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李洪亮


姓名:

李洪亮

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性别:

职称:

副教授

是否博导:

最高学历:

研究生

最高学位:

博士

Email

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详细情况

基本信息:

    李洪亮,博士、副教授、博士生导师,担任中国计算机学会分布式计算与系统专业委员会执行委员、容错计算专委会执行委员。于2012年在吉林大学计算机学院获得博士学位、曾于2011年在加拿大多伦多大学做访问学者、于2011年在加拿大Platform Computing   Inc.任软件工程师,于2016-2017年在美国天普大学吴杰教授课题组做博士后访问学者。曾获吉林省科技进步一等奖 1 项,中国商业联合会科技进步一等奖 1 项,所负责的“云计算技术”系列课程获批国家级一流本科课程虚拟仿真课程和吉林省一流本科课程国家,获 ACM 中国新星奖和 IBM 优秀教师奖教金等个人奖项。

主要面向云计算、数据中心和高性能计环境,研究系统资源调度和各类并行作业容错方法等,近年来主要开展大规模深度学习作业的分布式深度学习集群环境中的资源调度和容错优化研究。主持国家自然基金项目等国家级科研项目 2 项,省级科研项目 1 项,国际合作项目 1 项;参与国家级/省级科研项目 5 项等,相关成果发表论文 40 余篇(包括INFOCOMCLUSTER等顶级国际会议和TPDSJPDCJCSTFGCS等顶级国际期刊),获得国家发明专利 8 项。

教学方面主要负责云计算技术和分布式存储等系列课程的建设工作,其中云计算技术综合虚拟仿真实验课程获批国家级一流本科课程虚拟仿真课程和吉林省一流本科课程。

所研究方向:

分布式计算, 调度算法,容错,云计算

招生信息:

所在学科专业:计算机系统结构

招收博士/硕士研究生、本科实习生,欢迎同学们联系研讨。

团队新闻:

NEWS(11/2024) Our paper Convergence-aware   Optimal Checkpointing for Exploratory Deep Learning Training Jobs is accepted by Future   Generation Computer Systems (FGCS),中科院一区!

NEWS(12/2024) Our paper ArrayPipe:   Introducing Job-Array Pipeline Parallelism for High Throughput Model   Exploration. is   accepted by IEEE International Conference on Computer Communications (INFOCOM2025),CCF-A会议!

讲授课程:

云计算技术A》,计算机学院本科生选修课

云计算技术B》,计算机学院本科生限选课

《云计算技术》,软件学院本科生限选课

《分布式存储》,软件学院本科生必修课

《分布式计算和云计算》,计算机学院研究生选修课

《云计算技术》,软件学院研究生选修课

《云计算技术综合虚拟仿真实验》获国家级一流本科课程

教育经历:

2011-2011,加拿大,多伦多大学,访问学者

2009-2012,吉林大学,计算机科学与技术学院,博士

2006-2009,吉林大学,计算机科学与技术学院,硕士

2002-2006,吉林大学,计算机科学与技术学院,本科

工作经历:

2016至今,吉林大学,计算机科学与技术学院,副教授

2016-2017,美国,天普大学,博士后访问学者

2012-2016,吉林大学,计算机科学与技术学院,讲师

2011-2011,加拿大,Platform Computing   Inc.,软件工程师

科研项目:

吉林省科技厅,面上项目,在研

国家自然基金,青年科学基金,结题

国家重点研发计划项目,子课题,结题

IBM国际合作项目,结题

学术论文:

Selected   Publications

Journal   Papers

[1]  H. Li, Z.   Wang, H. Zhao, M. Zhang, X. Li, H. Xu. Convergence-aware Optimal   Checkpointing for Exploratory Deep Learning Training Jobs. Future Generation   Computer Systems (FGCS), Nov. 2024. (EA). (中科院一区)

[2]  H. Li, H.   Zhao, T. Sun, X. Li, H. Xu, K. Li. Interference-aware Opportunistic Job   Placement for Shared Distributed Deep Learning Clusters. Journal of Parallel   and Distributed Computing (JPDC), Jan. 2024. (CCF-B) DOI:10.1016/j.jpdc.2023.104776

[3]  Z. Xu, X Wei, J   Hao, J Han, H Li*, C L, Z Li, D Tian, N Zhang. DGFormer: A   Physics-Guided Station Level Weather Forecasting Model with Dynamic   Spatial-Temporal Graph Neural Network, GeoInformatica, Feb. 2024. (CCF-B)   DOI:10.1007/s10707-024-00511-1

[4]  Z. Xu, X, Wei, J.   Hao, J. Li, H. Li*, Z. Ding, S. Li. HiRM: Hierarchical Resource   Management for Earth System Models on Many-core Clusters. CCF Transactions on   High Performance Computing (THPC). Jan. 2024. (CCF-C) DOI:10.1007/s42514-023-00176-6

[5]  H. Li, J.   Wu, Z. Jiang, X. Li, X. Wei. A Task Allocation Method for Stream Processing   with Recovery Latency Guarantee. Journal of Computer Science and technology (JCST),   vol.33, no.6, pp.1125-1139, 2018.11. (CCF-B) DOI:10.1007/s11390-018-1876-6  

[6]  H. Li, J.   Wu, Z. Jiang, X. Li, X. Wei. Minimum Backups for Stream Processing with   Recovery Latency Guarantees. IEEE Transactions on Reliability, vol.66,   no.99, pp.1-12. 2017. (中科院二区) DOI:10.1109/TR.2017.2712563

[7]  X. Wei, L. Li, X.   Li, X. Wang, S. Gao. H. Li. Pec: Proactive Elastic Collaborative   Resource Scheduling in Data Stream Processing. IEEE Transactions on Parallel   and Distributed Systems (TPDS), vol. 30. No. 7, pp. 1628-1642, July 1   2019. (CCF-A) DOI:10.1109/TPDS.2019.2891587

[8]  X. Wei, Z. Xu, H.   Li, Z. Ding. Coordinated process scheduling algorithms for coupled earth   system models. Concurrency and Computation: Practice and Experience (CCPE),   e6346, Oct 25, 2021. (CCF-C)

[9]  Y. Zhuang, X. Wei,   H. Li, Y. Wang, X. He. An optimal checkpointing model with online OCI   adjustment for stream processing applications. Concurrency and Computation:   Practice and Experience (CCPE). June 10, 2019. (CCF-C) DOI:10.1002/cpe.5347

[10]  X. Wei, Y. Zhuang,   H. Li, Z. Liu. Reliable stream data processing for elastic distributed   stream processing systems. Cluster Computing. May 21, 2019. (中科院三区) DOI:10.1007/s10586-019-02939-9

[11]  W. Wei, X. Wei, H.   Li. Topology-aware Task Allocation for Online Distributed Stream Processing   Applications with Latency Constraints. Physica A: Statistical Mechanics and   its Applications. Vol. 534, Nov. 15, 2019. (中科院二区) DOI:10.1016/j.physa.2019.122024

[12]  X. Wei, H. Li,   K. Yang, L. Zou. Topology-aware Partial Virtual Cluster Mapping Algorithm on   Shared Distributed Infrastructures. IEEE Transactions of Parallel and   Distributed Systems (TPDS), vol.25, no.10, pp.2721-2730, October 2014.   (CCF-A) DOI:10.1109/TPDS.2013.224

[13]  H. Li, X.   Wei, Q. Fu, Y. Luo. MapReduce Delay Scheduling with Deadline Constraint. Concurrency   and Computation: Practice and Experience (CCPE), vol.26, no.3,   pp.766-778, March 10, 2014. (CCF-C) DOI:10.1002/cpe.3050

[14]  X. Wei, Y. Jin, H.   Li, X. Wang and S. Hu. Virtual Resource Consolidation for Green Computing   Based on Virtual Cluster Live Migration. Journal of Communications, vol.11,   no.2, pp.192-202, February 2016. DOI:10.12720/jcm.11.2.192-202

[15]  X. Wei, W. Li, H.   Tian, H. Li, H. Xu, T. Xu. THC-MP: High Performance Numerical   Simulation of Reactive Transport and Multiphase Flow in Porous Media.   Computers & Geosciences, vol. 80, pp.26-37, 2015.

[16]  X. Wei, X. Bai, S.   Bai and H. Li. On-demand Tile Preload for Large-scale Seismic Data   3D-visualization. Journal of Computational Information Systems, vol.11, no.4,   pp.1513-1520, February 2015. DOI:10.12733/jcis13585

[17]  X. Wei, S. Hu, H.   Li, F. Yang, Y. Jin. A survey on virtual network embedding in cloud   computing centers. Open Automation and Control Systems Journal, vol.6, no.1,   pp.414-425, 2014.

[18]  X. Wei, H. Li,   L. Hu, Q. Guo, N. Jiang. LimeVI: A Platform for Virtual Cluster Live   Migration over WAN. International Journal of Computer Systems Science and   Engineering (CSSE), vol.26, No.5, pp.353-364, September 2011.

 

Conference   Papers

[1]  H. Zhao, H. Li*,   Q. Tian, J. Wu, M. Zhang, Z. Xu, X. Li, H. Xu. ArrayPipe: Introducing   Job-Array Pipeline Parallelism for High Throughput Model Exploration. IEEE   International Conference on Computer Communications (INFOCOM2025), May, 2025.   (CCF-A)

[2] H. Li, H.   Zhao, Z. Xu, X. Li, and H. Xu. ExplSched: Maximizing Deep Learning Cluster   Efficiency for Exploratory Jobs. IEEE International Conference on Cluster   Computing (CLUSTER 2023), Oct. 31, 2023, Santa Fe, New Mexico, USA. (CCF-B)

[3] H. Zhao, X. Li, H.   Li*. Visage: Visual-Aware Generation of Adversarial Examples in Black-Box   for Text Classification. The 13th CCF International Conference on Natural   Language Processing and Chinese Computing (NLPCC 2024), Nov. 1, 2024,   Hangzhou, China. (the Best paper award) (CCF-C)

[4]  H. Li, D.   Xu, Z. Xu, X. Li. Hybrid Parameter Update: Alleviating Imbalance Impacts for   Distributed Deep Learning. 24th IEEE International Conference on High   Performance Computing and Communications (HPCC2022), Dec. 2022. (CCF-C)

[5]  H. Li, T.   Sun, X. Li, H. Xu. Job Placement Strategy with Opportunistic Resource Sharing   for Distributed Deep Learning Clusters. 2020 IEEE 22nd International   Conference on High Performance Computing and Communications (HPCC2020), Dec.   2020. (CCF-C)

[6]  H. Li, Z Xu,   F. Tang, X. Wei, Z. Ding. CPSA: A Coordinated Process Scheduling Algorithm   for Coupled Earth System Model. 2020 29th International Conference on   Computer Communication and Networks (ICCCN), August 2020. (CCF-C)

[7]  Y. Zhuang, X. Wei,   H. Li*, M. Hou, Y. Wang. Reducing Fault-tolerant Overhead for Distributed   Stream Processing with Approximate Backup. 2020 29th International Conference   on Computer Communication and Networks (ICCCN), August 2020. (CCF-C)

[8]  Y. Zhuang, X. Wei,   H. Li*, Y. Wang and X. He. An Optimal Checkpointing Model with Online   OCI Adjustment for Stream Processing Applications. 2018 27th International   Conference on Computer Communication and Networks (ICCCN), pp. 1-9, July 30   2018, Hangzhou, China. (CCF-C) DOI:10.1109/ICCCN.2018.8487327

[9]  H. Li, J.   Wu, Z. Jiang, X. Li, X. Wei. Task Allocation for Stream Processing with   Recovery Latency Guarantee. in Cluster Computing (CLUSTER), 2017 IEEE   International Conference on. IEEE, 2017, pp. 379–383. (CCF-B) DOI:10.1109/CLUSTER.2017.10

[10] H. Li, J.   Wu, Z. Jiang, X. Li, X. Wei, Y. Zhuang. Integrated Recovery and Task   Allocation for Stream Processing. 2017 IEEE 36th International Performance   Computing and Communications Conference (IPCCC), Dec. 10, 2017, San Diego,   CA, USA. (CCF-C) DOI:10.1109/PCCC.2017.8280443

获奖情况:

国家级一流本科课程虚拟仿真课程2023

吉林省科技进步一等奖2018
 
中国商业联合会科学技术奖一等奖 2014
  CSC-IBM
中国优秀教师奖教金 2014
  ACM
中国新星奖2015
  HPC China 2015
会议优秀论文奖 2015

 

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