GPU-based matrix multiplication methods for social networks analysis

Yong-Yeon Jo, Sang-Wook Kim, Duck-Ho Bae
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引用次数: 2

Abstract

A matrix multiplication is a building block for social networks analysis. Recently, there have been various methods proposed for GPU-based matrix multiplications. NVIDIA, one of major manufacturers of GPUs, has also proposed various matrix multiplication methods based on GPUs. In this paper, we introduce the methods, and evaluate their performance via extensive experiments using synthetic and real-world datasets. Our results would help practitioners choose the best one for analyzing real-world social networks.
基于gpu的社会网络矩阵乘法分析方法
矩阵乘法是社会网络分析的基石。最近,人们提出了各种基于gpu的矩阵乘法方法。作为gpu的主要制造商之一,NVIDIA也提出了各种基于gpu的矩阵乘法方法。在本文中,我们介绍了这些方法,并通过使用合成和现实世界数据集的大量实验来评估它们的性能。我们的结果将帮助从业者选择最好的一个来分析现实世界的社会网络。
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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