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Workload decomposition strategies for hierarchical distributed-shared memory parallel systems and their implementation with integration of high-level parallel languages

机译:用于分层分布式共享内存并行系统的工作负载分解策略及其实现,具有高级并行语言的集成

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In this paper we address the issue of workload decomposition in programming hierarchical distributed- shared memory parallel systems. The workload decomposition we have devised consists of a two-stage procedure: a higher-level decomposition among the computational nodes; and a lower-level one among the processors of each computational node. By focusing on porting of a case study particle-in-cell application, we have implemented the described work decomposition without large programming effort by using and integrating the high-level language extensions High-Performance Fortran and OpenMP.
机译:在本文中,我们在编程分布式共享内存并行系统中解决了工作负载分解问题。我们设计的工作负载分解包括两阶段过程:计算节点之间的更高级别分解;和每个计算节点的处理器中的较低级别。通过专注于移植案例研究粒子内应用程序,我们通过使用并集成了高级语言扩展高性能FORTRAN和OpenMP而无需大量编程工作,我们已经实现了所描述的工作分解。

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