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刘卫国

发布日期:2019-06-25    作者:     来源:     点击:

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个人简介

刘卫国于1994年进入西安交通大学并获得学士和硕士学位,2007年在新加坡南洋理工大学获得博士学位,2012年被授予山东省泰山学者加入全国十大赌博官网任教并担任高性能计算学科组负责人。现为山东大学教授,博士生导师,CCF高性能计算专委委员,CCF生物信息学专委委员,其研究领域为高性能计算、大数据处理与分析。迄今为止以第一作者或通讯作者发表学术论文60余篇,发表在包括著名国际期刊如IEEE TPDS, Bioinformatics,IEEE TCBB, BMC Bioinformatics, Computational and Structural Biotechnology Journal,Journal of Computational Biology和著名国际会议如SC, FAST, NSDI, IPDPS, ICPP, BIBM, IEEE Cluster等。其中,所发表的关于使用GPU处理器进行生物大数据处理的论文曾两次获得德国Fraunhofer IGD的最佳论文一等奖;2016年,其参与的在神威·太湖之光超级计算机上关于高性能应用IO分析的工作被CCF高性能计算专业委员会授予优秀论文奖(Best Paper);2017年,其项目团队参与的超算应用课题18.9-Pflops Nonlinear Earthquake Simulation on Sunway TaihuLight: Enabling Depiction of 18-Hz and 8-Meter Scenarios荣获ACM“戈登•贝尔”奖。目前承担了包括科技部国家重点研发计划、国家自然科学基金面上项目、国家自然科学基金山东联合基金、中德合作科研项目(PPP)等国家和省部级重要科研项目。

联系方式

Email: weiguo.liu@sdu.edu.cn


研究方向

主要研究方向包括异构高性能计算、大数据处理与分析、智能计算。

招生意向

每年招收博士研究生1名,硕士研究生1-4名。

讲授课程

Parallel Computing

多核平台上的并行计算

承担国家级科研项目

1.国家自然科学基金面上项目,面向超大规模短读生物序列数据的高性能匹配算法研究,2020.01-2023.12

2.国家自然科学基金-山东联合基金,海量数据驱动下的高分辨率海洋数值模式关键算法研究,2019.01-2022.12

3.中德合作科研项目(PPP),面向下一代测序数据分析的高性能算法和通用模块设计研究,2019.01-2020.12

4.国家重点研发计划,高性能计算应用软件协同开发工具与环境研究,2017.07-2021.06

5.国家重点研发计划,大规模并行计算的工具库和领域相关基础软件包, 2017.7-2020.12

6.中德合作科研项目(PPP),异构平台上面向基因组大数据处理任务的并行编程系统设计关键技术研究,2016.01-2017.12

发表论文

1.H. Lan, J. Meng, C. Hundt, B. Schmidt, M. Deng, X. Wang, W. Liu, Y. Qiao, S. Feng: FeatherCNN: Fast Inference Computation with TensorGEMM on ARM Architectures, accepted by IEEE Transactions on Parallel and Distributed Systems.(impact factor: 3.402)

2.T. Zhang, Y. Li, X. Duan, P. Gao, M. Zhang, W. Liu, Z. Liu, L. Gan, H. Fu, W. Xue, G. Yang, etc.: SW_Gromacs: Acceletate Gromacs on Sunway Taihulight, SC 2019,Denver, USA, November, 2019.

3.K. Xu, Z. Song, Y. Chan, S. Wang, X. Meng, W. Liu, W. Xue: Refactoring and Optimizing WRF Model on Sunway TaihuLight, ICPP 2019,Kyoto,Japan,August, 2019.

4.Z. Yin, T. Zhang, H. Liu, Y. Wei, B. Schmidt, W. Liu: Efficient Parallel Sort on AVX-512-based Multi-core and Many-core Architectures, HPCC 2019,Zhangjiajie,China,August, 2019.

5.Z. Yin, H. Zhang, P. Shao, X. Wang, B. Schmidt, W. Liu: XLCS: A New Bit-Parallel Longest Common Subsequence Algorithm on Xeon Phi Clusters, HPCC 2019,Zhangjiajie,China,August, 2019.

6.Bin Yang; Xu Ji, Xiaosong Ma, Xiyang Wang, Tianyu Zhang, Xiupeng Zhu, Nosayba El-Sayed, Haidong Lan, Yibo Yang, Jidong Zhai, Weiguo Liu and Wei Xue: End-to-end I/O Monitoring on a Leading Supercomputer, NSDI 2019,February, 2019,Boston, MA, USA

7.Xu Ji, Bin Yang, Tianyu Zhang, Xiaosong Ma, Xiupeng Zhu, Xiyang Wang, Nosayba EI-Sayed, Jidong Zhai, Weiguo Liu and Wei Xue;: Automatic, Application-Aware I/O Forwarding Resource Allocation for High-end System, FAST 2019,February, 2019,Boston, MA, USA

8.J. Zhang, H. Lan, Y. Chan, Y. Shang, B. Schmidt, W. Liu: BGSA: A Bit-Parallel Global Sequence Alignment Toolkit for Multi-core and Many-core Architectures, accepted by Bioinformatics, 2019. (impact factor: 5.481)

9.X. Duan, P. Gao, T. Zhang, M. Zhang, W. Liu, W. Zhang, W. Xue, H. Fu, L. Gan, D. Chen, X. Meng, G. Yang: Redesigning LAMMPS for Peta-scale and Hundred-billion-atom Simulation on Sunway TaihuLight, SC 2018, Dallas, Texas, USA, 2018.

10.K. Xu, R. Kobus, Y. Chan, P. Gao, X. Meng, Y. Wei, B. Schmidt, W. Liu: SPECTR: Scalable Parallel Short Read Error Correction on Multi-core and Many-core Architectures, ICPP 2018, Eugene, Oregon, USA, 2018.

11.H. Zhang, Y. Chan, K. Fan, B. Schmidt and W. Liu: Fast and efficient short read mapping based on a succinct hash index, BMC Bioinformatics, 19:92, 2018. (impact factor: 2.448)

12.Y. Chan, K. Xu, H. Lan, B. Schmidt, S. Peng, and W. Liu: MyPhi: Efficient Levenshtein Distance Computation on Xeon Phi based Architectures, Current Bioinformatics, 2018. (impact factor: 0.6)

13.Haohuan Fu, Junfeng Liao, Nan Ding, Xiaohui Duan, Lin Gan, Yishuang Liang, Xinliang Wang, Jinzhe Yang, Yan Zheng, Weiguo Liu, Lanning Wang, Guangwen Yang: Redesigning CAM-SE for Petascale Climate Modeling Performance on Sunway TaihuLight, the International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2017), Denver, USA, November, 2017. (ACM Gordon Bell Prize Finalist)

14.Haohuan Fu, Conghui He, Bingwei Chen, Zekun Yin, Zhenguo Zhang, Wenqiang Zhang, Tingjian Zhang, Wei Xue, Weiguo Liu, Wanwang Yin, Guangwen Yang, Xiaofei Chen: 18.9-Pflops Nonlinear Earthquake Simulation on Sunway TaihuLight: Enabling Depiction of 18-Hz and 8-Meter Scenarios, the International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2017), Denver, USA, November, 2017. (ACM Gordon Bell Prize)

15.Xiaohui Duan, Kai Xu, Yuandong Chan, Christian Hundt, Bertil Schmidt, Pavan Balaji and Weiguo Liu: S-Aligner: Ultrascalable read mapping on Sunway Taihu Light, the 19th IEEE International Conference on Cluster Computing (IEEE Cluster 2017), Hawaii, USA, September, 2017.

16.Zekun Yin, Haidong Lan, Guangming Tan, Mian Lu, Athanasios V. Vasilakos, Weiguo Liu: Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges, accepted by Computational and Structural Biotechnology Journal, 2017. (CiteScore: 3.16)

17.Peng S, Yang S, Su W, Zhang X, Zhang T, Liu W, Zhao XM: A CPU/MIC Collaborated Parallel Framework for GROMACS on Tianhe-2 Supercomputer, accepted by IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017. (impact factor:1.609)

18.Qingke Zhang, Weiguo Liu, Xiangxu Meng, Bo Yang, and Athanasios V. Vasilakos: Vector Coevolving Particle Swarm Optimization Algorithm, accepted by Information Sciences, 2017. (impact factor:3.364)

19.Shuai Zhang, Zhao Wang, Ying Peng, Bertil Schmidt, and Weiguo Liu: Mapping of Option Pricing Algorithms onto Heterogeneous Many-Core Architectures, accepted by The Journal of Supercomputing, 2017. (impact factor: 1.088)

20.Yuandong Chan, Kai Xu, Haidong Lan, Weiguo Liu, Yongchao Liu and Bertil Schmidt: A Parallel Ungapped-Alignment-Featured Seed Verification Algorithm for Next-Generation Sequencing Read Alignment, the 31stIEEE International Parallel & Distributed Processing Symposium (IPDPS 2017), Orlando, USA, May, 2017.

21.Haidong Lan, Weiguo Liu, Yongchao Liu and Bertil Schmidt: SWhybrid: A Hybrid-Parallel Framework for Large-Scale Protein Sequence Database Search, the 31st IEEE International Parallel & Distributed Processing Symposium (IPDPS 2017), Orlando, USA, May, 2017.

22.Y. Yang, X. Wang, B. Yang, W. Liu, and W. Xue: IO Trace Tool for HPC applications over Sunway TaihuLight Supercomputer, CCF HPC China 2016 (Best Paper).

23.Y. Chan, K. Xu, J. Zhang, X. Wang, and W. Liu: SLPal – Fast Bit Parallel Algorithm for Accelerating Long DNA Sequence Comparison on Xeon Phi, CCF HPC China 2016 (优秀应用论文).

24.H. Lan, Y. Chan, K. Xu, B. Schmidt, S. Peng, and W. Liu: Parallel algorithms for large-scale biological sequence alignment on Xeon-Phi based clusters, BMC Bioinformatics, 17(9):11-23, 2016. (Imapct factor: 2.576).

25.Y. Chan, K. Xu, J. Zhang, X. Yu and W. Liu: XMapper - A Parallel Full Comprehensive DNA Read Mapping Algorithm Based on Intel Xeon and Xeon Phi Heterogeneous Architecture, CCF HPC China 2015 (优秀应用论文).

26.H. Lan, W. Liu, B. Schmidt, and B. Wang: Accelerating Large-Scale Biological Database Search on Xeon Phi-based Neo-Heterogeneous Architectures, 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2015), Washington D.C., USA, November 2015.

27.Q. Zheng, H. Lan, and W. Liu: XPFS: A New Parallel PROSITE Profile Search Algorithm on Xeon Phi, IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2014), Belfast, UK, November 2014.

28.S. Zhang and W. Liu: Parallel Monte Carlo Option Pricing Algorithms on Hybrid Heterogeneous Many-Core Architectures, CCF HPC China 2014.

29.L. Wang, Y. Chan, X. Duan, H. Lan, X. Meng, and W. Liu: XSW: Accelerating Biological Database Search on Xeon Phi, the 28th IEEE International Parallel & Distributed Processing Symposium (IPDPSW 2014), Phoenix, USA, May, 2014.

30.X. Duan, K. Zhao, and W. Liu: HiPGA: A High Performance Genome Assembler for Short Read Sequence Data, the 28th IEEE International Parallel & Distributed Processing Symposium (IPDPSW 2014), Phoenix, USA, May, 2014.

31.K. Zhao, W. Liu, G. Voss, and W. Müller-Wittig: Accelerating de Bruijn Graph-based Genome Assembly for High-Throughput Short Read Data, the 19th IEEE International Conference on Parallel and Distributed Systems (ICPADS 2013), Korea, December, 2013.

32.Y. Guo, W. Liu, B. Gong, G. Voss, and W. Müller-Wittig: GCMR: A GPU Cluster-based MapReduce Framework for Large-scale Data Processing, The 15th IEEE International Conference on High Performance Computing and Communications (HPCC 2013), Zhangjiajie, China, November 13-15, 2013.

33.K. Zhao, W. Liu, G. Voss, and W. Müller-Wittig: A Dynamic Hashing approach to build de Bruijn graph for genome assembly, IEEE TENCON 2013, Xi’an, China, October 22-25, 2013.

34.H. Shi, B. Schmidt, W. Liu, and W. Müller-Wittig: Parallel Mutual Information Estimation for Inferring Gene Regulatory Networks on GPUs, BMC Research Notes, DOI:10.1186/1756-0500-4-189

35.W. Liu, B. Schmidt, and W. Mueller-Wittig: CUDA-BLASTP: Accelerating BLASTP on CUDA-enabled Graphics Hardware, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2011 November. (Imapct factor: 2.246)

36.W. Liu, B. Schmidt, Y. Liu, G. Voss, and W. Müller-Wittig: Mapping of BLASTP Algorithm onto GPU Clusters, the 17th IEEE International Conference on Parallel and Distributed Systems (ICPADS 2011), Tainan, December 7-9, 2011.

37.H. Shi, W. Liu, B. Schmidt: CUDA-EC: CUDA Error Correction Method for High-Throughput Short-Read Sequencing Data, in Bioinformatics: High Performance Parallel Computer Architectures, Taylor & Francis/CRC Press, 2010.

38.H. Shi, B. Schmidt, W. Liu, and W. Müller-Wittig: A Parallel Algorithm for Error Correction in High-Throughput Short-Read Data on CUDA-enabled Graphics Hardware, Journal of Computational Biology, vol. 17, no. 4, pp. 603-615, 2010. (Impact Factor: 1.694)

39.H. Shi, B. Schmidt, W. Liu, and W. Müller-Wittig: Quality-Score Guided Error Correction for Short-Read Sequencing Data using CUDA, The International Conference on Computational Science 2010 (ICCS 2010), Amsterdam, Netherlands, Procedia Vol. 1, No. 1, pp. 1123-1132, 2010.

40.Y. Liu, B. Schmidt, W. Liu, and D. Maskell: CUDA-MEME: Accelerating Motif Discovery in Biological Sequences Using CUDA-enabled Graphics Processing Units, Pattern Recognition Letters, in press, doi: 10.1016/j.patrec.2009.10.009. (Impact Factor: 1.772)

41.H. Shi, B. Schmidt, W. Liu, and W. Müller-Wittig: Accelerating Error Correction in High-Throughput Short-Read DNA Sequencing Data with CUDA, in Proc. 23th IEEE International Parallel & Distributed Processing Symposium (IPDPSW 2009).

42.B. Schmidt, C. Chen, W. Liu, W. Mitchell: PheGee@Home: A Grid-based Tool for Comparative Genomics, in Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine and Healthcare, IGI Global, 2008.

43.W. Liu, B. Schmidt, G. Voss, and W. Müller-Wittig: Accelerating Molecular Dynamics Simulations using Graphics Processing Units with CUDA, Computer Physics Communications, vol. 179, pp. 634-641, 2008. (Impact Factor: 1.958)

44.A. Singh, C. Chen, W. Liu, W. Mitchell, and B. Schmidt: A Hybrid Computational Grid Architecture for Comparative Genomics, IEEE Transactions on Information Technology in Biomedicine, vol. 12, no. 2, pp. 218-225, 2008. (Impact Factor: 1.694)

45.C. Chen, B. Schmidt, W. Liu, and W. Müller-Wittig, Using Graphics Hardware to Accelerate Motif Finding in DNA Sequences, Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB’08), LNBI, Australia, 2008.

46.B. Schmidt, CX. Chen, W. Liu: Hierarchical Grid Computing for High Performance Bioinformatics, in Grid Computing for Bioinformatics and Computational Biology, John Wiley & Sons, 2007.

47.W. Liu, B. Schmidt, and W. Müller-Wittig: Performance Analysis of General-Purpose Computation on Commodity Graphics Hardware: A Case Study Using Bioinformatics, The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, vol. 48, no. 3, pp. 209-221, 2007. (Impact Factor: 0.732)

48.W. Liu, B. Schmidt, G. Voss, and W. Müller-Wittig: Streaming Algorithms for Biological Sequence Alignment on GPUs, IEEE Transactions on Parallel and Distributed Systems, vol. 18, no. 9, pp. 1270-1281, 2007. (Impact Factor: 1.733)

49.W. Liu, B. Schmidt, G. Voss, and W. Müller-Wittig: Molecular Dynamics Simulations on Commodity GPUs with CUDA, 14th Annual IEEE International Conference on High Performance Computing (HiPC 2007), LNCS 4873, pp. 185-196, Goa, India, December 18-21, 2007.

50.M. Low, W. Liu, and B. Schmidt: A Parallel BSP Algorithm for Irregular Dynamics Programming, 7th International Symposium on Advanced Parallel Processing Technologies (APPT 2007), LNCS 4847, pp. 151-160, Guangzhou, China, 2007.

51.W. Liu, B. Schmidt, and W. Müller-Wittig: Performance Predictions for General-Purpose Computation on GPUs, International Conference on Parallel Processing (ICPP 2007), Xi’an, China, September 10-14, 2007.

52.J. Feng, S. Chakraborty, B. Schmidt, W. Liu, and U.D. Bordoloi: Fast Schedulability Analysis Using Commodity Graphics Hardware, 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2007), Daegu, Korea, 2007.

53.C. Chen, A. Singh, W. Liu, W. Müller-Wittig, W. Mitchell, and B. Schmidt, Phenotype Genotype Exploration on A Desktop GPU Grid, 3rd International Workshop on Grid Computing & Applications (GCA 2007), Singapore, 2007.

54.W. Liu, B. Schmidt, Parallel Pattern-based Systems for Computational Biology: A Case Study, IEEE Transactions on Parallel and Distributed Systems, vol. 17, no. 8, pp. 750-763, August 2006. (Impact Factor: 1.733)

55.W. Liu, B., Schmidt, Mapping of Hierarchical Parallel Genetic Algorithms for Protein Folding onto Computational Grids, IEICE Transactions on Information and Systems, E89-D(2):589-596, February 2006. (Impact Factor: 0.396)

56.W. Liu, B. Schmidt, G. Voss, and W. Müller-Wittig: GPU-ClustalW: Using Graphics Hardware to Accelerate Multiple Sequence Alignment, 13th Annual IEEE International Conference on High Performance Computing (HiPC 2006), Bangalore, India, LNCS 4297, pp. 363-374, 2006.

57.W. Liu, B. Schmidt, G. Voss, and W. Müller-Wittig: Bio-Sequence Database Scanning on a GPU, in Proc. 20th IEEE International Parallel & Distributed Processing Symposium (IPDPSW 2006), Rhode Island, Greece, 2006.

58.W. Liu, B. Schmidt, Mapping of Hierarchical Parallel Genetic Algorithms for Protein Folding onto Computational Grids, IEEE Tencon 2005, Melbourne, Australia, 2005.

59.W. Liu, B. Schmidt, A Case Study on Pattern-based Systems for High Performance Computational Biology, in Proc. 19th IEEE International Parallel & Distributed Processing Symposium (IPDPSW 2005), Denver, CO, 2005.

60.W. Liu, B. Schmidt: A Tunable Coarse-Grained Parallel Algorithm for Irregular Dynamic Programming Applications, 11th Annual IEEE International Conference on High Performance Computing (HiPC 2004), Bangalore, India, Springer, LNCS, 2004.

61.W. Liu, B. Schmidt, A Generic Parallel Pattern-based System for Bioinformatics, Euro-Par 2004, Pisa, Italy, LNCS, Springer, 2004.

62.W. Liu, B. Schmidt, Parallel Design Pattern for Computational Biology and Scientific Computing, IEEE International Conference on Cluster Computing (Cluster 2003), Hong Kong, 2003.

本人研究生从事的工作领域

所培养的研究生适合高校、科研院所及工业界的学术、科研、设计和研发工作。

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