By Last Name
GUO QiProfessor
Research Areas:
Computer Architecture;AI Computing Systems;Compilers
Department:
Intelligent Processor Research Center
Tutor Category:
Contact:
guoqi@ict.ac.cn
Personal Page:
http://novel.ict.ac.cn/qguo
Qi Guo is a full professor at Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS). He received the PhD degree from ICT in 2012. He received the B.E. degree in CS from Tongji University in 2007. From 2012 to 2014, he was a staff researcher at IBM Research. From 2014 to 2015, he was a postdoctoral researcher at Carnegie Mellon University. His research interests include computer architecture, compilation, and artificial intelligence.
Selected Publications
Conference Papers
1. Jun Bi, Qi Guo, Xiaqing Li, Yongwei Zhao, Yuanbo Wen, Yuxuan Guo, Enshuai Zhou, Xing Hu, Zidong Du, Ling Li, Huaping Chen, Tianshi Chen. Automatically constrained high-performance library generation for deep learning accelerators. In: Proceedings of International Conference on Architectural Support of for Programming Language and Operating Systems (ASPLOS), 2023. (CCF-A)
2. Yifan Hao, Yongwei Zhao, Chenxiao Liu, Shuyao Cheng, Xiaqing Li, Xing Hu, Zidong Du, Qi Guo, Zhiwei Xu, Tianshi Chen. Cambricon-P: A bitflow architecture for arbitrary precision computing. In: Proceedings of International Symposium on Microarchitecture (MICRO), 2022. (CCF-A, Best Paper Runner-Up Award)
3. Yuanbo Wen, Qi Guo, Qiang Fu, Xiaqing Li, Jianxing Xu, Yanling Tang, Yongwei Zhao, Xing Hu, Zidong Du, Ling Li, Chao Wang, Xuehai Zhou, Yunji Chen. BabelTower: Learning to auto-parellelized program translation. In: Proceedings of International Conference on Machine Learning (ICML), 2022. (CCF-A)
4. Yongwei Zhao, Chang Liu, Zidong Du, Qi Guo, Xing Hu, Yimin Zhuang, Zhenxing Zhang, Xinkai Song, Wei Li, Xishan Zhang, Ling Li, Zhiwei Xu, Tianshi Chen. Cambricon-Q: A hybrid architecture for efficient training. In: Proceedings of International Symposium on Computer Architecture (ISCA), 2021. (CCF-A)
5. Xishan Zhang, Shaoli Liu, Rui Zhang, Chang Liu, Di Huang, Shiyi Zhou, Jiaming Guo, Qi Guo, Zidong Du, Tian Zhi, Yunji Chen. Fixed-point back-propagation training. In: Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (CCF-A)
6. Di Huang, Xishan Zhang, Rui Zhang, Tian Zhi, Deyuan He, Jiaming Guo, Chang Liu, Qi Guo, Zidong Du, Shaoli Liu, Tianshi Chen, Yunji Chen. DWM: A decomposable winograd method for convolution acceleration. In: Proceedings of AAAI Conference on Artificial Intelligence (AAAI), 2020. (CCF-A)
7. Yongwei Zhao, Zidong Du, Qi Guo, Shaoli Liu, Ling Li, Zhiwei Xu, Tianshi Chen, Yunji Chen. Cambricon-F: Machine learning computers with fractal von Neumann architecture. In: Proceedings of International Symposium on Computer Architecture (ISCA), 2019. (CCF-A)
8. Xuda Zhou, Zidong Du, Qi Guo, Chengsi Liu, Chao Wang, Xuehai Zhou, Ling Li, Tianshi Chen, Yunji Chen. Cambricon-S: Addressing irregularity in sparse neural networks through a cooperative software/hardware approach. In: Proceedings of International Symposium on Microarchitecture (MICRO), 2018. (CCF-A)
9. Shijin Zhang, Zidong Du, Lei Zhang, Huiying Lan, Shaoli Liu, Ling Li, Qi Guo, Tianshi Chen, and Yunji Chen. Cambricon-X: An accelerator for sparse neural networks. In: Proceedings of International Symposium on Microarchitecture (MICRO), 2016. (CCF-A)
10. Qi Guo, Tze-Meng Low, Nikolaos Alachiotis, Berkin Akin, Larry Pileggi, James C. Hoe, and Franz Franchetti. Enabling portable energy efficiency with memory accelerated library. In: Proceedings of International Symposium on Microarchitecture (MICRO), 2015. (CCF-A)
2. Yifan Hao, Yongwei Zhao, Chenxiao Liu, Shuyao Cheng, Xiaqing Li, Xing Hu, Zidong Du, Qi Guo, Zhiwei Xu, Tianshi Chen. Cambricon-P: A bitflow architecture for arbitrary precision computing. In: Proceedings of International Symposium on Microarchitecture (MICRO), 2022. (CCF-A, Best Paper Runner-Up Award)
3. Yuanbo Wen, Qi Guo, Qiang Fu, Xiaqing Li, Jianxing Xu, Yanling Tang, Yongwei Zhao, Xing Hu, Zidong Du, Ling Li, Chao Wang, Xuehai Zhou, Yunji Chen. BabelTower: Learning to auto-parellelized program translation. In: Proceedings of International Conference on Machine Learning (ICML), 2022. (CCF-A)
4. Yongwei Zhao, Chang Liu, Zidong Du, Qi Guo, Xing Hu, Yimin Zhuang, Zhenxing Zhang, Xinkai Song, Wei Li, Xishan Zhang, Ling Li, Zhiwei Xu, Tianshi Chen. Cambricon-Q: A hybrid architecture for efficient training. In: Proceedings of International Symposium on Computer Architecture (ISCA), 2021. (CCF-A)
5. Xishan Zhang, Shaoli Liu, Rui Zhang, Chang Liu, Di Huang, Shiyi Zhou, Jiaming Guo, Qi Guo, Zidong Du, Tian Zhi, Yunji Chen. Fixed-point back-propagation training. In: Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (CCF-A)
6. Di Huang, Xishan Zhang, Rui Zhang, Tian Zhi, Deyuan He, Jiaming Guo, Chang Liu, Qi Guo, Zidong Du, Shaoli Liu, Tianshi Chen, Yunji Chen. DWM: A decomposable winograd method for convolution acceleration. In: Proceedings of AAAI Conference on Artificial Intelligence (AAAI), 2020. (CCF-A)
7. Yongwei Zhao, Zidong Du, Qi Guo, Shaoli Liu, Ling Li, Zhiwei Xu, Tianshi Chen, Yunji Chen. Cambricon-F: Machine learning computers with fractal von Neumann architecture. In: Proceedings of International Symposium on Computer Architecture (ISCA), 2019. (CCF-A)
8. Xuda Zhou, Zidong Du, Qi Guo, Chengsi Liu, Chao Wang, Xuehai Zhou, Ling Li, Tianshi Chen, Yunji Chen. Cambricon-S: Addressing irregularity in sparse neural networks through a cooperative software/hardware approach. In: Proceedings of International Symposium on Microarchitecture (MICRO), 2018. (CCF-A)
9. Shijin Zhang, Zidong Du, Lei Zhang, Huiying Lan, Shaoli Liu, Ling Li, Qi Guo, Tianshi Chen, and Yunji Chen. Cambricon-X: An accelerator for sparse neural networks. In: Proceedings of International Symposium on Microarchitecture (MICRO), 2016. (CCF-A)
10. Qi Guo, Tze-Meng Low, Nikolaos Alachiotis, Berkin Akin, Larry Pileggi, James C. Hoe, and Franz Franchetti. Enabling portable energy efficiency with memory accelerated library. In: Proceedings of International Symposium on Microarchitecture (MICRO), 2015. (CCF-A)
Journal Articles
1. Zidong Du, Qi Guo, Yongwei Zhao, Xi Zeng, Ling Li, Limin Cheng, Zhiwei Xu, Ninghui Sun, Yunji Chen. Breaking the interaction wall: A DLPU-Centric deep learning computing system. IEEE Transactions on Computers (IEEE TC) 71(1): 209-222 (2022) (CCF-A)
2. Yuanbo Wen, Qi Guo, Zidong Du, Jianxing Xu, Zhenxing Zhang, Xing Hu, Wei Li, Rui Zhang, Chao Wang, Xuehai Zhou, Tianshi Chen. Enabling one-size-fits-all compilation optimization for inference across machine learning computers. IEEE Transactions on Computers (IEEE TC) 71(9): 2313-2326 (2022) (CCF-A)
3. Xinkai Song, Tian Zhi, Zhe Fan, Zhenxing Zhang, Xi Zeng, Wei Li, Xing Hu, Zidong Du, Qi Guo, Yunji Chen. Cambricon-G: A polyvalent energy-efficient accelerator for dynamic graph neural networks. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD) 41(1): 116-128 (2022) (CCF-A)
4. Xing Hu, Ling Liang, Xiaobing Chen, Lei Deng, Yu Ji, Yufei Ding, Zidong Du, Qi Guo, Timothy Sherwood, Yuan Xie. A systematic view of model leakage risks in deep neural network systems. IEEE Transactions on Computers (IEEE TC) 71(12): 3254-3267 (2022) (CCF-A)
5. Zidong Du, Qi Guo, Tian Zhi, Yongwei Zhao, Yunji Chen, and Zhiwei Xu. Self-aware Neural Network Systems: A Survey and New Perspective. Proceedings of IEEE (PIEEE) 108(7): 1047-1067 (2020) (CCF-A)
6. Yongwei Zhao, Zhe Fan, Zidong Du, Tian Zhi, Ling Li, Qi Guo, Shaoli Liu, Zhiwei Xu, Tianshi Chen, Yunji Chen. Machine learning computers with fractal von Neumann architecture. IEEE Transactions on Computers (IEEE TC) 69(7): 998-1014 (2020) (CCF-A)
7. Xi Zeng, Tian Zhi, Xuda Zhou, Zidong Du, Qi Guo, Shaoli Liu, Bingrui Wang, Yuanbo Wen, Chao Wang, Xuehai Zhou, Ling Li, Tianshi Chen, Ninghui Sun, Yunji Chen. Addressing irregularity in sparse neural networks through a cooperative software/hardware approach. IEEE Transactions on Computers (IEEE TC) 69(7): 968-985 (2020) (CCF-A)
8. Shengyuan Zhou, Qi Guo, Zidong Du, Daofu Liu, Tianshi Chen, Ling Li, Shaoli Liu, Jinhong Zhou, Olivier Temam, Xiaobing Feng, Xuda Zhou, Yunji Chen. ParaML: A polyvalent multi-core accelerator for machine learning. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD) 39(9): 1764-1777 (2020) (CCF-A)
9. Xuda Zhou, Zidong Du, Shijin Zhang, Lei Zhang, Huiying Lan, Shaoli Liu, Ling Li, Qi Guo, Tianshi Chen, Yunji Chen. Addressing sparsity in deep neural networks. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD) 38(10): 1858-1871 (2019) (CCF-A)
10. Yunji Chen, Huiying Lan, Zidong Du, Shaoli Liu, Jinhua Tao, Dong Han, Tao Luo, Qi Guo, Ling Li, Yuan Xie, Tianshi Chen. An instruction set architecture for machine learning. ACM Transactions on Computer Systems (ACM TOCS) 36(3): 9:1-9:35 (2018) (CCF-A)
2. Yuanbo Wen, Qi Guo, Zidong Du, Jianxing Xu, Zhenxing Zhang, Xing Hu, Wei Li, Rui Zhang, Chao Wang, Xuehai Zhou, Tianshi Chen. Enabling one-size-fits-all compilation optimization for inference across machine learning computers. IEEE Transactions on Computers (IEEE TC) 71(9): 2313-2326 (2022) (CCF-A)
3. Xinkai Song, Tian Zhi, Zhe Fan, Zhenxing Zhang, Xi Zeng, Wei Li, Xing Hu, Zidong Du, Qi Guo, Yunji Chen. Cambricon-G: A polyvalent energy-efficient accelerator for dynamic graph neural networks. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD) 41(1): 116-128 (2022) (CCF-A)
4. Xing Hu, Ling Liang, Xiaobing Chen, Lei Deng, Yu Ji, Yufei Ding, Zidong Du, Qi Guo, Timothy Sherwood, Yuan Xie. A systematic view of model leakage risks in deep neural network systems. IEEE Transactions on Computers (IEEE TC) 71(12): 3254-3267 (2022) (CCF-A)
5. Zidong Du, Qi Guo, Tian Zhi, Yongwei Zhao, Yunji Chen, and Zhiwei Xu. Self-aware Neural Network Systems: A Survey and New Perspective. Proceedings of IEEE (PIEEE) 108(7): 1047-1067 (2020) (CCF-A)
6. Yongwei Zhao, Zhe Fan, Zidong Du, Tian Zhi, Ling Li, Qi Guo, Shaoli Liu, Zhiwei Xu, Tianshi Chen, Yunji Chen. Machine learning computers with fractal von Neumann architecture. IEEE Transactions on Computers (IEEE TC) 69(7): 998-1014 (2020) (CCF-A)
7. Xi Zeng, Tian Zhi, Xuda Zhou, Zidong Du, Qi Guo, Shaoli Liu, Bingrui Wang, Yuanbo Wen, Chao Wang, Xuehai Zhou, Ling Li, Tianshi Chen, Ninghui Sun, Yunji Chen. Addressing irregularity in sparse neural networks through a cooperative software/hardware approach. IEEE Transactions on Computers (IEEE TC) 69(7): 968-985 (2020) (CCF-A)
8. Shengyuan Zhou, Qi Guo, Zidong Du, Daofu Liu, Tianshi Chen, Ling Li, Shaoli Liu, Jinhong Zhou, Olivier Temam, Xiaobing Feng, Xuda Zhou, Yunji Chen. ParaML: A polyvalent multi-core accelerator for machine learning. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD) 39(9): 1764-1777 (2020) (CCF-A)
9. Xuda Zhou, Zidong Du, Shijin Zhang, Lei Zhang, Huiying Lan, Shaoli Liu, Ling Li, Qi Guo, Tianshi Chen, Yunji Chen. Addressing sparsity in deep neural networks. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD) 38(10): 1858-1871 (2019) (CCF-A)
10. Yunji Chen, Huiying Lan, Zidong Du, Shaoli Liu, Jinhua Tao, Dong Han, Tao Luo, Qi Guo, Ling Li, Yuan Xie, Tianshi Chen. An instruction set architecture for machine learning. ACM Transactions on Computer Systems (ACM TOCS) 36(3): 9:1-9:35 (2018) (CCF-A)
Awards
1. 2022 Young Scientist Award of Chinese Academy of Sciences
2. 2022 Outstanding Members of Youth Innovation Promotion Association, Chinese Academy of Sciences
3. 2022 Best Paper Runner-Up Award of MICRO
4. 2021 CAS Project for Young Scientists in Basic Research
5. 2019 Outstanding Science and Technology Achievement Prize of the Chinese Academy of Sciences
6. 2018 Members of Youth Innovation Promotion Association, Chinese Academy of Sciences
7. 2015 Young Elite Scientists Sponsorship Program by CAST, CCF Youth Talent Support Program
8. 2015 CGO Best Paper Nominee