguel R. D. Rodrigues, Wayne Luk
2022	—	`conf`	Accelerating Transformer Neural Networks on FPGAs for High Energy Physics Experiments. FPT Filip Wojcicki, Zhiqiang Que, Alexander D. Tapper, Wayne Luk
2022	—	`conf`	Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator. ASP-DAC Hongxiang Fan, Martin Ferianc, Zhiqiang Que, He Li, Shuanglong Liu, Xinyu Niu, Wayne Luk
2022	C	`conf`	Customizable FPGA-based Accelerator for Binarized Graph Neural Networks. ISCAS Ziwei Wang, Zhiqiang Que, Wayne Luk, Hongxiang Fan
2022	J	`jnl`	FPGA-Based Acceleration for Bayesian Convolutional Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Hongxiang Fan, Martin Ferianc, Zhiqiang Que, Shuanglong Liu, Xinyu Niu, Miguel R. D. Rodrigues, Wayne Luk
2022	—	`conf`	Hardware-Aware Optimizations for Deep Learning Inference on Edge Devices. ARC Markus Rognlien, Zhiqiang Que, José Gabriel F. Coutinho, Wayne Luk
2022	J	`jnl`	LL-GNN: Low Latency Graph Neural Networks on FPGAs for Particle Detectors. CoRR Zhiqiang Que, Marcus Loo, Hongxiang Fan, Michaela Blott, Maurizio Pierini, Alexander D. Tapper, Wayne Luk
2022	B	`conf`	Optimizing Graph Neural Networks for Jet Tagging in Particle Physics on FPGAs. FPL Zhiqiang Que, Marcus Loo, Hongxiang Fan, Maurizio Pierini, Alexander D. Tapper, Wayne Luk
2022	—	`conf`	Reconfigurable Acceleration of Graph Neural Networks for Jet Identification in Particle Physics. AICAS Zhiqiang Que, Marcus Loo, Wayne Luk
2022	J	`jnl`	Recurrent Neural Networks With Column-Wise Matrix-Vector Multiplication on FPGAs. IEEE Trans. Very Large Scale Integr. Syst. Zhiqiang Que, Hiroki Nakahara, Eriko Nurvitadhi, Andrew Boutros, Hongxiang Fan, Chenglong Zeng, Jiuxi Meng, Kuen Hung Tsoi, Xinyu Niu, Wayne Luk
2022	—	`conf`	Verifying Hardware Optimizations for Efficient Acceleration. HEART Qianzhou Wang, Yat Wong, Zhiqiang Que, Wayne Luk
2021	—	`conf`	Accelerating Recurrent Neural Networks for Gravitational Wave Experiments. ASAP 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
2021	J	`jnl`	Accelerating Recurrent Neural Networks for Gravitational Wave Experiments. CoRR 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
2021	J	`jnl`	Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator. CoRR Hongxiang Fan, Martin Ferianc, Zhiqiang Que, He Li, Shuanglong Liu, Xinyu Niu, Wayne Luk
2021	J	`jnl`	Applications and Techniques for Fast Machine Learning in Science. CoRR 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
2021	Misc	`conf`	Flexible Instrumentation for Live On-Chip Debug of Machine Learning Training on FPGAs. FCCM Daniel Holanda Noronha, Zhiqiang Que, Wayne Luk, Steven J. E. Wilton
2021	J	`jnl`	High-Performance FPGA-based Accelerator for Bayesian Recurrent Neural Networks. CoRR Martin Ferianc, Zhiqiang Que, Hongxiang Fan, Wayne Luk, Miguel Rodrigues
2021	J	`jnl`	In-circuit tuning of deep learning designs. J. Syst. Archit. Zhiqiang Que, Daniel Holanda Noronha, Ruizhe Zhao, Xinyu Niu, Steven J. E. Wilton, Wayne Luk
2021	—	`conf`	Optimizing Bayesian Recurrent Neural Networks on an FPGA-based Accelerator. FPT Martin Ferianc, Zhiqiang Que, Hongxiang Fan, Wayne Luk, Miguel Rodrigues
2020	—	`conf`	A Reconfigurable Multithreaded Accelerator for Recurrent Neural Networks. FPT Zhiqiang Que, Hiroki Nakahara, Hongxiang Fan, Jiuxi Meng, Kuen Hung Tsoi, Xinyu Niu, Eriko Nurvitadhi, Wayne Luk
2020	Misc	`conf`	High-Throughput Convolutional Neural Network on an FPGA by Customized JPEG Compression. FCCM Hiroki Nakahara, Zhiqiang Que, Wayne Luk
2020	J	`jnl`	Mapping Large LSTMs to FPGAs with Weight Reuse. J. Signal Process. Syst. Zhiqiang Que, Yongxin Zhu, Hongxiang Fan, Jiuxi Meng, Xinyu Niu, Wayne Luk
2020	C	`conf`	Optimizing FPGA-Based CNN Accelerator Using Differentiable Neural Architecture Search. ICCD Hongxiang Fan, Martin Ferianc, Shuanglong Liu, Zhiqiang Que, Xinyu Niu, Wayne Luk
2020	Misc	`conf`	Optimizing Reconfigurable Recurrent Neural Networks. FCCM Zhiqiang Que, Hiroki Nakahara, Eriko Nurvitadhi, Hongxiang Fan, Chenglong Zeng, Jiuxi Meng, Xinyu Niu, Wayne Luk
2020	A	`conf`	R2CNN: Recurrent Residual Convolutional Neural Network on FPGA. FPGA Hiroki Nakahara, Zhiqiang Que, Akira Jinguji, Wayne Luk
2020	—	`conf`	Towards Overlay-based Rapid In-Circuit Tuning of Deep Learning Designs. FPT Zhiqiang Que, Daniel Holanda Noronha, Ruizhe Zhao, Xinyu Niu, Steven J. E. Wilton, Wayne Luk
2019	—	`conf`	An Overlay for Rapid FPGA Debug of Machine Learning Applications. FPT Daniel Holanda Noronha, Ruizhe Zhao, Zhiqiang Que, Jeffrey Goeders, Wayne Luk, Steven J. E. Wilton
2019	J	`jnl`	An efficient convolutional neural network for small traffic sign detection. J. Syst. Archit. Shijin Song, Zhiqiang Que, Junjie Hou, Sen Du, Yuefeng Song
2019	—	`conf`	Efficient Weight Reuse for Large LSTMs. ASAP Zhiqiang Que, Thomas Nugent, Shuanglong Liu, Li Tian, Xinyu Niu, Yongxin Zhu, Wayne Luk
2019	—	`conf`	F-E3D: FPGA-based Acceleration of an Efficient 3D Convolutional Neural Network for Human Action Recognition. ASAP Hongxiang Fan, Cheng Luo, Chenglong Zeng, Martin Ferianc, Zhiqiang Que, Shuanglong Liu, Xinyu Niu, Wayne Luk
2019	—	`conf`	Real-Time Anomaly Detection for Flight Testing Using AutoEncoder and LSTM. FPT Zhiqiang Que, Yanyang Liu, Ce Guo, Xinyu Niu, Yongxin Zhu, Wayne Luk
2019	A	`conf`	Towards In-Circuit Tuning of Deep Learning Designs. ICCAD Zhiqiang Que, Daniel Holanda Noronha, Ruizhe Zhao, Steven J. E. Wilton, Wayne Luk
2018	—	`conf`	A Real-Time Object Detection Accelerator with Compressed SSDLite on FPGA. FPT Hongxiang Fan, Shuanglong Liu, Martin Ferianc, Ho-Cheung Ng, Zhiqiang Que, Shen Liu, Xinyu Niu, Wayne Luk
2018	—	`conf`	Application of Transfer Learning in Continuous Time Series for Anomaly Detection in Commercial Aircraft Flight Data. SmartCloud Peng Xiong, Yonxin Zhu, Zhanrui Sun, Zihao Cao, Menglin Wang, Yu Zheng, Junjie Hou, Tian Huang, Zhiqiang Que
2018	—	`conf`	FPGA Acceleration of LSTM Based on Data for Test Flight. SmartCloud Zhanrui Sun, Yongxin Zhu, Yu Zheng, Hao Wu, Zihao Cao, Peng Xiong, Junjie Hou, Tian Huang, Zhiqiang Que
2018	—	`conf`	Memory-Efficient Architecture for Accelerating Generative Networks on FPGA. FPT Shuanglong Liu, Chenglong Zeng, Hongxiang Fan, Ho-Cheung Ng, Jiuxi Meng, Zhiqiang Que, Xinyu Niu, Wayne Luk
2018	B	`conf`	Reconfigurable Acceleration of 3D-CNNs for Human Action Recognition with Block Floating-Point Representation. FPL Hongxiang Fan, Ho-Cheung Ng, Shuanglong Liu, Zhiqiang Que, Xinyu Niu, Wayne Luk
2018	—	`conf`	Reconfigurable Hardware Generation for Tensor Flow Models of CNN Algorithms on a Heterogeneous Acceleration Platform. SmartCom 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
2010	C	`conf`	Implementing Medical CT Algorithms on Stand-alone FPGA Based Systems Using an Efficient Workflow with SysGen and Simulink. CIT Zhiqiang Que, Yongxin Zhu, Xuan Wang, Jibo Yu, Tian Huang, Zhe Zheng, Li Yang, Feng Zhao, Yuzhuo Fu
2010	—	`conf`	Revealing Feasibility of FMM on ASIC: Efficient Implementation of N-Body Problem on FPGA. CSE Zhe Zheng, Yongxin Zhu, Xu Wang, Zhiqiang Que, Tian Huang, Xiaojing Yin, Hui Wang, Guoguang Rong, Meikang Qiu
2009	—	`conf`	Design and Implementation of a Cordless Power Supply System for Pervasive Medical Devices. ICESS Zhiqiang Que, Yongxin Zhu, Tingting Mo, Bin Chen, Zhijun Li