I am an Assistant Professor at the State Key Lab of Processors, Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS). I received my Ph.D. degree from the University of Chinese Academy of Sciences supervised by Prof. Xiaobing Feng, and received my M.S. degree and B.S. degree from the College of Computer Science and Technology, Jilin University.
I am a member of the programming languages and compilers group (led by Prof. Huimin Cui) at ICT, CAS. I am also a visiting fellow of the CORG group (led by Prof. Jingling Xue) at UNSW Sydney. My research interests lie at the intersection of programming systems and artificial intelligence. My current research focuses on programming languages, compilers, and run-time systems for emerging AI applications and accelerators. I have published 30+ papers in prestigious conferences and journals such as ASPLOS, CGO, TACO, and TCAD.

We are looking for self-motivated students in deep learning systems and compilers. Please send me an email with your CV if interested.

🔥 News

• 2024.07: 🎉 Thanks for the support of CCF-Tencent Open Fund for our research on LLM system optimization.
• 2024.01: 🎉 Our work on characterizing DNN batching systems is accepted by TBench.
• 2023.11: 🎉 LoWino is accepted by TACO (CCF-A).
• 2023.11: 🎉 MikPoly is conditionally accepted by ASPLOS 2024 (CCF-A).
• 2023.08: 🎉 CoAxNN is accepted by JSA (CCF-B).
• 2023.02: 🎉 LBPM-NAS is accepted by JSA (CCF-B).
• 2022.07: 🎉 MaskACC is accepted by Neurocomputing (CCF-C).
• 2022.05: 🎉 AppObMem is accepted by TACO (CCF-A).
• 2022.01: 🎉 FlexPruner is accepted by JSA (CCF-B).

📝 Publications

(* indicates the corresponding author)

• CCF-A ASPLOS'24 Optimizing dynamic-shape neural networks on accelerators via on-the-fly micro-kernel polymerization. Feng Yu, Guangli Li*, Jiacheng Zhao, Huimin Cui, Xiaobing Feng, Jingling Xue. International Conference on Architectural Support for Programming Languages and Operating Systems, 2024: 797–812.
• CCF-A TACO'24 Fast convolution meets low precision: Exploring efficient quantized Winograd convolution on modern CPUs. Xueying Wang, Guangli Li*, Zhen Jia, Xiaobing Feng, Yida Wang. ACM Transactions on Architecture and Code Optimization, 2024: 1-26.
• CCF-A TCAD'24 ApproxDup: Developing an approximate instruction duplication mechanism for efficient SDC detection in GPGPUs. Xiaohui Wei, Nan Jiang, Hengshan Yue, Xiaonan Wang, Jianpeng Zhao, Guangli Li, Meikang Qiu. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2024: 1051-1064.
• TBench'23 Characterizing and understanding deep neural network batching systems on GPUs. Feng Yu, Hao Zhang, Ao Chen, Xueying Wang, Xiaoxia Liang, Sheng Wang, Guangli Li*, Huimin Cui, Xiaobing Feng. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 2023: 100151.
• CCF-B JSA'23 CoAxNN: Optimizing on-device deep learning with conditional approximate neural networks. Guangli Li, Xiu Ma, Qiuchu Yu, Lei Liu, Huaxiao Liu, Xueying Wang. Journal of Systems Architecture, 2023: 102978.
• CCF-C CCF-THPC'23 FASS-pruner: Customizing a fine-grained CNN accelerator-aware pruning framework via intra-filter splitting and inter-filter shuffling. Xiaohui Wei, Xinyang Zheng, Chenyang Wang, Guangli Li, Hengshan Yue. CCF Transactions on High Performance Computing, 2023: 1-12.
• CCF-B JSA'23 Facilitating hardware-aware neural architecture search with learning-based predictive models. Xueying Wang, Guangli Li*, Xiu Ma, Xiaobing Feng. Journal of Systems Architecture, 2023, 137: 102838.
• CCF-C NEUCOM'22 Accelerating deep neural network filter pruning with mask-aware convolutional computations on modern CPUs. Xiu Ma, Guangli Li*, Lei Liu, Huaxiao Liu, Xueying Wang. Neurocomputing, 2022, 505: 375-387.
• CCF-A TACO'22 An application-oblivious memory scheduling system for DNN accelerators. Jiansong Li, Xueying Wang, Xiaobing Chen, Guangli Li*, Xiao Dong, Peng Zhao, Xianzhi Yu, Yongxin Yang, Wei Cao, Lei Liu, Xiaobing Feng. ACM Transactions on Architecture and Code Optimization, 2022: 1-26.
• CCF-B JSA'22 Optimizing deep neural networks on intelligent edge accelerators via flexible-rate filter pruning. Guangli Li, Xiu Ma, Xueying Wang, Hengshan Yue, Jiansong Li, Lei Liu, Xiaobing Feng, Jingling Xue. Journal of Systems Architecture, 2022, 124: 102431.
• CCF-B JCST'22 FlexPDA: A flexible programming framework for deep learning accelerators. Lei Liu, Xiu Ma, Huaxiao Liu, Guangli Li, and Lei Liu. Journal of Computer Science and Technology, 2022, 37(5): 1200-1220.
• CCF-B ICPP'21 LoWino: Towards efficient low-precision Winograd convolutions on modern CPUs. Guangli Li, Zhen Jia, Xiaobing Feng, Yida Wang. International Conference on Parallel Processing, 2021: 1-11.
• CCF-B CGO'21 Unleashing the low-precision computation potential of Tensor Cores on GPUs. Guangli Li, Jingling Xue, Lei Liu, Xueying Wang, Xiu Ma, Xiao Dong, Jiansong Li, Xiaobing Feng. International Symposium on Code Generation and Optimization, 2021: 90-102.
• CCF-A SC'21 G-SEPM: Building an accurate and efficient soft error prediction model for GPGPUs. Hengshan Yue, Xiaohui Wei, Guangli Li, Jianpeng Zhao, Nan Jiang, Jingweijia Tan. International Conference for High Performance Computing, Networking, Storage and Analysis, 2021: 1-15.
• CCF-C ISPA'21 Understanding the runtime overheads of deep learning inference on edge devices. Xiu Ma, Guangli Li*, Lei Liu, Huaxiao Liu, Xiaobing Feng. International Symposium on Parallel and Distributed Processing with Applications, 2021: 390-397.
• IJPP'21 Compiler-assisted operator template library for DNN accelerators. Jiansong Li, Wei Cao, Xiao Dong, Guangli Li, Xueying Wang, Peng Zhao, Lei Liu, Xiaobing Feng. International Journal of Parallel Programming, 2021: 628-645.
• CCF-A TCAD'20 Fusion-catalyzed pruning for optimizing deep learning on intelligent edge devices. Guangli Li, Xiu Ma, Xueying Wang, Lei Liu, Jingling Xue, Xiaobing Feng. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2020: 3614-3626.
• CCF-B ICASSP'20 LANCE: Efficient low-precision quantized Winograd convolution for neural networks based on graphics processing units. Guangli Li, Xueying Wang, Xiu Ma, Lei Liu, Xiaobing Feng. IEEE International Conference on Acoustics, Speech and Signal Processing, 2020: 3842-3846.
• CCF-B Euro-Par'20 Accelerating deep learning inference with cross-layer data reuse on GPUs. Xueying Wang, Guangli Li, Xiao Dong, Jiansong Li, Lei Liu and Xiaobing Feng. International European Conference on Parallel and Distributed Computing, 2020: 219-233.
• CCF-C ISPA'20 Characterizing the I/O pipeline in the deployment of CNNs on commercial accelerators. Jiansong Li, Zihan Jiang, Fangxin Liu, Xiao Dong, Guangli Li, Xueying Wang, Wei Cao, Lei Liu, Yanzhi Wang, Tao Li, Xiaobing Feng. International Symposium on Parallel and Distributed Processing with Applications, 2020: 137-144.
• Bench'19 XDN: Towards efficient inference of residual neural networks on Cambricon chips. Guangli Li, Xueying Wang, Xiu Ma, Lei Liu, Xiaobing Feng. International Symposium on Benchmarking, Measuring and Optimization, 2019: 51-56.
• CCF-B PACT'19 Acorns: A framework for accelerating deep neural networks with input sparsity. Xiao Dong, Lei Liu, Peng Zhao, Guangli Li, Jiansong Li, Xueying Wang, Xiaobing Feng. International Conference on Parallel Architectures and Compilation Techniques, 2019: 178-191.
• CCF-C ICANN'18 Auto-tuning neural network quantization framework for collaborative inference between the cloud and edge. Guangli Li, Lei Liu, Xueying Wang, Xiao Dong, Peng Zhao, Xiaobing Feng. International Conference on Artificial Neural Networks, 2018: 402-411.
• CCF-C ICANN'18 Fast CNN pruning via redundancy-aware training. Xiao Dong, Lei Liu, Guangli Li, Peng Zhao, Xiaobing Feng. International Conference on Artificial Neural Networks, 2018: 3-13.

📑 Funding and Grants

• Research on Key Technologies of Semantic-Fusion Compilation for Intelligent Application Automatic Differentiation.
  National Natural Science Foundation of China (Young Scientists Fund), PI, 2024-2026.
• Compiler Optimization for Dynamic-Shape Operators in Low-Precision Quantized LLMs
  CCF-Tencent Open Fund, PI, 2024-2025.
• Research on AI Compilation Technologies Integrating Differentiation and Approximation Characteristics.
  China Postdoctoral Science Foundation, PI, 2023-2024.
• Research on Neural Network Model Compression-Compilation Co-optimization Technologies.
  Postdoctoral Fund of SKLP (ICT, CAS), PI, 2023-2024.
• Efficient Automatic Differentiation Frameworks on AI Processors.
  CCF-Huawei Populus Grove Fund, PI, 2022-2023.
• Deep Learning Compilers based on Approximate Computing.
  CCF-Baidu Open Fund, PI, 2022-2023.

🏢 Professional Services

• Program Committee Member for IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA), 2024
• Program Committee Member for BenchCouncil International Symposium On Benchmarking, Measuring And Optimizing (Bench), 2022-2024
• Program Committee Member for International Conference on Artificial Neural Networks (ICANN), 2018
• Artifact Evaluation Committee Member for International Symposium on Code Generation and Optimization (CGO), 2022
• Journal Reviewer for IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD)
• Journal Reviewer for IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
• Journal Reviewer for IEEE Transactions on Sustainable Computing (TSUSC)
• Journal Reviewer for IEEE Transactions on Artificial Intelligence (TAI)
• Journal Reviewer for IEEE Transactions on Consumer Electronics (TCE)
• Journal Reviewer for IEEE Transactions on Industrial Informatics (TII)
• Journal Reviewer for IEEE Internet of Things Journal (IoT-J)
• Journal Reviewer for IEEE Design & Test (D&T)
• Journal Reviewer for ACM Transactions on Reconfigurable Technology and Systems (TRETS)
• Journal Reviewer for ACM Transactions on Knowledge Discovery from Data (TKDD)
• Journal Reviewer for Journal of Systems Architecture (JSA)
• Journal Reviewer for The Journal of Supercomputing (TJSC)
• Journal Reviewer for BenchCouncil Transactions on Benchmarks, Standards and Evaluations (TBench)
• Journal Reviewer for Machine Intelligence Research (MIR)
• Journal Reviewer for Knowledge-Based Systems (KBS)
• Journal Reviewer for Neural Networks
• Journal Reviewer for Neurocomputing
• Journal Reviewer for Computer Science, Excellent Peer Reviewer in 2019-2022

📖 Teaching

• Teaching Assistant, Compilers: Principles, Techniques & Tools.
  (for undergraduate students. 2018, 2020, 2022, and 2023, University of Chinese Academy of Sciences)
• Teaching Assistant, Open Innovation Experiment Project.
  (for undergraduate students. 2015 and 2016, Jilin University)
• Teaching Assistant, Compiler Construction Principle and Implementation Technique.
  (for undergraduate students. 2015, Jilin University)

🎓 Education

• 2018.09-2022.01: Ph.D. student at the University of Chinese Academy of Sciences under the supervision of Prof. Xiaobing Feng
• 2016.09-2018.06: Visiting student at ICT, CAS under the supervision of Prof. Xiaobing Feng
• 2015.09-2018.06: M.E. student at Jilin University under the supervision of Prof. Lei Liu and Prof. Shuai Lyu
• 2011.09-2015.06: B.S. student at Jilin University

✉️ Contact

• Email: liguangli [at] ict.ac.cn
• Address: No.6 Kexueyuan South Road Zhongguancun, Haidian District Beijing, China