Journal of KIISE (정보과학회 논문지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Workflow Based on Pipelining for Performance Improvement of Volcano Disaster Damage Prediction System

화산재해 피해 예측 시스템의 성능 향상을 위한 파이프라인 기반 워크플로우

  • 허대영 (국민대학교 컴퓨터공학부) ;
  • 이동환 (국민대학교 컴퓨터공학부) ;
  • 황선태 (국민대학교 컴퓨터공학부)
  • Received : 2014.09.03
  • Accepted : 2014.12.15
  • Published : 2015.03.15
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Abstract

A volcano disaster damage prediction system supports decision making for counteracting volcanic disasters by simulating meteorological condition and volcanic eruptions. In this system, a program called Fall3D generates predicted results for the diffusion of ash after a volcanic eruption on the basis of meteorological information. The relevant meteorological information is generated by a weather numerical prediction model known as Weather Research & Forecasting (WRF). In order to reduce the entire processing time without modifying these two simulation programs, pipelining can be used by partly executing Fall3D whenever the hourly (partial) results of WRF are generated. To reduce the processing time, successor programs such as Fall3D require that certain features be suspended until the part of the results that is based on prior calculation is generated by a predecessor. Even though Fall3D does not have a suspend or resume feature, pipelining effect can be produced by using the program's restart feature, which resumes simulation from the previous session. In this study, we suggest a workflow that can control the execution type.

화산재해 피해 예측 시스템은 기상과 화산분화 시뮬레이션 결과를 기반으로 화산재해대응을 위한 판단을 도와주는 시스템이다. 이 시스템에서 Fall3D라는 프로그램은 기상정보를 바탕으로 화산분화 이후 화산재의 확산예측결과를 생성하고 기상정보를 생성하기 위해 WRF라는 기상수치예보모델을 사용한다. 두 시뮬레이션의 프로그램을 수정하지 않고, 전체 실행시간을 줄이기 위해서는 WRF의 기상예측모델의 시간별 부분결과가 발생할 때마다 Fall3D를 부분수행 할 수 있도록 하는 파이프라이닝 방식을 생각할 수 있다. 이를 위해서 Fall3D와 같은 후속계산은 선행계산의 부분결과가 생성될 때까지 일시정지하고, 계산에 필요한 정보가 발생하면 재개할 수 있어야한다. 비록 Fall3D가 이런 일시정지와 재개기능을 가지고 있지는 않지만 그 이전 계산을 이어서 진행할 수 있는 재시작기능을 활용하여 파이프라이닝 효과를 낼 수 있다. 본 논문에서는 이러한 실행 형태를 제어할 수 있는 워크플로우를 제안한다.

Keywords

Acknowledgement

Grant : 화산재해 대응시스템개발

Supported by : 소방방재청

References

  1. Michalakes, J., et al., "The weather research and forecast model: software architecture and performance," Proc. of the 11th ECMWF Workshop on the Use of High Performance Computing In Meteorology, World Scientific, Vol. 25, pp. 29, 2004.
  2. Folch, Arnau, Antonio Costa, and Giovanni Macedonio, "FALL3D: A computational model for transport and deposition of volcanic ash," Computers & Geosciences, Vol. 35, No. 6, pp. 1334-1342, Jun. 2009. https://doi.org/10.1016/j.cageo.2008.08.008
  3. National Centers for Enviornmental Predication/National Weather Service/NOAA/U.S. Department of Commerce (1997). NCEP FNL Operational Model Global Tropospheric Analyses, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Dataset. [Online]. Available: http://dx.doi.org/10.5065/D6FB50XD (Accessed 2014, Apr. 28)
  4. Rew, Russ, and Glenn Davis, "NetCDF: an interface for scientific data access," IEEE Computer Graphics and Applications, Vol. 10, No. 4, pp. 76-82, Jul. 1990. https://doi.org/10.1109/38.56302
  5. Wright, Thomas. "NCAR graphics software." Atmospheric Technology Division, National Center for Atmospheric Research, Boulder, Colorado (1977). [Online]. Available: http://ngwww.ucar.edu (downloaded 2014, Apr. 28)
  6. Thain, Douglas, Todd Tannenbaum, and Miron Livny, "Distributed computing in practice: The Condor experience," Concurrency and Computation: Practice and Experience, Vol. 17, No. 2-4, pp. 323-356, 2005. https://doi.org/10.1002/cpe.938
  7. Ludäscher, Bertram, et al., "Scientific workflow management and the Kepler system," Concurrency and Computation: Practice and Experience, Vol. 18, No. 10, pp. 1039-1065, Aug. 2006. https://doi.org/10.1002/cpe.994
  8. Yu, Jia, and Rajkumar Buyya, "A taxonomy of scientific workflow systems for grid computing," ACM Sigmod Record, Vol. 34, No. 3, pp. 44-49, Sep. 2005. https://doi.org/10.1145/1084805.1084814
  9. Romano, P., "Automation of in-silico data analysis processes through workflow management systems," Brief Bioinform, Vol. 9, No. 1, pp. 57-68, Jan. 2008. https://doi.org/10.1093/bib/bbm056