.png){kind=icon}
返回
A PIPELINED ALGORITHM FOR LARGE, IRREGULAR ALL-GATHER PROBLEMS
.png){kind=icon}
PRE
AI
DOI：10.1177/1094342009359013.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We describe and evaluate a new pipelined algorithm for large, irregular all-gather problems. In the irregular all-gather problem each process in a set of processes contributes individual data of possibly different size, and all processes have to collect all data from all processes. The pipelined algorithm is useful for the implementation of the MPI_Allgatherv collective operation of the Message-Passing Interface (MPI) for large problems. By conception, the new algorithm is well suited to implementation on clustered multiprocessors, such as symmetric multiprocessing (SMP) clusters. The new algorithm has been implemented within different MPI libraries. Benchmark results on NEC SX-8, Linux clusters with InfiniBand and Gigabit Ethernet, IBM Blue Gene/P, and SiCortex systems show huge performance gains in accordance with the expected behavior.
Keyword:
message-passing interface
collective operations
all-gather problem
pipelining
NEC SX-8
Linux clusters
IBM Blue Gene/P
SiCortex
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
2.5
论文数:
1.1K
被引数:
1.3K
机构
查看更多机构
.png){kind=icon}
