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A two-level parallelization method for distributed hydrological models

机译:a two-level parallelization method for distributed hydrological models

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摘要

This paper proposes a scalable two-level parallelization method for distributed hydrological models that can use parallelizability at both the sub-basin level and the basic simulation-unit level (e.g., grid cell) simultaneously. This approach first uses the message-passing programming model to dispatch parallel tasks at the sub-basin level to different nodes with multi-core CPUs in the cluster. Each node is responsible for some of the sub-basins. Parallel tasks for each sub-basin at the basic simulation-unit level are then dispatched to multiple cores within each node using the shared-memory programming model. A grid-based distributed hydrological model was parallelized to demonstrate the performance of the proposed method, which was tested in different scenarios (e.g., different data volume, different numbers of sub-basins). Results show that the proposed two-level parallelization method had better scalability than the parallel computation at sub-basin level alone, and the parallel performance increased with data volume and the number of sub-basins. (C) 2016 Elsevier Ltd. All rights reserved.
机译:本文针对分布式水文模型提出了一种可扩展的两级并行化方法,该方法可以在子流域一级和基本模拟单元一级(例如网格单元)同时使用并行性。此方法首先使用消息传递编程模型将子盆地级别的并行任务分派给群集中具有多核CPU的不同节点。每个节点负责一些子流域。然后,使用共享内存编程模型将基本仿真单元级别上每个子流域的并行任务分派到每个节点内的多个核心。对基于网格的分布式水文模型进行了并行处理,以证明所提出方法的性能,该方法已在不同场景(例如,不同数据量,不同子盆地数量)中进行了测试。结果表明,所提出的两级并行化方法具有比单独在子流域级的并行计算更好的可伸缩性,并且并行性能随数据量和子流域数的增加而提高。 (C)2016 Elsevier Ltd.保留所有权利。

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