支天 - 中国科学院大学 - 计算机科学与技术学院

个人简介

招生专业 081201-计算机系统结构招生方向集成电路设计可重构计算教育背景 2009-09--2014-06 中国科学院电子学研究所硕博连读，获得工学博士学位工作经历 2020年9月—今：中国科学院计算技术研究所，高级工程师 2017年7月—2020年9月：中国科学院计算技术研究所，工程师 2014年7月—2017年6月：中国科学院计算技术研究所，博士后教授课程智能计算机基础及应用专利与奖励 [1] 赵永威,支天,杜子东,陈云霁,孙凝晖,郭崎。用于智能处理器的控制系统、方法及电子设备，中国，201911335142.2，实审。 [2] 支天,赵永威,李威,张士锦,杜子东,郭崎。用于智能处理器的指令分解方法、装置及电子设备，中国，201911335857.8，实审。支天,赵永威,李威,张士锦,杜子东,郭崎。用于智能处理器的内存管理装置、方法及电子设备，中国，202010492049.9，申请提交奖励信息（1） 2020年度中科院计算所卓越之星, 特等奖, 研究所（学校）, 2020 科研活动作为课题负责人承担了中科院战略性先导专项、科技部重点项目、国家自然科学基金等7项课题。

研究领域

集成电路设计，可重构计算

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

期刊文章: [1] Zidong Du, Qi Guo, Yongwei Zhao, Tian Zhi, Yunji Chen, Zhiwei Xu: Self-Aware Neural Network Systems: A Survey and New Perspective. Proceedings of the IEEE 108(7): 1047-1067 (2020). [2] 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 Trans. Computers 69(7): 968-985 (2020). [3] 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 Trans. Computers 69(7): 998-1014 (2020). [4] Dong Han, Shengyuan Zhou, Tian Zhi, Yibo Wang, Shaoli Liu: Float-Fix: An Efficient and Hardware-Friendly Data Type for Deep Neural Network. Int. J. Parallel Program. 47(3): 345-359 (2019). [5] Yong Yu, Tian Zhi, Xuda Zhou, Shaoli Liu, Yunji Chen, Shuyao Cheng: BSHIFT: A Low Cost Deep Neural Networks Accelerator. Int. J. Parallel Program. 47(3): 360-372 (2019). [6] Zhen Li, Yuqing Wang, Tian Zhi, Tianshi Chen: A survey of neural network accelerators. Frontiers Comput. Sci. 11(5): 746-761 (2017). 会议文章： [1] 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. AAAI 2020: 4174-4181. [2] 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. CVPR 2020: 2327-2335 [3] Lei Zhang, Shengyuan Zhou, Tian Zhi, Zidong Du, Yunji Chen: TDSNN: From Deep Neural Networks to Deep Spike Neural Networks with Temporal-Coding. AAAI 2019: 1319-1326. [4] Jin Song, Yimin Zhuang, Xiaobing Chen, Tian Zhi, Shaoli Liu: Compiling Optimization for Neural Network Accelerators. APPT 2019: 15-26. [5] Weijian Du, Linyang Wu, Xiaobing Chen, Yimin Zhuang, Tian Zhi: ZhuQue: A Neural Network Programming Model Based on Labeled Data Layout. APPT 2019: 27-39. [6] Xiaobing Chen, Shaohui Peng, Luyang Jin, Yimin Zhuang, Jin Song, Weijian Du, Shaoli Liu, Tian Zhi: Partition and Scheduling Algorithms for Neural Network Accelerators. APPT 2019: 55-67. [7] Yimin Zhuang, Shaohui Peng, Xiaobing Chen, Shengyuan Zhou, Tian Zhi, Wei Li, Shaoli Liu: Deep Fusion: A Software Scheduling Method for Memory Access Optimization. NPC 2019: 277-288. [8] Xiao Zhang, Huiying Lan, Tian Zhi: Leveraging Subgraph Extraction for Performance Portable Programming Frameworks on DL Accelerators. NPC 2018: 179-184. [9] Jinhong Zhou, Shaoli Liu, Qi Guo, Xuda Zhou, Tian Zhi, Dao-Fu Liu, Chao Wang, Xuehai Zhou, Yunji Chen, Tianshi Chen: TuNao: A High-Performance and Energy-Efficient Reconfigurable Accelerator for Graph Processing. CCGrid 2017: 731-734.