Xiaofan Zhang
Orcid: 0000-0001-5081-3972Affiliations:
- University of Illinois Urbana-Champaign, IL, USA
According to our database1,
Xiaofan Zhang
authored at least 36 papers
between 2017 and 2023.
Collaborative distances:
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Bibliography
2023
Augmenting Hessians with Inter-Layer Dependencies for Mixed-Precision Post-Training Quantization.
CoRR, 2023
Mixed Precision Post Training Quantization of Neural Networks with Sensitivity Guided Search.
CoRR, 2023
2022
IEEE Trans. Circuits Syst. II Express Briefs, 2022
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022
CoRR, 2022
AutoDistill: an End-to-End Framework to Explore and Distill Hardware-Efficient Language Models.
CoRR, 2022
Proceedings of the IEEE International Symposium on Smart Electronic Systems, 2022
2021
IEEE Trans. Parallel Distributed Syst., 2021
CoRR, 2021
Being-ahead: Benchmarking and Exploring Accelerators for Hardware-Efficient AI Deployment.
CoRR, 2021
Exploring HW/SW Co-Optimizations for Accelerating Large-scale Texture Identification on Distributed GPUs.
Proceedings of the ICPP 2021: 50th International Conference on Parallel Processing, Lemont, IL, USA, August 9, 2021
Scaling Up Hardware Accelerator Verification using A-QED with Functional Decomposition.
Proceedings of the Formal Methods in Computer Aided Design, 2021
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021
2020
SkyNet: a Hardware-Efficient Method for Object Detection and Tracking on Embedded Systems.
Proceedings of Machine Learning and Systems 2020, 2020
DNNExplorer: A Framework for Modeling and Exploring a Novel Paradigm of FPGA-based DNN Accelerator.
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020
Proceedings of the GLSVLSI '20: Great Lakes Symposium on VLSI 2020, 2020
Proceedings of the FPGA '20: The 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2020
HybridDNN: A Framework for High-Performance Hybrid DNN Accelerator Design and Implementation.
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020
EDD: Efficient Differentiable DNN Architecture and Implementation Co-search for Embedded AI Solutions.
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020
2019
CoRR, 2019
T-DLA: An Open-source Deep Learning Accelerator for Ternarized DNN Models on Embedded FPGA.
Proceedings of the 2019 IEEE Computer Society Annual Symposium on VLSI, 2019
Proceedings of the International Joint Conference on Neural Networks, 2019
Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2019
FPGA/DNN Co-Design: An Efficient Design Methodology for IoT Intelligence on the Edge.
Proceedings of the 56th Annual Design Automation Conference 2019, 2019
Implementing neural machine translation with bi-directional GRU and attention mechanism on FPGAs using HLS.
Proceedings of the 24th Asia and South Pacific Design Automation Conference, 2019
2018
DNNBuilder: an automated tool for building high-performance DNN hardware accelerators for FPGAs.
Proceedings of the International Conference on Computer-Aided Design, 2018
Proceedings of the 2018 on Great Lakes Symposium on VLSI, 2018
Design Flow of Accelerating Hybrid Extremely Low Bit-Width Neural Network in Embedded FPGA.
Proceedings of the 28th International Conference on Field Programmable Logic and Applications, 2018
Proceedings of the 26th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2018
CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018
2017
Proceedings of the 2017 IEEE/ACM International Conference on Computer-Aided Design, 2017
Proceedings of the International Conference on Field Programmable Technology, 2017
High-performance video content recognition with long-term recurrent convolutional network for FPGA.
Proceedings of the 27th International Conference on Field Programmable Logic and Applications, 2017