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Efficient data IO for a Parallel Global Cloud Resolving Model

Palmer, Bruce ; Koontz, Annette ; Schuchardt, Karen ; Heikes, Ross ; Randall, David

Environmental Modelling and Software, 2011, Vol.26(12), pp.1725-1735 [Periódico revisado por pares]

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  • Título:
    Efficient data IO for a Parallel Global Cloud Resolving Model
  • Autor: Palmer, Bruce ; Koontz, Annette ; Schuchardt, Karen ; Heikes, Ross ; Randall, David
  • Assuntos: High Performance Io ; Parallel Io Libraries ; Data Formatting ; Geodesic Grid ; Global Cloud Resolving Model ; Grid Specifications ; Engineering ; Environmental Sciences ; Computer Science ; Ecology
  • É parte de: Environmental Modelling and Software, 2011, Vol.26(12), pp.1725-1735
  • Descrição: Execution of a Global Cloud Resolving Model (GCRM) at target resolutions of 2–4 km will generate, at a minimum, 10s of Gigabytes of data per variable per snapshot. Writing this data to disk, without creating a serious bottleneck in the execution of the GCRM code, while also supporting efficient post-execution data analysis is a significant challenge. This paper discusses an Input/Output (IO) application programmer interface (API) for the GCRM that efficiently moves data from the model to disk while maintaining support for community standard formats, avoiding the creation of very large numbers of files, and supporting efficient analysis. Several aspects of the API will be discussed in detail. First, we discuss the output data layout which linearizes the data in a consistent way that is independent of the number of processors used to run the simulation and provides a convenient format for subsequent analyses of the data. Second, we discuss the flexible API interface that enables...
  • Idioma: Inglês

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