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MPI Reduction Operations for Sparse Floating-point Data

机译:稀疏浮点数据的MPI减少操作

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This paper presents a pipeline algorithm for MPI_Reduce that uses a Run Length Encoding (RLE) scheme to improve the global reduction of sparse floating-point data. The RLE scheme is directly incorporated into the reduction process and causes only low overheads in the worst case. The high throughput of the RLE scheme allows performance improvements when using high performance interconnects, too. Random sample data and sparse vector data from a parallel FEM application is used to demonstrate the performance of the new reduction algorithm for an HPC Cluster with InfiniBand interconnects.
机译:本文提出了一种针对MPI_Reduce的流水线算法,该算法使用游程长度编码(RLE)方案来改善稀疏浮点数据的全局约简。 RLE方案直接合并到简化过程中,在最坏的情况下仅导致较低的开销。当使用高性能互连时,RLE方案的高吞吐量也可以提高性能。来自并行FEM应用程序的随机样本数据和稀疏矢量数据用于演示具有InfiniBand互连的HPC群集的新归约算法的性能。

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