Department of Computer Science & Engineering,
Shanghai Jiao Tong University Office: Rm521, SEIEE Building #03, Dong Chuan Road #800, Min Hang District, Shanghai Tel: 86-21-34208232 Email: ljiang_cs AT
sjtu.edu.cn I’m recruiting Experienced system
engineers, Scholars in computer architecture, EDA and AI areas, and
self-motivated student research assistant! |
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News |
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Two papers are accepted by ICCD
2022. Congratulation to Fangxin Liu, Zongwu Wang, Xuan Zhang and others. |
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Short Bio |
Li
Jiang received the B.S. degree from the Dept. of CS&E, Shanghai Jiao Tong
University in 2007, the MPhil, and the Ph.D. degree from the Dept. of
CS&E, the Chinese University of Hong Kong in 2010 and 2013, respectively.
He
has been working on Computer Architecture and Design Automation for years.
His research interests are Domain Specific Architecture for emerging
applications, e.g., AI, database and Networking, emerging computer
architecture such as compute-in-memory, near-data processing and etc. He has published more than 80 peer-review papers
in top-tier computer architecture, EDA and AI/Database conferences and
journals, including ISCA, MICRO, DAC, ICCAD, AAAI, ICCV, SigIR,
TC, TCAD, TPDS and etc. He received the Best Paper
Award in DATE’22, Best Paper Nomination in ICCAD10, and DATE21. According to the
IEEE Digital Library, five articles ranked in the top 5 of citations of all
papers collected at its conferences. Some of the achievements have been
introduced into the IEEE P1838 standard, and several technologies have been
in commercial use in cooperation with TSMC, Huawei, and Alibaba. He
got the best Ph.D. Dissertation award in ATS 2014, and he was in the final
list of TTTC’s E. J. McCluskey Doctoral Thesis Award. He received ACM Shanghai Rising
Star award and CCF VLSI early career award in 2019. He received the 2nd
class prize of Wu Wenjun Award for Artificial Intellegence.
He serves as co-chair and TPC member in several international and national
conferences, such as MICRO, DATE, ASP-DAC, ITC-Asia, ATS, CFTC, CTC, etc. He
is an Associate Editor of IET Computers Digital Techniques, VLSI, the
Integration Journal. He is the co-founder of ChinaDA
and ACM/SigDA East China Branch. |
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Research Interest |
- Near Data Processing, Compute-in-memory, Neuromorphic
Computing - Domain Specific Architecture for AI, Database,
networking etc. - AI compiling framework |
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Teaching |
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CS308 Compiler Principles (2015-2017, 2021, 2022) -
CS427 Multicore Architecture and Parallel
Programming (2014-2016,2021) -
CS222 Algorithm Design and Analysis (2018-2020) -
CS339 Computer Networks (2014-2016) |
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Honor |
- Best Paper Award (Test & Dependability
Track), 2022 - Wu Wenjun Award for Artificial Intelligence, 2nd
class, 2021 - CCF Distinguished Lecturer, 2020 - CCF VLSI Early Career Award, 2019 - ACM Shanghai Rising Star Award, 2019 - Youth sailing program of excellence in science
and technology, 2015 - IEEE TTTC Doctoral Thesis Award Semi-final, Asian
Test Symposium, Best Thesis Award (Rank 1), Nov. 2014 - CCF-Tecent
"rhino bird" creativity award fund - Nominated for Best Paper Award, IEEE/ACM
International Conference on Computer-Aided Design (ICCAD) 2010 - Certificate of Merit for Excellent Teaching
Assistant Department of CS&E, CUHK, Hongkong SAR 2010 - Outstanding graduate of colleges and
universities in Shanghai, China 2007 |
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Publication |
My DBLP,Google
Scholar,IEEE and ACM profile Recent Publication: Transactions
and Journals 2022 [1]. Fangxin Liu,Zongwu
Wang,Yongbiao Chen, Zhezhi
He, Tao Yang, Xiaoyao Liang, and Li Jiang*, “SoBS-X:Squeeze-Out Bit Sparsity for ReRAM-Crossbar-Based Neural Network Accelerator”, accepted by IEEE Transactions on Computer-Aided Design of
Integrated Circuits and Systems(TCAD), 2022 (CCF-A) [2]. Tao Yang,Dongyue Li,Fei Ma,Zhuoran Song,Yilong Zhao,Jiaxi Zhang,Fangxin Liu and Li
Jiang*, “PASGCN: An ReRAM-Based PIM Design
for GCN with Adaptively Sparsified Graphs”, accepted by IEEE Transactions on Computer-Aided Design of
Integrated Circuits and Systems(TCAD), 2022 (CCF-A) [3].
Weidong
Cao, Yilong Zhao, (CO-first author), Boloor Adith Jagadish, Yinhe Han, Xuan Zhang*, Li Jiang*, “Neural-PIM: Efficient Processing-In-Memory with Neural
Approximation of Peripherals”, accepted by IEEE
Transactions on Computers (TC), Accepted, 2022 (CCF-A) [4]. Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Tao Yang and Li Jiang*, “SSTDP: Supervised Spike Timing Dependent
Plasticity for Efficient Spiking Neural Network Training”, accepted by
Frontiers in Neuroscience, section Neuromorphic Engineering, 2022 [5]. Fangxin Liu, Wenbo
Zhao, Zongwu Wang, Yilong
Zhao, Tao Yang, Yiran Chen and Li Jiang*, “IVQ: In-Memory Acceleration of DNN
Inference Exploiting Varied Quantization“, IEEE
Transactions on Computer-Aided Design of Integrated Circuits and Systems(TCAD), 2022 (CCF-A) Peered-review
Conferences 2022 [6]. Fangxin
Liu, Zongwu Wang, and Li Jiang*, “Irregular
and Match: A Co-Design Framework for Energy Efficient Processing in Spiking
Neural Networks”, to appear in IEEE International Conference on
Computer Design, 2022 (CCF-B) [7]. Xuan
Zhang, Zhuoran Song, Xing Li, Linan
Yang, Qijun Zhang, Zhezhi
He, Li Jiang, Naifeng Jing and Xiaoyao Liang*, “IHAA: An Item-Hotness-Aware
RRAM-based Accelerator for Recommendation Model”, to appear in IEEE
International Conference on Computer Design, 2022 (CCF-B) [8].
Zhi
Li, Yanan Sun, Zhezhi He,
Liukai Xu, Li Jiang*, “CIM-ISP: Computing In-Memory for Image Signal Processing”, Proceedings of Asia and South Pacific Design Automation
Conference (ASP-DAC), Japan, 2022 (CCF-C) [9]. Qidong Tang, Zhezhi He, Fangxin Liu, Zongwu Wang, Yiyuan Zhou, Yinghuan Zhang, Li
Jiang*, "HAWIS: Hardware-Aware Automated WIdth
Search for Accurate, Energy-Efficient and Robust Binary Neural Network on
ReRAM Dot-Product Engine," 27th Asia and South Pacific Design Automation
Conference (ASP-DAC), 2022, pp. 226-231 (CCF-C) [10].
Yu Gong, Zhihan
Xu, Zhezhi He, Weifeng
Zhang, Xiaobing Tu, Xiaoyao
Liang, Li Jiang*, “N3H-Core:
Neuron-designed Neural Network Accelerator via FPGA-based Heterogeneous
Computing Cores”, Proceedings of the 2022
ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA),
February 2022, Pages 112–122 (CCF-B) [11].
Fangxin
Liu,Haomin Li,Xiaokang Yang,Li Jiang*,
“L3E-HD: A
Framework Enabling Efficient Ensemble in High-Dimensional Space for Language
Tasks”,International Conference on
Research and Development in Information Retrieval (SIGIR), 2022 (CCF-A) [12].
Fangxin
Liu, Wenbo Zhao, Zongwu Wang,Qidong Tang, Yongbiao Chen,Zhezhi He,Naifeng Jing,Xiaoyang Liang and Li Jiang*, “EBSP: Evolving Bit Sparsity Patterns
for Hardware-Friendly Inference of Quantized Deep Neural Networks”, ACM/IEEE Design Automation Conference (DAC), 2022 (CCF-A) [13].
Fangxin
Liu, Wenbo Zhao, Zongwu
Wang, Yongbiao Chen, Tao Yang, Zhezhi
He, Xiaokang Yang and Li Jiang*,
“SATO: Spiking
Neural Network Acceleration via Temporal-Oriented Dataflow and Architecture”, ACM/IEEE Design Automation Conference (DAC), 2022 (CCF-A) [14].
Fangxin
Liu, Wenbo Zhao, Yongbiao
Chen, Zongwu Wang, Zhezhi
He, Rui Yang, Qidong Tang, Tao Yang, Cheng Zhuo and Li Jiang*, ”PIM-DH: ReRAM-based Processing-in-Memory Architecture for Deep
Hashing Acceleration”, ACM/IEEE Design
Automation Conference (DAC), 2022 (CCF-A) [15].
Fangxin
Liu,Wenbo Zhao, Zongwu
Wang,Yongbiao Chen, Li Jiang*, “SpikeConverter:
An Efficient Conversion Framework Zipping the Gap between Artificial Neural
Networks and Spiking Neural Networks”,
Association for the Advancement of Artificial Intelligence(AAAI), 2022
(CCF-A) [16].
Tao Yang, Dongyue
Li, Zhuoran Song, Yilong
Zhao, Fangxin Liu, Zongwu
Wang, Zhezhi He and Li Jiang*, “DTQAtten: Leveraging Dynamic Token-based Quantization for Efficient
Attention Architecture”, Design Automation
& Test in Europe Conference & Exhibition (DATE), 2022 (CCF-B) [17].
Zongwu
Wang, Zhezhi He, Rui Yang, Shiquan
Fan, Jie Lin, Fangxin
Liu, Yueyang Jia, Chenxi
Yuan, Qidong Tang, and Li Jiang*, “Self-Terminated Write of
Multi-Level Cell ReRAM for Efficient Neuromorphic Computing”, Design Automation & Test in Europe Conference &
Exhibition (DATE), 2022 (CCF-B) (Best
Paper Award) |
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Finished Project |
1. 国家自然科学基金青年项目、“单体三维碳纳米晶体管存储器的容错技术研究与实现”、2017/01-2019/12、主持。 2. 国家重点研发计划,“信息产品及科技服务集成化众测服务平台研发与应用”、参与(校内主持),2019/01-2021/12 3. 上海交通大学重点前瞻布局基金,“忆阻器阵列芯片”,2020-2021、主持 4. 上海市青年科技英才扬帆计划、“基于碳纳米管技术的计算机体系架构探索与研究”、2015/01-2017/12、主持 5. 上海市自然科学基金探索类项目、“适合在线学习的类脑芯片计算架构”、2018/01-2021/7、主持 6. 中兴通讯产学研合作项目,“低能耗CNN深度学习图像识别算法”,主持,2018-2020 7. 阿里巴巴AIR横向课题,“分布式系统IO性能问题检测与定位”,参与,2019-2020 8. 阿里巴巴AIR横向课题、“A LSTM-Recurrent
Generative Adversarial Network (RGAN) based Health-Status Analysis for
Distributed System”、主持, 2018-2019 9. 阿里巴巴AIR横向课题,“基于样本与特征增强的大规模数据中心内存故障预测”,主持,2019-2020 10. 阿里巴巴AIR横向课题,“针对资源受限架构的DNN模型压缩技术”,
主持,2019-2020 11. 华为横向课题,“基于ReRAM的高效可靠DNN加速器技术研究”, 2019-2020,主持 12. 华为横向课题,“端侧稀疏化深度神经网络训练框架”, 2019-2020、主持 13. 华为智库专家, 2019-2020 14. 华为横向课题,“低延迟SoC通信协议评估与优化”,
2019-2020、主持 15. Intel Gift, DNN
acceleration with heterogeneous computing, 2020 |
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On-Going Project |
1.
国家自然科学基金重点项目、“集成电路近似计算基础理论与设计方法”
、2019/01-2022/12、子课题负责人 2.
华为横向课题,“近cache计算架构”,2021-2022、主持 3.
华为横向课题,“光通信存算一体架构与电路研究”, 2021-2022、主持 4.
华为横向课题,“稀疏AI框架研究”, 2021-2022、主持 5.
横向课题,“存搜一体架构研究”,2022-2023、主持 |
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Research Group |
Current: PhD: Fangxin Liu; Tao
Yang; Zongwu Wang; Ning Yang; Shiyuan
Huang. Master: Yiyuan Zhou; Qidong Tang; Feng Xu; Hui Ma. Research Assistant: Yilong
Zhao, Haomin Li, Peng Xu, Yifan
Wen. Collaborators @ SJTU team: @Dept. of CSE Zhezhi He (Assistant Professor), Zhuoran Song
(Assistant Professor), and Xiaoyao Liang
(Professor) @ Dept. of ME Yanan Sun (Associate Professor), Yaoyao Ye
(Associate Professor), Naifeng Jing (Associate
Professor) @ Joint Institute Rui Yang (Assistant Professor), Weikang Qian (Associate Professor) Alumni: Graduated in 2022: Tian Li (Huawei), Yunyan Hong (ByteDance) Graduated in 2021: Zhuoran
Song(co-supervised, first position, Assistant
Professor @ SJTU) Graduated in 2020: Xiaoyi
Sun (AntGroup), Xingyi
Wang (ByteDance), Yilong
Zhao (Shanghai Qizhi Research Institute), Chaoqun Chu (Megvii) Graduated in 2019: Zishan Jiang (SenseTime); Chengwen Xu(NVIDIA); Graduated in 2018: Jun Li (miHoYo);
Hao Dong (A finance company -_-!); Yi Liu (DJI); Lerong
Chen (Entrepreneurship); Tianjian Li (First
Position Sensetime) Graduated in 2017: Feng Xie,
Xiangyu Wu (First Position: Google), Xiangwei Huang Graduated in 2016: Yihuang
Huang (Netease Games), Hao Chen (UT-Austin), Mengyun Liu (Duke), Wenkang Yu
(UCSD), Jiawen Li (UCLA), Xiangyu
Bi (UT-Austin), Yan Han, Chengkai Zhu (UCSD) |
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Research Activity |
Chair: TPC chair in CFTC2021, General Chair in ChinaDA, Tutorial Chair in ITC-Asia, Workshop Chair in
CTC/CFTC Associate Editor: IET Journal on Computers &
Digital Techniques TPC Member: Design Automation and Test in Europe
Conference (DATE); Asia and South Pacific Design Automation Conference
(ASP-DAC); Asian Test Symposium (ATS); 3D-Test workshop; IEEE/ACM
International Symposium on Nanoscale Architectures (NANOARCH), IEEE Computer
Society Annual Symposium on VLSI (ISVLSI), IEEE Microarchitecture (MICRO) Reviewer: IEEE Transaction on CAD of Integrated
Circuits and Systems (TCAD), IEEE Transactions on Very Large
Scale Integration (VLSI) Systems (TVLSI), IEEE Transactions on
Computer (TC), ACM/IEEE Design Automation Conference (DAC), Asian Test
Symposium conference (ATS). |