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劉衛國

發布日期:2019-06-25    作者:     來源:     點擊:

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個人簡介

劉衛國于1994年進入西安交通大學并獲得學士和碩士學位,2007年在新加坡南洋理工大學獲得博士學位,2012年被授予山東省泰山學者加入全國十大賭博官網任教并擔任高性能計算學科組負責人。現為山東大學教授,博士生導師,CCF高性能計算專委委員,CCF生物信息學專委委員,其研究領域為高性能計算、大數據處理與分析。迄今為止以第一作者或通訊作者發表學術論文60余篇,發表在包括著名國際期刊如IEEE TPDS, Bioinformatics,IEEE TCBB, BMC Bioinformatics, Computational and Structural Biotechnology Journal,Journal of Computational Biology和著名國際會議如SC, FAST, NSDI, IPDPS, ICPP, BIBM, IEEE Cluster等。其中,所發表的關于使用GPU處理器進行生物大數據處理的論文曾兩次獲得德國Fraunhofer IGD的最佳論文一等獎;2016年,其參與的在神威·太湖之光超級計算機上關于高性能應用IO分析的工作被CCF高性能計算專業委員會授予優秀論文獎(Best Paper);2017年,其項目團隊參與的超算應用課題18.9-Pflops Nonlinear Earthquake Simulation on Sunway TaihuLight: Enabling Depiction of 18-Hz and 8-Meter Scenarios榮獲ACM“戈登?貝爾”獎。目前承擔了包括科技部國家重點研發計劃、國家自然科學基金面上項目、國家自然科學基金山東聯合基金、中德合作科研項目(PPP)等國家和省部級重要科研項目。

聯系方式

Email: [email protected]


研究方向

主要研究方向包括異構高性能計算、大數據處理與分析、智能計算。

招生意向

每年招收博士研究生1名,碩士研究生1-4名。

講授課程

Parallel Computing

多核平臺上的并行計算

承擔國家級科研項目

1.國家自然科學基金面上項目,面向超大規模短讀生物序列數據的高性能匹配算法研究,2020.01-2023.12

2.國家自然科學基金-山東聯合基金,海量數據驅動下的高分辨率海洋數值模式關鍵算法研究,2019.01-2022.12

3.中德合作科研項目(PPP),面向下一代測序數據分析的高性能算法和通用模塊設計研究,2019.01-2020.12

4.國家重點研發計劃,高性能計算應用軟件協同開發工具與環境研究,2017.07-2021.06

5.國家重點研發計劃,大規模并行計算的工具庫和領域相關基礎軟件包, 2017.7-2020.12

6.中德合作科研項目(PPP),異構平臺上面向基因組大數據處理任務的并行編程系統設計關鍵技術研究,2016.01-2017.12

發表論文

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 (優秀應用論文).

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 (優秀應用論文).

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: [email protected]: 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.

本人研究生從事的工作領域

所培養的研究生適合高校、科研院所及工業界的學術、科研、設計和研發工作。

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