Heterogeneous Compute Clusters and Massive Environmental Simulations Based on the EPIC Model

16922 7 92552 2 268468 document 92552 modelling-01-00013-v2.pdf application/pdf ce00f551506a7aaba1fbfd964c067011 MD5 266105 2020-12-10 10:38:38 https://pure.iiasa.ac.at/id/eprint/16922/1/modelling-01-00013-v2.pdf 16922 1 1 application/pdf text en public cc_by_4

modelling-01-00013-v2.pdf

published 92553 2 268474 document 92553 lightbox.jpg image/png 2631f4a2a65a51159f27a00d23a9e902 MD5 51057 2020-12-10 10:48:45 https://pure.iiasa.ac.at/id/eprint/16922/2/lightbox.jpg 16922 2 2 image/png other Thumbnails conversion from text to thumbnail_lightbox en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/92552 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/92552 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/92552 archive 353 disk0/00/01/69/22 2020-12-10 10:41:43 2021-08-27 17:34:04 2020-12-10 10:41:43 article show Khabarov N. 1850 0000-0001-5372-4668 Smirnov A. 98121 0000-0003-1765-0782 Balkovič J. 1977 0000-0003-2955-4931 Skalský R. 1986 0000-0002-0983-6897 Folberth C. 2033 0000-0002-6738-5238 Van Der Velde M. Obersteiner M. 7255 0000-0001-6981-2769 Heterogeneous Compute Clusters and Massive Environmental Simulations Based on the EPIC Model pub prog_esm EPIC model; high performance computing (HPC); high-throughput computing (HTC); HTCondor; massive spatio-temporal modeling; legacy source code; environmental simulation; heterogeneous compute clusters; crop model; agriculture; climate change In recent years, the crop growth modeling community invested immense effort into high resolution global simulations estimating inter alia the impacts of projected climate change. The demand for computing resources in this context is high and expressed in processor core-years per one global simulation, implying several crops, management systems, and a several decades time span for a single climatic scenario. The anticipated need to model a richer set of alternative management options and crop varieties would increase the processing capacity requirements even more, raising the looming issue of computational efficiency. While several publications report on the successful application of the original field-scale crop growth model EPIC (Environmental Policy Integrated Climate) for running on modern supercomputers, the related performance improvement issues and, especially, associated trade-offs have only received, so far, limited coverage. This paper provides a comprehensive view on the principles of the EPIC setup for parallel computations and, for the first time, on those specific to heterogeneous compute clusters that are comprised of desktop computers utilizing their idle time to carry out massive computations. The suggested modification of the core EPIC model allows for a dramatic performance increase (order of magnitude) on a compute cluster that is powered by the open-source high-throughput computing software framework HTCondor. 2020-12-04 published MDPI 151 288 23 287 92 219 public Modelling 1 2 215-224 TRUE 2673-3951 Effects of phosphorus limitations on Life, Earth system and Society (IMBALANCE-P, FP7 610028) FALSE yes info:eu-repo/grantAgreement/EC/FP7/610028/EU//IMBALANCE-P info:eu-repo/semantics/article info:eu-repo/semantics/openAccess