Application note: High-performance computing for climate change impact studies with the Pasture Simulation model

  • Authors:

  • Jean-André Vital;Michael Gaurut;Romain Lardy;Nicolas Viovy;Jean-François Soussana;Gianni Bellocchi;Raphaël Martin

  • Affiliations:

  • Grassland Ecosystem Research Unit, French National Institute for Agricultural Research (INRA), 5 Chemin de Beaulieu, 63039 Clermont-Ferrand, France;Grassland Ecosystem Research Unit, French National Institute for Agricultural Research (INRA), 5 Chemin de Beaulieu, 63039 Clermont-Ferrand, France;Grassland Ecosystem Research Unit, French National Institute for Agricultural Research (INRA), 5 Chemin de Beaulieu, 63039 Clermont-Ferrand, France;Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CE L'Orme des Merisiers, 91191 Gif-sur-Yvette, France;Scientific Direction in Environment, French National Institute for Agricultural Research (INRA), 147 rue de l'Université, 75338 Paris, France;Grassland Ecosystem Research Unit, French National Institute for Agricultural Research (INRA), 5 Chemin de Beaulieu, 63039 Clermont-Ferrand, France;Grassland Ecosystem Research Unit, French National Institute for Agricultural Research (INRA), 5 Chemin de Beaulieu, 63039 Clermont-Ferrand, France

  • Venue:
  • Computers and Electronics in Agriculture
  • Year:
  • 2013

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Abstract

High-performance computing technology permits to efficiently achieve high-performance throughputs for intensive CPU load applications. We describe the development of an integrated tool for climate change impact studies on grassland ecosystems running with pixel-wise data. The pixel-based Pasture Simulation model (PaSim) is suited to work with a NetCDF format of input and output files. It includes the parallel job launcher, which dispatches individual jobs to execute simulations. In a case study covering metropolitan France, we demonstrate how this approach is configured and used to evaluate the impact of climate change on grassland productivity. Over ~10,000pixels of 8x8km resolution, we report ~25h to complete the simulation on a cluster machine (TITANE) with 200 processors, which is a speedup of 200.