| 2026 | EDBT | Understanding the Performance of Native Execution in Big Data Engines: The Good, the Bad, and How to Fix It. | Haikai Zhao, Zhenman Fang |
| 2026 | FPGA | vFPGA: Towards Sub-s Reconfiguration via 3D FPGA and Packaging Co-Design. | Nikhil K. Cherukuri, Sharad Nag, Pragnya Sudershan Nalla, Ashish K. Kola, Chetan S. Gadireddi, Kevin Dai, Jae-sun Seo, Zhenman Fang, Jeff Zhang, Yu Cao |
| 2026 | FPGA | SORCERI: Streaming Overlay Acceleration for Highly Contracted Electron Repulsion Integral Computations in Quantum Chemistry. | Philip Stachura, Xin Wu, Christian Plessl, Zhenman Fang |
| 2026 | HPCA | An Efficient and Scalable Hardware Architecture for Number Theoretic Transform on FPGA with Design Automation. | Yilan Zhu, Geng Yang, Xingyu Tian, Dilshan Kumarathunga, Liang Kong, Xianglong Deng, Shengyu Fan, Guang Fan, Guiming Shi, Lei Chen, Bo Zhang, Yisong Chang, Shoumeng Yan, Zhenman Fang, Mingzhe Zhang |
| 2025 | FCCM | AutoNTT: Automatic Architecture Design and Exploration for Number Theoretic Transform Acceleration on FPGAs. | Dilshan Kumarathunga, Qilin Hu, Zhenman Fang |
| 2025 | ICCAD | Perturbation-efficient Zeroth-order Optimization for Hardware-friendly On-device Training. | Qitao Tan, Sung-En Chang, Rui Xia, Huidong Ji, Chence Yang, Ci Zhang, Jun Liu, Zheng Zhan, Zhenman Fang, Zhuo Zou, Yanzhi Wang, Jin Lu, Geng Yuan |
| 2024 | DCC | Learned Image Compression with Dual-Branch Encoder and Conditional Information Coding. | Haisheng Fu, Feng Liang, Jie Liang, Zhenman Fang, Guohe Zhang, Jingning Han |
| 2024 | ECCV | WeConvene: Learned Image Compression with Wavelet-Domain Convolution and Entropy Model. | Haisheng Fu, Jie Liang, Zhenman Fang, Jingning Han, Feng Liang, Guohe Zhang |
| 2024 | FPGA | HiSpMV: Hybrid Row Distribution and Vector Buffering for Imbalanced SpMV Acceleration on FPGAs. | Manoj B. Rajashekar, Xingyu Tian, Zhenman Fang |
| 2024 | FPGA | E4SA: An Ultra-Efficient Systolic Array Architecture for 4-Bit Convolutional Neural Networks. | Geng Yang, Jie Lei, Zhenman Fang, Jiaqing Zhang, Junrong Zhang, Weiying Xie, Yunsong Li |
| 2024 | FPL | BitBlender: Scalable Bloom Filter Acceleration on FPGAs with Dynamic Scheduling. | Kenneth Liu, Alec Lu, Zhenman Fang |
| 2024 | FPL | SERI: High-Throughput Streaming Acceleration of Electron Repulsion Integral Computation in Quantum Chemistry using HBM-based FPGAs. | Philip Stachura, Guanyu Li, Xin Wu, Christian Plessl, Zhenman Fang |
| 2024 | FPL | FORC: A High-Throughput Streaming FPGA Accelerator for Optimized Row Columnar File Decoders in Big Data Engines. | Abdul Wadood, Alec Lu, Ken Zhang, Zhenman Fang |
| 2024 | FPL | SA4: A Comprehensive Analysis and Optimization of Systolic Array Architecture for 4-bit Convolutions. | Geng Yang, Jie Lei, Zhenman Fang, Jiaqing Zhang, Junrong Zhang, Weiying Xie, Yunsong Li |
| 2024 | FPL | SDA: Low-Bit Stable Diffusion Acceleration on Edge FPGAs. | Geng Yang, Yanyue Xie, Zhong Jia Xue, Sung-En Chang, Yanyu Li, Peiyan Dong, Jie Lei, Weiying Xie, Yanzhi Wang, Xue Lin, Zhenman Fang |
| 2024 | ICASSP | Efficient Learned Image Compression with Selective Kernel Residual Module and Channel-Wise Causal Context Model. | Haisheng Fu, Feng Liang, Jie Liang, Zhenman Fang, Guohe Zhang, Jingning Han |
| 2024 | ICS | Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision Transformers. | Zhengang Li, Alec Lu, Yanyue Xie, Zhenglun Kong, Mengshu Sun, Hao Tang, Zhong Jia Xue, Peiyan Dong, Caiwen Ding, Yanzhi Wang, Xue Lin, Zhenman Fang |
| 2023 | DATE | ESRU: Extremely Low-Bit and Hardware-Efficient Stochastic Rounding Unit Design for Low-Bit DNN Training. | Sung-En Chang, Geng Yuan, Alec Lu, Mengshu Sun, Yanyu Li, Xiaolong Ma, Zhengang Li, Yanyue Xie, Minghai Qin, Xue Lin, Zhenman Fang, Yanzhi Wang |
| 2023 | FCCM | PASTA: Programming and Automation Support for Scalable Task-Parallel HLS Programs on Modern Multi-Die FPGAs. | Moazin Khatti, Xingyu Tian, Yuze Chi, Licheng Guo, Jason Cong, Zhenman Fang |
| 2023 | FCCM | SQL2FPGA: Automatic Acceleration of SQL Query Processing on Modern CPU-FPGA Platforms. | Alec Lu, Zhenman Fang |
| 2023 | FCCM | HyBNN: Quantifying and Optimizing Hardware Efficiency of Binary Neural Networks. | Geng Yang, Jie Lei, Zhenman Fang, Yunsong Li, Jiaqing Zhang, Weiying Xie |
| 2023 | HPCA | HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers. | Peiyan Dong, Mengshu Sun, Alec Lu, Yanyue Xie, Kenneth Liu, Zhenglun Kong, Xin Meng, Zhengang Li, Xue Lin, Zhenman Fang, Yanzhi Wang |
| 2022 | DAC | Hardware-efficient stochastic rounding unit design for DNN training: late breaking results. | Sung-En Chang, Geng Yuan, Alec Lu, Mengshu Sun, Yanyu Li, Xiaolong Ma, Zhengang Li, Yanyue Xie, Minghai Qin, Xue Lin, Zhenman Fang, Yanzhi Wang |
| 2022 | DAC | FPGA-aware automatic acceleration framework for vision transformer with mixed-scheme quantization: late breaking results. | Mengshu Sun, Zhengang Li, Alec Lu, Haoyu Ma, Geng Yuan, Yanyue Xie, Hao Tang, Yanyu Li, Miriam Leeser, Zhangyang Wang, Xue Lin, Zhenman Fang |
| 2022 | DATE | FitAct: Error Resilient Deep Neural Networks via Fine-Grained Post-Trainable Activation Functions. | Behnam Ghavami, Mani Sadati, Zhenman Fang, Lesley Shannon |
| 2022 | DSD | A Majority-based Approximate Adder for FPGAs. | Behnam Ghavami, Mahdi Sajedi, Mohsen Raji, Zhenman Fang, Lesley Shannon |
| 2022 | DSD | Blind Data Adversarial Bit-flip Attack against Deep Neural Networks. | Behnam Ghavami, Mani Sadati, Mohammad Shahidzadeh, Zhenman Fang, Lesley Shannon |
| 2022 | ECCV | You Already Have It: A Generator-Free Low-Precision DNN Training Framework Using Stochastic Rounding. | Geng Yuan, Sung-En Chang, Qing Jin, Alec Lu, Yanyu Li, Yushu Wu, Zhenglun Kong, Yanyue Xie, Peiyan Dong, Minghai Qin, Xiaolong Ma, Xulong Tang, Zhenman Fang, Yanzhi Wang |
| 2022 | FCCM | TopSort: A High-Performance Two-Phase Sorting Accelerator Optimized on HBM-based FPGAs. | Weikang Qiao, Licheng Guo, Zhenman Fang, Mau-Chung Frank Chang, Jason Cong |
| 2022 | FPGA | FILM-QNN: Efficient FPGA Acceleration of Deep Neural Networks with Intra-Layer, Mixed-Precision Quantization. | Mengshu Sun, Zhengang Li, Alec Lu, Yanyu Li, Sung-En Chang, Xiaolong Ma, Xue Lin, Zhenman Fang |
| 2022 | FPL | Auto-ViT-Acc: An FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization. | Zhengang Li, Mengshu Sun, Alec Lu, Haoyu Ma, Geng Yuan, Yanyue Xie, Hao Tang, Yanyu Li, Miriam Leeser, Zhangyang Wang, Xue Lin, Zhenman Fang |
| 2021 | FPGA | LEAP: A Deep Learning based Aging-Aware Architecture Exploration Framework for FPGAs. | Behnam Ghavami, Seyed Milad Ebrahimi, Zhenman Fang, Lesley Shannon |
| 2021 | FPGA | Demystifying the Memory System of Modern Datacenter FPGAs for Software Programmers through Microbenchmarking. | Alec Lu, Zhenman Fang, Weihua Liu, Lesley Shannon |
| 2021 | FPL | MAPLE: A Machine Learning based Aging-Aware FPGA Architecture Exploration Framework. | Behnam Ghavami, Milad Ibrahimipour, Zhenman Fang, Lesley Shannon |
| 2021 | FPL | SyncNN: Evaluating and Accelerating Spiking Neural Networks on FPGAs. | Sathish Panchapakesan, Zhenman Fang, Jian Li |
| 2020 | FCCM | Algorithm-Hardware Co-design for BQSR Acceleration in Genome Analysis ToolKit. | Michael Lo, Zhenman Fang, Jie Wang, Peipei Zhou, Mau-Chung Frank Chang, Jason Cong |
| 2020 | FCCM | EASpiNN: Effective Automated Spiking Neural Network Evaluation on FPGA. | Sathish Panchapakesan, Zhenman Fang, Nitin Chandrachoodan |
| 2020 | ICCAD | Aadam: A Fast, Accurate, and Versatile Aging-Aware Cell Library Delay Model using Feed-Forward Neural Network. | Seyed Milad Ebrahimipour, Behnam Ghavami, Hamid Mousavi, Mohsen Raji, Zhenman Fang, Lesley Shannon |
| 2019 | FCCM | Rethinking Integer Divider Design for FPGA-Based Soft-Processors. | Eric Matthews, Alec Lu, Zhenman Fang, Lesley Shannon |
| 2019 | FCCM | An FPGA-Based BWT Accelerator for Bzip2 Data Compression. | Weikang Qiao, Zhenman Fang, Mau-Chung Frank Chang, Jason Cong |
| 2018 | FCCM | Understanding Performance Differences of FPGAs and GPUs. | Jason Cong, Zhenman Fang, Michael Lo, Hanrui Wang, Jingxian Xu, Shaochong Zhang |
| 2018 | FCCM | High-Throughput Lossless Compression on Tightly Coupled CPU-FPGA Platforms. | Weikang Qiao, Jieqiong Du, Zhenman Fang, Michael Lo, Mau-Chung Frank Chang, Jason Cong |
| 2018 | FPGA | K-Flow: A Programming and Scheduling Framework to Optimize Dataflow Execution on CPU-FPGA Platforms: (Abstract Only). | Jason Cong, Zhenman Fang, Yao Hu, Di Wu |
| 2018 | FPGA | Understanding Performance Differences of FPGAs and GPUs: (Abtract Only). | Jason Cong, Zhenman Fang, Michael Lo, Hanrui Wang, Jingxian Xu, Shaochong Zhang |
| 2018 | FPGA | High-Throughput Lossless Compression on Tightly Coupled CPU-FPGA Platforms: (Abstract Only). | Weikang Qiao, Jieqiong Du, Zhenman Fang, Libo Wang, Michael Lo, Mau-Chung Frank Chang, Jason Cong |
| 2018 | ISPASS | Doppio: I/O-Aware Performance Analysis, Modeling and Optimization for In-memory Computing Framework. | Peipei Zhou, Zhenyuan Ruan, Zhenman Fang, Megan Shand, David Roazen, Jason Cong |
| 2017 | FPGA | CPU-FPGA Co-Optimization for Big Data Applications: A Case Study of In-Memory Samtool Sorting (Abstract Only). | Jason Cong, Zhenman Fang, Muhuan Huang, Libo Wang, Di Wu |
| 2017 | HPCA | Supporting Address Translation for Accelerator-Centric Architectures. | Yuchen Hao, Zhenman Fang, Glenn Reinman, Jason Cong |
| 2016 | CLOUD | Programming and Runtime Support to Blaze FPGA Accelerator Deployment at Datacenter Scale. | Muhuan Huang, Di Wu, Cody Hao Yu, Zhenman Fang, Matteo Interlandi, Tyson Condie, Jason Cong |
| 2016 | DAC | A quantitative analysis on microarchitectures of modern CPU-FPGA platforms. | Young-kyu Choi, Jason Cong, Zhenman Fang, Yuchen Hao, Glenn Reinman, Peng Wei |
| 2016 | FCCM | When Spark Meets FPGAs: A Case Study for Next-Generation DNA Sequencing Acceleration. | Yu-Ting Chen, Jason Cong, Zhenman Fang, Jie Lei, Peng Wei |
| 2016 | FCCM | Energy Efficiency of Full Pipelining: A Case Study for Matrix Multiplication. | Peipei Zhou, Hyunseok Park, Zhenman Fang, Jason Cong, Andr DeHon |
| 2016 | FPGA | ARAPrototyper: Enabling Rapid Prototyping and Evaluation for Accelerator-Rich Architecture (Abstact Only). | Yu-Ting Chen, Jason Cong, Zhenman Fang, Peipei Zhou |
| 2016 | ICCAD | Caffeine: towards uniformed representation and acceleration for deep convolutional neural networks. | Chen Zhang, Zhenman Fang, Peipei Zhou, Peichen Pan, Jason Cong |
| 2015 | ICCAD | PARADE: A Cycle-Accurate Full-System Simulation Platform for Accelerator-Rich Architectural Design and Exploration. | Jason Cong, Zhenman Fang, Michael Gill, Glenn Reinman |
| 2014 | ICS | Multi-stage coordinated prefetching for present-day processors. | Sanyam Mehta, Zhenman Fang, Antonia Zhai, Pen-Chung Yew |
| 2012 | DAC | Transformer: a functional-driven cycle-accurate multicore simulator. | Zhenman Fang, Qinghao Min, Keyong Zhou, Yi Lu, Yibin Hu, Weihua Zhang, Haibo Chen, Jian Li, Binyu Zang |
| 2011 | ISPASS | A comprehensive analysis and parallelization of an image retrieval algorithm. | Zhenman Fang, Donglei Yang, Weihua Zhang, Haibo Chen, Binyu Zang |