| Caffeine: Towards uniformed representation and acceleration for deep convolutional neural networks C Zhang, G Sun, Z Fang, P Zhou, P Pan, J Cong IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2019 | 744 | 2019 |
| SuperYOLO: Super resolution assisted object detection in multimodal remote sensing imagery J Zhang, J Lei, W Xie, Z Fang, Y Li, Q Du IEEE Transactions on Geoscience and Remote Sensing 61, 1-15, 2023 | 213 | 2023 |
| A quantitative analysis on microarchitectures of modern CPU-FPGA platforms Y Choi, J Cong, Z Fang, Y Hao, G Reinman, P Wei Proceedings of the 53rd Annual Design Automation Conference, 109, 2016 | 194 | 2016 |
| Understanding Performance Differences of FPGAs and GPUs J Cong, Z Fang, M Lo, H Wang, J Xu, S Zhang 2018 IEEE 26th Annual International Symposium on Field-Programmable Custom …, 2018 | 175 | 2018 |
| Supporting address translation for accelerator-centric architectures Y Hao, Z Fang, G Reinman, J Cong 2017 IEEE International Symposium on High Performance Computer Architecture …, 2017 | 127 | 2017 |
| Programming and Runtime Support to Blaze FPGA Accelerator Deployment at Datacenter Scale M Huang, D Wu, CH Yu, Z Fang, M Interlandi, T Condie, J Cong Proceedings of the Seventh ACM Symposium on Cloud Computing, 456-469, 2016 | 112 | 2016 |
| When Apache Spark Meets FPGAs: A Case Study for Next-Generation DNA Sequencing Acceleration YT Chen, J Cong, Z Fang, J Lei, P Wei 8th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 16), 2016 | 106 | 2016 |
| FILM-QNN: Efficient FPGA Acceleration of Deep Neural Networks with Intra-Layer, Mixed-Precision Quantization M Sun, Z Li, A Lu, Y Li, SE Chang, X Ma, X Lin, Z Fang Proceedings of the 2022 ACM/SIGDA International Symposium on Field …, 2022 | 75 | 2022 |
| High-Throughput Lossless Compression on Tightly Coupled CPU-FPGA Platforms W Qiao, J Du, Z Fang, M Lo, MCF Chang, J Cong 2018 IEEE 26th Annual International Symposium on Field-Programmable Custom …, 2018 | 73* | 2018 |
| PARADE: A Cycle-Accurate Full-System Simulation Platform for Accelerator-Rich Architectural Design and Exploration J Cong, Z Fang, M Gill, G Reinman Proceedings of the IEEE/ACM International Conference on Computer-Aided …, 2015 | 69 | 2015 |
| Auto-ViT-Acc: An FPGA-aware automatic acceleration framework for vision transformer with mixed-scheme quantization Z Li, M Sun, A Lu, H Ma, G Yuan, Y Xie, H Tang, Y Li, M Leeser, Z Wang, ... 2022 32nd International Conference on Field-Programmable Logic and …, 2022 | 65* | 2022 |
| In-Depth Analysis on Microarchitectures of Modern Heterogeneous CPU-FPGA Platforms YK Choi, J Cong, Z Fang, Y Hao, G Reinman, P Wei ACM Transactions on Reconfigurable Technology and Systems (TRETS) 12 (1), 4, 2019 | 56 | 2019 |
| HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers P Dong, M Sun, A Lu, Y Xie, K Liu, Z Kong, X Meng, Z Li, X Lin, Z Fang, ... 2023 IEEE International Symposium on High-Performance Computer Architecture …, 2023 | 51* | 2023 |
| SyncNN: Evaluating and accelerating spiking neural networks on FPGAs S Panchapakesan, Z Fang, J Li ACM Transactions on Reconfigurable Technology and Systems 15 (4), 1-27, 2022 | 48 | 2022 |
| Programming and Synthesis for Software-defined FPGA Acceleration: Status and Future Prospects YH Lai, E Ustun, S Xiang, Z Fang, H Rong, Z Zhang ACM Transactions on Reconfigurable Technology and Systems (TRETS) 14 (4), 1-39, 2021 | 47 | 2021 |
| Best-Effort FPGA Programming: A Few Steps Can Go a Long Way J Cong, Z Fang, Y Hao, P Wei, CH Yu, C Zhang, P Zhou arXiv preprint arXiv:1807.01340, 2018 | 36 | 2018 |
| Multi-stage coordinated prefetching for present-day processors S Mehta, Z Fang, A Zhai, PC Yew Proceedings of the 28th ACM international conference on Supercomputing, 73-82, 2014 | 34 | 2014 |
| Rethinking Integer Divider Design for FPGA-Based Soft-Processors E Matthews, A Lu, Z Fang, L Shannon 2019 IEEE 27th Annual International Symposium on Field-Programmable Custom …, 2019 | 32 | 2019 |
| CPU-FPGA Coscheduling for Big Data Applications J Cong, Z Fang, M Huang, L Wang, D Wu IEEE Design & Test 35 (1), 16-22, 2018 | 32* | 2018 |
| CHIP-KNN: A Configurable and High-Performance K-Nearest Neighbors Accelerator on Cloud FPGAs A Lu, Z Fang, N Farahpour, L Shannon The International Conference on Field-Programmable Technology (FPT 2020 …, 2020 | 31 | 2020 |
Jingsheng Jason CongVolgenau Chair for Engineering Excellence, Computer Science and Electrical Engineering, UniversityVerified email at cs.ucla.edu
