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Double standards

机译:双重标准

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摘要

High Performance Fortran (HPF) does not allow efficient expression of mixed task/data-parallel computations or the coupling of separately compiled data-parallel modules. In this paper, we show how a coordination library implementing the Message Passing Interface (MPI) can be used to represent these common parallel program structures. This library allows data-parallel tasks to exchange distributed data structures using calls to simple communication functions. We present microbenchmark results that characterize the performance of this library and that quantify the impact of optimizations that allow reuse of communication schedules in common situations. In addition, results from two-dimensional FFT, convolution, and multiblock programs demonstrate that the HPF/MPI library can provide performance superior to that of pure HPF. We conclude that this synergistic combination of two parallel programming standards represents a useful approach to task parallelism in a data-parallel framework, increasing the range of problems addressable in HPF without requiring complex compiler technology.

机译:

高性能Fortran(HPF)不允许高效表达混合任务/数据并行计算或耦合单独编译的数据并行模块。在本文中,我们展示了如何使用实现消息传递接口(MPI)的协调库来表示这些常见的并行程序结构。该库允许数据并行任务使用对简单通信功能的调用来交换分布式数据结构。我们提供了微基准测试结果,这些结果表征了该库的性能,并量化了优化的影响,这些优化允许在常见情况下重用通信计划。此外,二维FFT,卷积和多块程序的结果表明,HPF / MPI库可提供优于纯HPF的性能。我们得出的结论是,两种并行编程标准的这种协同组合代表了一种在数据并行框架中解决任务并行性的有用方法,从而无需复杂的编译器技术即可扩大HPF可解决的问题范围。

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