在PC上的大型图上缩放KNN计算

Proceedings of the Posters and Demos Session of the 15th International Middleware Conference Pub Date : 2014-12-08 DOI:10.1145/2678508.2678513

Nitin Chiluka, Anne-Marie Kermarrec, J. Olivares

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引用次数: 4

摘要

本文提出了一种利用商用PC上的磁盘和内存高效地计算大用户集上k -最近邻(KNN)算法的新方法。为了更好地利用计算能力，提高算法效率，系统的设计是尽量减少对磁盘的随机访问和从磁盘加载/卸载的数据量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Scaling KNN computation over large graphs on a PC

This paper proposes a novel approach to compute K-Nearest Neighbors (KNN) algorithm on a large set of users by leveraging disk and memory efficiently on a commodity PC. The system is designed to minimize random accesses to disk as well as the amount of data loaded/unloaded from/to disk so as to better utilize the computational power, thus improving the algorithmic efficiency.

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Proceedings of the Posters and Demos Session of the 15th International Middleware Conference

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