STINGER:用于流图的高性能数据结构

David Ediger, R. McColl, E. J. Riedy, David A. Bader
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引用次数: 204

摘要

目前对“大数据”问题的研究重点突出了所需分析的规模和复杂性,以及数据可能变化的高速率。在本文中,我们展示了我们的高性能,可扩展和便携式软件,时空交互网络和图形可扩展表示(STINGER),其中包括支持这些应用程序的图形数据结构。STINGER的关键属性是在倾斜度分布的语义图上快速插入、删除和更新。我们演示了在Cray XMT系列和Intel多核服务器上实现高性能的算法和架构优化过程。我们在Cray XMT上实现的STINGER每秒处理超过300万次更新,在一个无尺度图上有5.37亿个边。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
STINGER: High performance data structure for streaming graphs
The current research focus on “big data” problems highlights the scale and complexity of analytics required and the high rate at which data may be changing. In this paper, we present our high performance, scalable and portable software, Spatio-Temporal Interaction Networks and Graphs Extensible Representation (STINGER), that includes a graph data structure that enables these applications. Key attributes of STINGER are fast insertions, deletions, and updates on semantic graphs with skewed degree distributions. We demonstrate a process of algorithmic and architectural optimizations that enable high performance on the Cray XMT family and Intel multicore servers. Our implementation of STINGER on the Cray XMT processes over 3 million updates per second on a scale-free graph with 537 million edges.
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