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 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Amsterdam
Elsevier B.V
01.02.2020
Elsevier BV |
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| ISSN: | 0168-1699, 1872-7107 |
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| Abstract | •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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| AbstractList | •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. 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. 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. |
| ArticleNumber | 105196 |
| Author | Hyun, Shinwoo Kim, Kwang Soo Kim, Junhwan Park, Jinew Fleisher, David H. |
| Author_xml | – sequence: 1 givenname: Junhwan surname: Kim fullname: Kim, Junhwan organization: Crop Production & Physiology Division, National Institute of Crop Science, Rural Development Administration, Wanju-gun, Jeollabuk-do 55365, Republic of Korea – sequence: 2 givenname: Jinew surname: Park fullname: Park, Jinew organization: Department of Plant Science, Seoul National University, Seoul 08826, Republic of Korea – sequence: 3 givenname: Shinwoo surname: Hyun fullname: Hyun, Shinwoo organization: Department of Plant Science, Seoul National University, Seoul 08826, Republic of Korea – sequence: 4 givenname: David H. surname: Fleisher fullname: Fleisher, David H. organization: Adaptive Cropping Systems Laboratory, United States Department of Agriculture – Agricultural Research Service, Beltsville, MD 20705, USA – sequence: 5 givenname: Kwang Soo surname: Kim fullname: Kim, Kwang Soo email: luxkwang@snu.ac.kr organization: Department of Plant Science, Seoul National University, Seoul 08826, Republic of Korea |
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| Snippet | •A distributed computing system, GROWLERS, was developed for crop growth simulations.•GROWLERS requires minimum sets of user inputs and manual operations for... The spatial distribution of crop yield has been assessed under current and future climate conditions using gridded crop growth simulations. This task usually... |
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| SubjectTerms | 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 |
| Title | Development of an automated gridded crop growth simulation support system for distributed computing with virtual machines |
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