Li Jiang   Professor 

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

Photo                              Email: ljiang_cs AT sjtu.edu.cn

I＇ｍ recruiting 3 master 's degree candidates( including Joint Postgraduate Programme with Hisilicon)

I＇ｍ recruiting Experienced  system engineers, Scholars in computer architecture, EDA and AI areas, and self-motivated student research assistant!

 News

My talk in CCFSys 2023

My talk in CCF Chips 2022

-       Our paper " Exploiting Temporal-Unrolled Parallelism for Energy-Efficient SNN Acceleration" has been accepted by IEEE Transactions on Parallel and Distributed Systems 2024! Congratulation to Fangxin Liu and others.

-       Our paper " COMPASS: SRAM-Based Computing-in-Memory SNN Accelerator with Adaptive Spike Speculation" has been accepted by MICRO 2024! Congratulation to Zongwu Wang and others.

-       Our paper " SpMMPlu-Pro: An Enhanced Compiler Plug-in for Efficient SpMM and Sparsity Propagation Algorithm" has been accepted by IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2024! Congratulation to Shiyuan Huang and others.

-       Our paper " UM-PIM: DRAM-based PIM with Uniform & Shared Memory Space" has been accepted by ISCA 2024! Congratulation to Yilong zhao and others.

-       Our paper " SPARK:Scalable and Precision-Aware Accelerationof Neural Networks via Efficient Encoding" has been accepted by HPCA 2024! Congratulation to Ning Yang 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 100 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, DATE＇23, 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 2^nd class prize of Wu Wenjun Award for Artificial Intellegence. He has been selected  the national ten thousand talents plan—top-notch young talents, 2023. 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.

Research

Interest

- Near Data Processing, Compute-in-memory, Neuromorphic Computing

- Domain Specific Architecture for AI, Database, networking etc.

- AI compiling framework

Teaching

-       CS2951 Computer System (2022，2023)

-       CS308 Compiler Principles (2015-2017, 2021, 2022)

-       CS427 Multicore Architecture and Parallel Programming (2014-2016,2021,2022)

-       CS222 Algorithm Design and Analysis (2018-2020)

-       CS339 Computer Networks (2014-2016)

Honor

- Selected The National Ten Thousand Talents Plan—Top-notch Young Talents, 2023（入选万人计划——青年拔尖人才计划）

- Wu Wen Jun Award for Artificial Intelligence, 2^nd 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

    Honor(student)

- Best Paper Award (Embedded Systems Design Track), DATE 2023. Congratulation to Zhuoran Song and others.

- Spark Award (Data-free/Label-free), Huawei, 2022. Congratulation to Fangxiu Liu.

- Best Paper Award (Test & Dependability Track), DATE 2022. Congratulation to Zongwu Wang and others.

- Best Paper Award Nomintion(E Track), DATE 2022. Congratulation to Tao Yang and others.

-National Scholarship(2021,2022)-Fangxiu Liu;

-National Scholarship(2021)-Tao Yang;

-Wu Wen Jun Honorary Doctoral Scholarship, 2021-Fangxiu Liu.

Publication

Full Publication List

My DBLP，Google Scholar，IEEE and ACM profile

Recent Publication:

Transactions and Journals

2024

[1].    Fangxin Liu, Zongwu Wang,Wenbo Zhao, Ning Yang, Yongbiao Chen,Shiyuan Huang,Haomin Li,Tao Yang,Songwen Pei,Xiaoyao Liang and Li Jiang*, “Exploiting Temporal-Unrolled Parallelism for Energy-Efficient SNN Acceleration＂, accepted by IEEE Transactions on Parallel and Distributed Systems (TPDS), 2024 (CCF-A)

[2].    Shiyuan Huang, Fangxin Liu*, Tao Yang, Zongwu Wang, Ning Yang and Li Jiang*, “SpMMPlu-Pro: An Enhanced Compiler Plug-in for Efficient SpMM and Sparsity Propagation Algorithm＂, accepted by IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2024 (CCF-A)

2023

[3].    Fangxin Liu, Wenbo Zhao, Zongwu Wang,Yongbiao Chen, Xiaoyao Liang and Li Jiang*, “ERA-BS: Boosting the Efficiency of ReRAM-based PIM Accelerator with Fine-Grained Bit-Level Sparsity＂, accepted by IEEE Transactions on Computers (TC), 2023 (CCF-A)

2022

[4].    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)

[5].    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)

[6].    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)

[7].    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

[8].    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

[9].    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)

[10]. 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)

[11]. 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)

[12]. 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)

[13]. 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)

[14]. 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)

[15]. 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)

[16]. 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)

[17]. 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)

[18]. 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)

[19]. 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)

[20]. 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)

Finished

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” 、2019/01-2023/12、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，“面向通信系统的存算一体实现研究项目”， 2021-2022、主持

4.华为横向课题，“稀疏AI框架研究”， 2021-2022、主持

5.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。

6.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

7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

8.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

9.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

10.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

11.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

12.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

13.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

14.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

15.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

16.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

17.华为智库专家， 2019-2020

18.华为横向课题，“低延迟SoC通信协议评估与优化”， 2019-2020、主持

19. Intel Gift, DNN acceleration with heterogeneous computing, 2020

On-Going

Project

1.中组部人才项目：“基于DRAM的近存计算系统架构关键技术研究”，2024-2026、主持

2.亿铸智能科技：“面向基于ReRAM忆阻器的存算一体智能芯片架构和编译器研究项目”，2021-2024、主持

3.中兴通讯：“多模型适配的高效量化压缩平台技术研究”，2024-2025、主持

4.亿咖通科技： “上海交通大学-亿咖通汽车半导体智能技术联合实验室”,2023-2025、参与

Research

Group

Current:

PhD: Zongwu Wang; Shiyuan Huang; Ning Yang; Yilong Zhao; Haoming Li; Hanjing Shen; Runpei Cai.

Master: Longyu Zhao; Peng Xu; QUENTIN KASAN TIM PATINIER; Yiwei Hu; Tianheng Wang; Gongye Chen.

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 (Associate Professor), Weikang Qian (Associate Professor)

Alumni:

Graduated in 2024: Hui Ma(Huawei),Feng Xu(Tencent)

Graduated in 2023: Fangxin Liu(Assistant Professor@SJTU), Tao Yang(Huawei's "Genius Youth" program 2023), Qidong Tang(MING HONG INVESTMENT), Yiyuan Zhou(MOORE THREADS)

Graduated in 2022: Tian Li (Huawei), Yunyan Hong (ByteDance), Hanchen Guo (ICBC)

Graduated in 2021: Zhuoran Song(co-supervised, 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), Jianfei Wang( Sensetime)

Graduated in 2018: Jun Li (miHoYo), Hao Dong (Akuna Capital),Yi Liu (DJI),Lerong Chen (Entrepreneurship),Tianjian Li ( Sensetime)

Graduated in 2017: Feng Xie (ele.me), Xiangyu Wu (Google), Xiangwei Huang(Huawei)

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)

      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).