Bringing task and data parallelism to analysis of climate model output

Robert Jacob, Jayesh Krishna, Xiabing Xu, Sheri Mickelson, Tim Tautges, Mike Wilde, Robert Latham, Ian Foster, Robert Ross, Mark Hereld, Jay Larson, Pavel Bochev, Kara Peterson, Mark Taylor, Karen Schuchardt, Jain Yin, Don Middleton, Mary Haley, David Brown, Wei HuangDennis Shea, Richard Brownrigg, Mariana Vertenstein, Kwan-Liu Ma, Jingrong Xie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Climate models are both outputting larger and larger amounts of data and are doing it on more sophisticated numerical grids. The tools climate scientists have used to analyze climate output, an essential component of climate modeling, are single threaded and assume rectangular structured grids in their analysis algorithms. We are bringing both task- and data-parallelism to the analysis of climate model output. We have created a new data-parallel library, the Parallel Gridded Analysis Library (ParGAL) which can read in data using parallel I/O, store the data on a compete representation of the structured or unstructured mesh and perform sophisticated analysis on the data in parallel. ParGAL has been used to create a parallel version of a script-based analysis and visualization package. Finally, we have also taken current workflows and employed task-based parallelism to decrease the total execution time.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 SC Companion
Subtitle of host publicationHigh Performance Computing, Networking Storage and Analysis, SCC 2012
Pages1493-1495
Number of pages3
DOIs
StatePublished - Dec 1 2012
Event2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012 - Salt Lake City, UT, United States
Duration: Nov 10 2012Nov 16 2012

Other

Other2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012
CountryUnited States
CitySalt Lake City, UT
Period11/10/1211/16/12

Keywords

  • climate
  • parallel analysis
  • unstructured grids

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

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  • Cite this

    Jacob, R., Krishna, J., Xu, X., Mickelson, S., Tautges, T., Wilde, M., Latham, R., Foster, I., Ross, R., Hereld, M., Larson, J., Bochev, P., Peterson, K., Taylor, M., Schuchardt, K., Yin, J., Middleton, D., Haley, M., Brown, D., ... Xie, J. (2012). Bringing task and data parallelism to analysis of climate model output. In Proceedings - 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012 (pp. 1493-1495). [6496065] https://doi.org/10.1109/SC.Companion.2012.282