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Performance analysis of message-passing libraries on high-speed clusters

机译:高速集群中消息传递库的性能分析

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This paper presents a performance analysis of message-passing overhead on high-speed clusters. Communication performance is critical for the overall high-speed cluster performance. In order to analyze the communication overhead, a new linear model proposed in this work is used for its characterization. Performance models have been derived using our own micro-benchmark suite on MPI C and emerging Java message-passing libraries. These models predict communication overhead quite accurately. Representative performance metrics have also been obtained in order to evaluate message-passing performance and establish comparisons among different message-passing libraries and clusters. Besides the evaluation process, communication models are useful to optimize parallel applications. Several model-based performance optimizations have been reported. Thus, inefficient primitives have been replaced by more efficient equivalent combinations of primitives. Through a kernel benchmarking it has been analyzed the influence of multiple processor nodes and the message-passing overhead on the overall application performance. From this analysis, it has been concluded that current message-passing implementations do not fully benefit from multiple processor nodes.
机译:本文介绍了高速群集上消息传递开销的性能分​​析。通信性能对于整体高速群集性能至关重要。为了分析通信开销,本文提出了一种新的线性模型进行表征。性能模型是使用我们自己的MPI C微基准套件和新兴的Java消息传递库得出的。这些模型相当准确地预测了通信开销。为了评估消息传递性能并建立不同消息传递库和群集之间的比较,还获得了代表性的性能指标。除了评估过程外,通信模型对于优化并行应用程序也很有用。已经报告了几种基于模型的性能优化。因此,低效的图元已被更有效的图元等效组合所代替。通过内核基准测试,已经分析了多个处理器节点的影响以及消息传递开销对整体应用程序性能的影响。根据该分析,可以得出结论,当前的消息传递实现不能完全从多个处理器节点中受益。

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