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Common modeling infrastructure refers to software libraries that can be shared across multiple institutions in order to increase software reuse and interoperability in complex modeling systems. Early initiatives were in the climate and weather domain, where software components representing distinct physical domains (for example, ocean or atmosphere) tended to be developed by domain specialists, often at different organizations. In order to create complete applications, these needed to be combined, using for instance a general circulation model, that transfers data between different components. An additional challenge is that these models generally require supercomputers to run, to account for the collected data and for data analyses. Thus, it was important to provide an efficient massively

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  • Common modeling infrastructure (en)
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  • Common modeling infrastructure refers to software libraries that can be shared across multiple institutions in order to increase software reuse and interoperability in complex modeling systems. Early initiatives were in the climate and weather domain, where software components representing distinct physical domains (for example, ocean or atmosphere) tended to be developed by domain specialists, often at different organizations. In order to create complete applications, these needed to be combined, using for instance a general circulation model, that transfers data between different components. An additional challenge is that these models generally require supercomputers to run, to account for the collected data and for data analyses. Thus, it was important to provide an efficient massively (en)
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  • Common modeling infrastructure refers to software libraries that can be shared across multiple institutions in order to increase software reuse and interoperability in complex modeling systems. Early initiatives were in the climate and weather domain, where software components representing distinct physical domains (for example, ocean or atmosphere) tended to be developed by domain specialists, often at different organizations. In order to create complete applications, these needed to be combined, using for instance a general circulation model, that transfers data between different components. An additional challenge is that these models generally require supercomputers to run, to account for the collected data and for data analyses. Thus, it was important to provide an efficient massively parallel computer system, and the processing hardware and software, to account for all the different workloads and communication channels. (en)
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