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Multiple data parallelism with HPF and KeLP

机译:HPF和KeLP的多数据并行

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High Performance Fortran (HPF) is an effective language for implementing regular data parallel applications on distributed memory architectures, but it is not well studied to irregular, block-structured applications such as multiblock and adaptive mesh methods. A solution to this problem is to use an SPMD program to coordinate multiple concurrent HPF tasks, each operating on a regular subgrid of the multiblock domain. This paper presents such a system, in which the coordination layer is provided by the C++ class library KeLP. We describe the KeLP-HPF implementation and programming model, and show an example KeLP-HPF multiblock solver together with performance results.
机译:高性能Fortran(HPF)是一种用于在分布式内存体系结构上实现常规数据并行应用程序的有效语言,但是对不规则,块结构化的应用程序(例如多块和自适应网格方法)的研究还不够深入。解决此问题的方法是使用SPMD程序来协调多个并发HPF任务,每个任务都在多块域的常规子网格上运行。本文提出了一种这样的系统,其中协调层由C ++类库KeLP提供。我们描述了KeLP-HPF实现和编程模型,并给出了一个示例KeLP-HPF多块求解器以及性能结果。

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