EFFICIENCY OF ECOLOGICAL-CLIMATE AND OTHER MODELS BY DISTRIBUTING CALCULATIONS
DOI:
https://doi.org/10.31471/2415-3184-2021-1(23)-54-59Keywords:
distributed computing, environmental modeling, climate modeling, computing power, supercomputer, projects, global problems, World Community GridAbstract
Modern scientific models require significant computing power and access to the capabilities of supercomputers. The solution to this problem is the Distributed Computing Interface (BOINC), based on Berkeley's open software platform for GRID computing. This is a software for distributing an array of information between personal computers and further mathematical processing. Many universities in the world work with this system to solve problems, and formed national centers for grid computing, which includes many teams and individual volunteers.
In Ukraine, this center is called the Ukrainian National Grid (UNG) and is the only research national e-infrastructure in Ukraine, which brings together 39 resource centers of research organizations (29 belong to the NAS of Ukraine). UNG's integration into the European system helps to work together on global problems in mathematics, ecology and physics, using European resources for data processing and storage.
Mathematical models are widely used in ecology. They are empovered to make ecological and climatic forecasts, model the physical properties of natural components under different conditions to ensure optimal conditions for certain phenomena under study. The effectiveness of the application of grid technologies in ecology is demonstrated by successfully completed and current research projects of World Community Grid, which results have global significance.
With the development of distributed computing in science and the popularity of cryptography there is a problem of the feasibility of available users of desktop (personal computer) with their potentially low power and the need to analyze their effectiveness in various grid projects to determine the most effective use.
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References
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