Development of mpi_EPIC model for global agroecosystem modeling

Kang, Shujiang; Wang, Dali; Schuchart, Joseph; Kline, Keith L.; Wei, Yaxing; Ricciuto, Daniel M.; Wullschleger, Stan D.; Post, Wilfred M.; Izaurralde, R. Cesar

doi:10.1016/j.compag.2014.12.004

Title: Development of mpi_EPIC model for global agroecosystem modeling

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Abstract

Models that address policy-maker concerns about multi-scale effects of food and bioenergy production systems are computationally demanding. We integrated the message passing interface algorithm into the process-based EPIC model to accelerate computation of ecosystem effects. Simulation performance was further enhanced by applying the Vampir framework. When this enhanced mpi_EPIC model was tested, total execution time for a global 30-year simulation of a switchgrass cropping system was shortened to less than 0.5 hours on a supercomputer. The results illustrate that mpi_EPIC using parallel design can balance simulation workloads and facilitate large-scale, high-resolution analysis of agricultural production systems, management alternatives and environmental effects.

Authors:

Kang, Shujiang ^[1]; Wang, Dali ^[1]; Jeff A. Nichols; Schuchart, Joseph ^[2]; Kline, Keith L. ^[1]; Wei, Yaxing ^[1]; Ricciuto, Daniel M. ^[1]; Wullschleger, Stan D. ^[1]; Post, Wilfred M. ^[1]; Izaurralde, R. Cesar ^[3]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
The Dresden Univ. of Technology, Dresden (Germany)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Publication Date:: Wed Dec 31 00:00:00 EST 2014

Research Org.:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)

Sponsoring Org.:: USDOE Office of Science (SC); USDOE Laboratory Directed Research and Development (LDRD) Program

OSTI Identifier:: 1185384

Alternate Identifier(s):: OSTI ID: 1246540

Grant/Contract Number:: AC05-00OR22725

Resource Type:: Accepted Manuscript

Journal Name:: Computers and Electronics in Agriculture

Additional Journal Information:: Journal Volume: 111; Journal ID: ISSN 0168-1699

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING; 54 ENVIRONMENTAL SCIENCES; load balance; parallel design; MPI; food; bioenergy; sustainability; high performance computing (HPC); message passing interface

Citation Formats


                    Kang, Shujiang, Wang, Dali, Jeff A. Nichols, Schuchart, Joseph, Kline, Keith L., Wei, Yaxing, Ricciuto, Daniel M., Wullschleger, Stan D., Post, Wilfred M., and Izaurralde, R. Cesar. Development of mpi_EPIC model for global agroecosystem modeling.  United States: N. p., 2014. 
Web.  doi:10.1016/j.compag.2014.12.004.

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                    Kang, Shujiang, Wang, Dali, Jeff A. Nichols, Schuchart, Joseph, Kline, Keith L., Wei, Yaxing, Ricciuto, Daniel M., Wullschleger, Stan D., Post, Wilfred M., & Izaurralde, R. Cesar. Development of mpi_EPIC model for global agroecosystem modeling.  United States.  https://doi.org/10.1016/j.compag.2014.12.004

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                    Kang, Shujiang, Wang, Dali, Jeff A. Nichols, Schuchart, Joseph, Kline, Keith L., Wei, Yaxing, Ricciuto, Daniel M., Wullschleger, Stan D., Post, Wilfred M., and Izaurralde, R. Cesar. Wed .  
"Development of mpi_EPIC model for global agroecosystem modeling".  United States.  https://doi.org/10.1016/j.compag.2014.12.004.  https://www.osti.gov/servlets/purl/1185384.

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@article{osti_1185384,

  title        = {Development of mpi_EPIC model for global agroecosystem modeling},

  author       = {Kang, Shujiang and Wang, Dali and Jeff A. Nichols and Schuchart, Joseph and Kline, Keith L. and Wei, Yaxing and Ricciuto, Daniel M. and Wullschleger, Stan D. and Post, Wilfred M. and Izaurralde, R. Cesar},

  abstractNote = {Models that address policy-maker concerns about multi-scale effects of food and bioenergy production systems are computationally demanding. We integrated the message passing interface algorithm into the process-based EPIC model to accelerate computation of ecosystem effects. Simulation performance was further enhanced by applying the Vampir framework. When this enhanced mpi_EPIC model was tested, total execution time for a global 30-year simulation of a switchgrass cropping system was shortened to less than 0.5 hours on a supercomputer. The results illustrate that mpi_EPIC using parallel design can balance simulation workloads and facilitate large-scale, high-resolution analysis of agricultural production systems, management alternatives and environmental effects.},

  doi          = {10.1016/j.compag.2014.12.004},

  journal      = {Computers and Electronics in Agriculture},

  number       = ,

  volume       = 111,

  place        = {United States},

  year         = {Wed Dec 31 00:00:00 EST 2014},

  month        = {Wed Dec 31 00:00:00 EST 2014}

}

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