Li Jia 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! |
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News |
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Our two papers on the Acceleration with Sparse Compilation
Optimization and Guassian Splatting have been
accepted by HPCA 2025! Congratulations to Shiyuan Huang
and others. -
Our five papers on the brain-inspired HDC and LLM acceleration
have been accepted by DATE 2025! Congratulations to Haomin
Li, Zongwu Wang, Ning Yang and others. -
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. Welcome to follow our public account！WeChat ID：gh_c7b330226334 |
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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 2nd
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. |
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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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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) |
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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, 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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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. |
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Publication |
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) |
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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 |
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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 |
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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) |
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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). |
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