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Simple, efficient allocation of modelling runs on heterogeneous clusters with MPI

机译:简单,有效的建模分配在具有MPI的异构集群上运行

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In scientific modelling and computation, the choice of an appropriate method for allocating tasks for parallel processing depends on the computational setting and on the nature of the computation. The allocation of independent but similar computational tasks, such as modelling runs or Monte Carlo trials, among the nodes of a heterogeneous computational cluster is a special case that has not been specifically evaluated previously. A simulation study shows that a method of on-demand (that is, worker-initiated) pulling from a bag of tasks in this case leads to reliably short makespans for computational jobs despite heterogeneity both within and between cluster nodes. A simple reference implementation in the C programming language with the Message Passing Interface (MPI) is provided. Published by Elsevier Ltd.
机译:在科学建模和计算中,为并行处理分配任务的适当方法的选择取决于计算设置和计算的性质。在异构计算集群的节点之间分配独立但相似的计算任务(例如建模运行或蒙特卡洛试验)是一种特殊情况,以前没有专门评估过。仿真研究表明,在这种情况下,从一袋任务中按需(即由工作人员启动)拉动的方法可以可靠地缩短计算工作的跨度,尽管集群节点内部和节点之间存在异构性。提供了带有消息传递接口(MPI)的C编程语言的简单参考实现。由Elsevier Ltd.发布

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