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Topology-oblivious optimization of MPI broadcast algorithms on extreme-scale platforms

机译:极端规模平台上MPI广播算法的拓扑无关性优化

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摘要

Significant research has been conducted in collective communication operations, in particular in MPI broadcast, on distributed memory platforms. Most of the research efforts aim to optimize the collective operations for particular architectures by taking into account either their topology or platform parameters. In this work we propose a simple but general approach to optimization of the legacy MPI broadcast algorithms, which are widely used in MPICH and Open MPI. The proposed optimization technique is designed to address the challenge of extreme scale of future HPC platforms. It is based on hierarchical transformation of the traditionally flat logical arrangement of communicating processors. Theoretical analysis and experimental results on IBM BlueGene/P and a cluster of the Grid'5000 platform are presented. (C) 2015 Elsevier B.V. All rights reserved.
机译:在分布式存储平台上的集体通信操作中,尤其是在MPI广播中,已经进行了重大研究。大多数研究工作旨在通过考虑特定拓扑的拓扑或平台参数来优化其总体操作。在这项工作中,我们提出了一种简单但通用的方法来优化传统MPI广播算法,该算法在MPICH和Open MPI中得到了广泛使用。拟议的优化技术旨在解决未来HPC平台的极端规模挑战。它基于通信处理器的传统扁平逻辑排列的分层转换。介绍了在IBM BlueGene / P和Grid'5000平台的集群上的理论分析和实验结果。 (C)2015 Elsevier B.V.保留所有权利。

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