Research Projects:
Introduction:
Demonstration of Quantum Advantage Achieved by U-LYR in QuantumFlow.

Throughout our studies in these years (2019-Now), we have built the full stack for the co-design of the AI system using AutoML. The above figure demonstrates this stack in three layers: Application, Algorithm, and Hardware (see feature works [here](../../2017/06/01/research_nnFPGA/HW_NAS.pdf)).

Members:

Weiwen Jiang
Xinyi Zhang (Ph.D. candidate @ PITT)
Qing Lu (Ph.D. candidate @ ND)
Lei Yang (Postdoc @ GWU)

Publications:
1. Automated Architecture Search for Brain-inspired Hyperdimensional Computing [arXiv]
Junhuan Yang, Yi Sheng, Sizhe Zhang, Ruixuan Wang, Kenneth Foreman, Mikell Paige, Xun Jiao, Weiwen Jiang, and Lei Yang
Work-in-Progress, 2022
2. A collaboration strategy in the mining pool for proof-of-neural-architecture consensus
Boyang Li, Qing Lu, Weiwen Jiang, Taeho Jung, Yiyu Shi
Blockchain: Research and Applications, 100089, 2022
3. A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining
Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu and Caiwen Ding
Accepted by Design Automation Conference (DAC), 2022
4. Hardware and neural architecture co-search
Sakyasingha Dasgupta, Weiwen Jiang, Yiyu Shi
PUS Patent App. 17/362,997, 2022/7
5. Hardware/Software Co-Exploration for Graph Neural Architectures on FPGAs []
Qing Lu, Weiwen Jiang, Meng Jiang, Jingtong Hu, Yiyu Shi
Proc. IEEE Computer Society Annual Symposium on VLSI(ISVLSI), 2022/7
6. The Larger The Fairer? Small Neural Networks Can Achieve Fairness for Edge Devices [arXiv]
Yi Sheng, Junhuan Yang, Yawen Wu, Kevin Mao, Yiyu Shi, Jingtong Hu, Weiwen Jiang and Lei Yang
Accepted by Design Automation Conference (DAC), 2022
7. RADARS: Memory Efficient Reinforcement Learning Aided Differentiable Neural Architecture Search
Zheyu Yan, Weiwen Jiang, Xiaobo Sharon Hu, Yiyu Shi
2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC), 128-133,
8. One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search
Bingqian Lu, Jianyi Yang, Weiwen Jiang, Yiyu Shi and Shaolei Ren,
ACM SIGMETRICS/Performance, 2022
9. Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices [arXiv]
Y. Song, W. Jiang, B. Li, P. Qi, Q. Zhuge, E. H.-M. Sha, S. Dasgupta, Y. Shi, and C. Ding
Accepted by Design Automation Conference (DAC), 2021
10. FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery
D. Manu, Y. Sheng, Junhuan Yang, Jieren Deng, Tong Geng, Ang Li, Caiwen Ding, Weiwen Jiang, Lei Yang,
Accepted by IEEE/ACM International Conference On Computer-Aided Design (ICCAD), Virtual, 2021. (Invited paper)
11. Federated Contrastive Learning for Dermatological Disease Diagnosis via On-device Learning
Y. Wu, D. Zeng, Z. Wang, Y. Sheng, L. Yang, A. James, Y. Shi, J. Hu,
Accepted by IEEE/ACM International Conference On Computer-Aided Design (ICCAD), Virtual, 2021. (Invited paper)
12. Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search
Hongwu Peng, Shiyang Chen, Zhepeng Wang, Junhuan Yang, Scott A. Weitze, Tong Geng, Ang Li, Jinbo Bi, Minghu Song, Weiwen Jiang, Hang Liu, Caiwen Ding,
Accepted by IEEE/ACM International Conference On Computer-Aided Design (ICCAD), Virtual, 2021. (Invited paper)
13. RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions
S. Chang, Y. Li, M. Sun, W. Jiang, S. Liu, Y. Wang and X. Lin,
Proc. 2021 IEEE/CVF International Conference on Computer Vision (ICCV),
14. DIAN: Differentiable Accelerator-Network Co-Search Towards Maximal DNN Efficiency
Y. Zhang, Y. Fu, W. Jiang, C. Li, H. You, M. Li, V. Chandra and Y. Lin
in Proc. of ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED),
15. A Compression-Compilation Framework for On-mobile Real-time BERT Applications
W. Niu, Z. Kong, G. Yuan, W. Jiang, J. Guan, C. Ding, P. Zhao, S. Liu, B. Ren, Y. Wang
Demo Paper at International Joint Conference on Artificial Intelligence (IJCAI-21),
16. Work in Progress: Mobile or FPGA? A Comprehensive Evaluation on Energy Efficiency and a Unified Optimization Framework
G. Yuan, P. Dong, M. Sun, W. Niu, Z. Li, Y. Cai, J. Liu, W. Jiang, X. Lin, B. Ren, X. Tang, Y. Wang
IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), Virtual, May. 2021.
17. Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning
H Peng, S Huang, T Geng, A Li, W. Jiang, H Liu, S Wang, C Ding
in Proc. of International Symposium on Quality Electronic Design (ISQED),
18. Achieving Full Parallelism in LSTM via a Unified Accelerator Design
X. Zhang, W. Jiang, J. Hu
IEEE International Conference on Computer Design (ICCD2020@Online), Oct. 2020.
(acceptance rate 62/221=28.1%)
19. Hardware Design and the Competency Awareness of a Neural Network
Y. Ding, W. Jiang, Q. Lou, J. Liu, J. Xiong, X. Sharon Hu, X. Xu, and Y. Shi,
Nature Electronics, Aug. 2020 (in print)
20. Standing on the Shoulders of Giants: Hardware and Neural Architecture Co-Search with Hot Start [arXiv]
W. Jiang, L. Yang, S. Dasgupta, J. Hu and Y. Shi
International Conference on Hardware/Software Co-design and System Synthesis CODE+ISSS) in ESWEEK'20
(acceptance rate 94/375=25.1%)
also appears at IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Virtaul Conference, Oct. 2020.
21. Towards Cardiac Intervention Assistance: Hardware-Aware Neural Architecture Exploration for Real-Time 3D Cardiac Cine MRI Segmentation
D. Zeng, W. Jiang, T. Wang, X. Xu, H. Yuan, M. Hung, J. Zhuang, J. Hu and Y. Shi,
Proc. IEEE/ACM International Conference On Computer-Aided Design (ICCAD), Virtual, 2020. (Invited paper)
22. Device-Circuit-Architecture Co-Exploration for Computing-in-Memory Neural Accelerators [arXiv]
W. Jiang, Q. Lou, Z. Yan, L. Yang, J. Hu, X. S. Hu and Y. Shi
IEEE Transactions on Computers (TC), Accepted, 2020.
23. BUNET: Blind Medical Image Segmentation Based on Secure UNET
S. Bian, X. Xu, W. Jiang, Y. Shi
in Proc. of Medical Image Computing and Computer Assisted Interventions (MICCAI), Lima, Peru, 2020.
(acceptance rate 30%)
24. MS-NAS: Multi-Scale Neural Architecture Search for Medical Image Segmentation
X. Yan, W. Jiang, Y. Shi, C. Zhuo
in Proc. of Medical Image Computing and Computer Assisted Interventions (MICCAI), Lima, Peru, 2020.
(acceptance rate 30%)
25. Hardware/Software Co-Exploration of Neural Architectures [arXiv][slides]
      (2021 IEEE Transactions on Computer-Aided Design Donald O. Pederson Best Paper Award )
W. Jiang, L. Yang, E. H.-M. Sha, Q. Zhuge, S. Gu, S. Dasgupta, Y. Shi and J. Hu
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Accepted, 2020.
26. Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks [arXiv]
L. Yang, Z. Yan, M. Li, H. Kwon, L. Lai, T. Krishana, V. Chandra, W. Jiang, and Y. Shi
Design Automation Conference (DAC), 2020.
(acceptance rate 228/992=23.0%)
27. NASS: Optimizing Secure Inference via Neural Architecture Search [arXiv]
B. Song, W. Jiang, Q. Lu, Y. Shi and T. Sato
Proc. European Conference on Artificial Intelligence (ECAI), Santiago de Compostela, June. 2020.
(acceptance rate 365/1363=26.8%)
28. Co-Exploring Neural Architecture and Network-on-Chip Design for Real-Time Artificial Intelligence (BEST PAPER NOMINATION)
L. Yang, W. Jiang, W. Liu, E. H.-M. Sha, Y. Shi and J. Hu
Proc. Asia and South Pacific Design Automation Conference (ASP-DAC), Beijing, Jan. 2020.
(acceptance rate 86/263=32.6%)
29. Achieving Super-Linear Speedup across Multi-FPGA for Real-Time DNN Inference [arXiv][slides] (BEST PAPER NOMINATION)
W. Jiang, E. H.-M. Sha, X. Zhang, L. Yang, Q. Zhuge, Y. Shi and J. Hu
International Conference on Hardware/Software Co-design and System Synthesis CODE+ISSS) in ESWEEK'19
(acceptance rate 66/243=27.2%)
also appears at ACM Transactions on Embedded Computing Systems (TECS), NYC, New York, USA, Oct. 2019.
30. Integrating Memristors and CMOS for Better AI
W. Jiang, B. Xie, C-C Liu and Y. Shi,
Nature Electronics (News and Views), Sep. 2019
31. On Neural Architecture Search for Resource-Constrained Hardware Platforms
Q. Lu, W. Jiang, X. Xiao, J. Hu and Y. Shi,
Proc. IEEE/ACM International Conference On Computer-Aided Design (ICCAD), Westminster, CO, 2019. (Invited paper)
32. When Neural Architecture Search Meets Hardware Implementation: from Hardware Awareness to Co-Design
X. Zhang, W. Jiang, Y. Shi and J. Hu,
Proc. IEEE Computer Society Annual Symposium on VLSI (ISVLSI), Miami, Florida, USA, Aug. 2019. (Invited paper)
33. Accuracy vs. Efficiency: Achieving Both through FPGA-Implementation Aware Neural Architecture Search [arXiv]
      (BEST PAPER NOMINATION)
W. Jiang, X. Zhang, E. H.-M. Sha, L. Yang, Q. Zhuge, Y. Shi, and J. Hu
Design Automation Conference (DAC), 2019.
(acceptance rate 204/815=25%)
34. Heterogeneous FPGA-based Cost-Optimal Design for Timing-Constrained CNNs
W. Jiang, E. H.-M. Sha, Q. Zhuge, L. Yang, X. Chen, and J. Hu
International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (CASES) in ESWEEK'18
(acceptance rate 67/270=24.8%)
also appear at IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Torino, Italy, Oct. 2018.
Hornors: