인하대학교 소프트웨어 공학
연구실에서는 신입 대학원생
과 예비 대학원생을 모집
합니다. 연구실 지원을
희망하는 학생은 하이테크관
1407호 로 방문 또는
아래의 연락처로
연락 주시기 바랍니다.
TEL: (032) 860-7454
Email: inhaselab@gmail.com
Software Engineering Laboratory.
High Performance Parallel and Distributed Computing
Researchers: Yong Beom Ma (22nd semester), Tae Young Kim (18th semester), Hyunchang Oh (12th semester)
Related Published List:
1. Tae Young Kim, Jong Sik Lee, "Multi-policy based Scheduling for Face Certification on Distributed Computing", Information: An International Interdisciplinary Journal (Printed in Japan) (indexed by SCOPUS), Volume 16, Number 12(A), December 2013
2. Taeyoung Kim, Jaekwon Kim, Minoh Park, Sanggil Kang, Kangsun Lee, Jong Sik Lee, "Agent-based Flexible Management for Big Data Fusion Service on IRC Network", The Second International Conference on Big Data Science and Engineering (BDSE2013), Sydney, Austrailia, December 2013
3. 김재권, 이종식, "클라우드 프로비저닝 서비스를 위한 퍼지 로직 기반의 자원 평가 방법", 한국시뮬레이션학회 논문지, Vol. 22, No. 1, March 2013
4. Kyu Cheol Cho Jong Sik Lee, "Grid-based & Outlier Detection-based Data Clustering & Classification", INFORMATION: An International Journal, Vol.15, No.3, March 2012
5. 김재권, 이종식, "클라우드 환경의 교통정보 서비스를 위한 조건부 확률 추론을 이용한 가상 머신 프로비저닝 스케줄링", 한국시뮬레이션학회 논문지, 제20권 4호, December 2011
6. Tae Young Kim Jong Sik Lee, "Workload Prediction and Weighted Rule-Based Task Scheudling for Face Certificatoin System on Distributed Parallel Computing", Grid and Distributed Computing, CCIS 261, Jeju Island, Korea, December 2011
7. Yong Beom Ma, Sung Ho Jang, Jong Sik Lee, "QoS and Ontology-based Resource Management in Cloud Computing Environment", INFORMATION: An International Journal, Vol.14, No.11, November 2011
8. 오현창 이종식, "분산시뮬레이션을 이용한 워게임 이동객체의 최적경로 생성 시스템", 한국시뮬레이션학회 2011 춘계학술대회, 경기대학교 수원캠퍼스, May 2011
9. Yong Beom Ma, Sung Ho Jang, Jong Sik Lee, "Ontology-based Resource Management for Cloud Computing", The 3rd Asian Conference on Intelligent Information and Database Systems (ACIIDS) 2011, Daegu, Korea, April 2011
10. Sung Ho Jang Jong Sik Lee Chang Hyeon Noh Young Shin Han, "Ontology-based Adaptive Job Scheduling Using Mobile Agent Technology in Grid Computing", INFORMATION: An International Journal, Vol.13, No.5, September 2010
11. 마용범 김태영 이종식, "동적 로드 밸런싱을 이용한 그리드 기반의 생물학적 데이터 마이닝", 한국시뮬레이션학회 제19권 2호, June 2010
12. 김태영 노창현 이종식, "분산 얼굴인식을 위한 퍼지로직 기반 비트 압축법", 한국 시뮬레이션학회 논문지 제 18권 2호, June 2009
13. Sung Ho Jang Jong Sik Lee, "Fuzzy Logic Control-based Load Balancing Agent for Distributed RFID Systems", Shanghai, China, September 2008
14. 김태영 노창현 이종식, "대용량 패턴정보 데이터의 분산처리를 위한 비트변환 기반의 데이터 교환 방법", 한국시뮬레이션학회 2008 춘계학술대회, May 2008
15. In Kee Kim Sung Ho Jang Jong Sik Lee, "5th International Symposium on Parallel and Distributed Processing and Applications (ISPA 2007) Workshops on Ubiquitous Processing for Wireless Networks(UPWN 2007),", TNiagara Falls, Canada, August 2007
16. In Kee Kim Sung Ho Jang Jong Sik Lee, "Adaptive and Mobility-Predictive Quantization-based Communication Data Management in High-Performance Distributed Computing", SCS SIMULATION, July 2007
17. Jong Sik Lee , "Communication Data Multiplexing in Distributed Simulation", LECTURE NOTES IN COMPUTER SCIENCE, 3719, October 2005
18. Jong S. Lee , "High Performance Modeling for Distributed Simulation", LECTURE NOTES IN COMPUTER SCIENCE, 3397, February 2005
19. Jong Sik Lee , "High Performance System Modeling and Performance Evaluation for Grid Computing", PDPTA 04 - The 2004 International Conference on Parallel and Distributed Processing Techniques and Applications, Las Vegas, Nevada, June 2004
20. Jong S. Lee , "High Performance Modeling with Quantized System", LECTURE NOTES IN COMPUTER SCIENCE, 3045, May 2004
21. Jong S. Lee , "Data Management with Load Balancing in Distributed Computing", LECTURE NOTES IN COMPUTER SCIENCE, 3045, May 2004
22. Jong Sik Lee , "Quantized System Modeling and Performance Evaluation", 한국시뮬레이션학회 추계학술대회, November 2003
23. Jong S. Lee B. P. Zeigler, "High Performance Modeling of Ballistic Missile Federations in DEVS/GDDM", Advanced Simulation Technologies Conference, Orlando, FL, April 2003
24. Jong S. Lee Bernard. P. Zeigler, "Space-based Communication Data Management in Scalable Distributed simulation", Journal of Parallel and Distributed Computing, 62, (doi:10.1006/jpdc.2001.1798), available online http://www.idealibrary.com, March 2003
25. Bernard P. Zeigler Hyup J. Cho Jeong G. Kim Hessam Sarjoughian Jong S. Lee, "Quantization based filtering in distributed simulation: experiments and analysis", Journal of Parallel and Distributed Computing, Volume 62, number 11, November 2002
26. Jong Sik Lee Bernard. P. Zeigler, "Design and Development of Data distribution Management Environment", Journal of Society of Computer Simulation, Simulation, (77)1-2, July 2001
27. Bernard. P. Zeigler George Ball Hyup Cho J.S. Lee Hessam Sarjoughian, "Bandwidth Utilization/Fidelity Tradeoffs in Predictive Filtering", Simulation Interoperability Workshop (SIW), 99S-SIW-63, Orlando, FL., June 1999
28. Zeigler B.P J.S. Lee, "Theory of Quantized Systems: Formal Basis for DEVS/HLA Distributed Simulation Environment", Enabling Technology for Simulation Science(II), SPIE AeoroSense 98, vol.3369, April 1998
The efficient use of modern parallel computing platforms implies a careful adaptation of the underlying numerical algorithms. In practice, this translates into two main types of activities: most often, existing methods are parallelized with no modification to the numerical ingredients; however, in certain situations, new numerical methods have to be designed in order to fully benefit from the capabilities of these computers. The solution of the algebraic systems resulting from the discretization of partial differential equations is a classical context which is witnessing a large number of research activities worldwide that aim at developing new parallel solvers. These are for a great part based on domain decomposition principles. Project-team Caiman is currently contributing to both aspects. On one hand, the finite volume and discontinuous Galerkin methods on unstructured tetrahedral meshes are parallelized using a classical SPMD (Single Program Multiple Data) strategy that combines a partitioning of the computational domain and a message passing programming model based on MPI (Message Passing Interface). On the other hand, we develop domain decomposition algorithms for the solution of general sparse linear systems.
Moreover, the popularity of the Internet as well as the availability of powerful computers and high-speed network technologies as low-cost commodity components is changing the way we use computers today. These technological opportunities have led to the possibility of using distributed computing platforms as a single, unified resource, leading to what is popularly known as grid computing. Grids enable the sharing, selection and aggregation of a wide variety of resources including supercomputers, storage systems and specialized devices that are geographically distributed and owned by different organizations, for solving large-scale computational and data intensive problems in science, engineering and commerce. However this emerging grid computing concept also brings additional constraints on the development of scientific applications such as, heterogeneity (both in terms of CPUs and interconnection networks) and multi-localization. The development of scientific applications that fully exploit such distributed and heterogeneous computing platforms requires bringing together computer scientists from the grid computing community and computational mathematicians. The former are currently developing languages and tools relying on new programming paradigms, such as distributed oriented programming, that offer new perspectives of scientific applications.
HighTech Center 1407, SE Lab, School of CSE, Inha University #253, YongHyun-Dong, Nam-Ku, Incheon 402-751, South Korea
TEL: (+82) 32-860-7454, E-mail: inhaselab@gmail.com