Development of an automated gridded crop growth simulation support system for distributed computing with virtual machines

•A distributed computing system, GROWLERS, was developed for crop growth simulations.•GROWLERS requires minimum sets of user inputs and manual operations for distributed computing.•GROWLERS supports the crop model written in legacy code without modification to perform a gridded crop growth simulatio...

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Vydané v:Computers and electronics in agriculture Ročník 169; s. 105196
Hlavní autori: Kim, Junhwan, Park, Jinew, Hyun, Shinwoo, Fleisher, David H., Kim, Kwang Soo
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Amsterdam Elsevier B.V 01.02.2020
Elsevier BV
Predmet:
Automation
case studies
Central processing units
climatic factors
Clusters
Computer networks
Computer programming
Computer simulation
computer software
computers
CPUs
Crop growth
Crop model
crop models
Crop yield
data collection
Distributed processing
Gridded simulation
High performance computing
Input preparation
Microprocessors
Object oriented programming
Object-oriented languages
Oryza sativa
Personal computers
Programming languages
rice
Simulation
South Korea
sowing date
Spatial assessment
Spatial distribution
Support systems
Virtual environments
Weather
Workstations
South Korea
PDShell
GROWLERS
Input preparation
Crop model
IP
MPI
CPU
DSSAT
PC
High performance computing
XML
VMM
Spatial assessment
AWS
Gridded simulation
ISSN:0168-1699, 1872-7107
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Popis
Shrnutí:•A distributed computing system, GROWLERS, was developed for crop growth simulations.•GROWLERS requires minimum sets of user inputs and manual operations for distributed computing.•GROWLERS supports the crop model written in legacy code without modification to perform a gridded crop growth simulation.•The system would help researchers overcome technical barriers for gridded crop growth simulations to reduce the wall-clock time. The spatial distribution of crop yield has been assessed under current and future climate conditions using gridded crop growth simulations. This task usually requires considerable efforts to prepare input data and post-process the outputs. In the present study, the Gridded cRop grOWth simuLation suppoRt System (GROWLERS) was developed to automate repetitive and tedious tasks using multiple PCs. In particular, the system was designed to aid researchers who have minimum knowledge on computer programming, network, and cluster management. An object oriented programming language, C++, was used to design and implement the GROWLERS, which would increase flexibility of a system while simplifying complexity including supports for different types of gridded data. Functionality of the GROWLERS includes preparation of weather input files, launch of crop growth model, and creation of gridded output files. Tools for the GROWLERS were installed on virtual machines connected through local network, which allows for building of a cluster computer without dedicated workstations. In a case study, 5.8 × 107 simulations using the ORYZA2000 model were performed to examine spatial distribution of the optimum sowing date for rice under current climate conditions in Korea. The subsets of these simulations were allocated to groups of virtual machines hosted within five custom built personal computers of which the central processing unit was manufactured about 10 years ago. Weather input data were prepared automatically using the GROWLERS. A set of scripts were also prepared using the GROWLERS, which allowed to reduce the wall clock time by 88% using 16 processor cores for worker nodes. These results suggest that the GROWLERS would minimize researcher’s time involved in preparation and operation of a large number of crop growth simulations. Still, the support for nested simulations using multi-scale datasets would be needed to improve the GROWLERS, which merits further development as a next step.
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ISSN:0168-1699
1872-7107
DOI:10.1016/j.compag.2019.105196