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Title
Japanese:GPGPUを用いた高速大規模グラフ処理に向けて 
English:Towards GPGPU-Based Large-Scale Fast Graph Processing 
Author
Japanese: 白幡晃一, 佐藤仁, 鈴村豊太郎, 松岡聡.  
English: Koichi Shirahata, Hitoshi Sato, Toyotaro Suzumura, SATOSHI MATSUOKA.  
Language Japanese 
Journal/Book name
Japanese:情報処理学会研究報告2011-HPC-130 
English: 
Volume, Number, Page     No. 14    pp. 1--8
Published date Aug. 2011 
Publisher
Japanese: 
English: 
Conference name
Japanese:第130回 ハイパフォーマンスコンピューティング研究発表会 2011年並列／分散／協調処理に関する 『鹿児島』サマー・ワークショップ（SWoPP鹿児島2011） 
English: 
Conference site
Japanese:鹿児島 
English: 
Official URL http://www.hpcc.jp/swopp/
 
Abstract Large-scale graph processing is becoming more important due to the large vol-ume of available data, the low cost of storage and the stunning success of onlinesocial networks. Besides, recent large-scale computing systems tend to employGPUs to gain good peak performance and high memory bandwidth. Mars isone of the MapReduce library accelerated with GPUs;however, the problemson GPGPU-based large-scale graph processing, such as the performance im-provement by using GPUs, the memory management in GPUs, and the datadistribution between multiple GPUs, are not investigated. In order to clarifythe problems, we implemented several graph processing applications such asPageRank, Random Walk with Restart(RWR) and Connected Components ontop of Mars and compared the results with PEGASUS, one of the large-scalegraph processing library. Our experimental results show that the mean time ofone iteration in Mars is 2.17-9.53 times faster on PageRank, 2.18-5.47 times onRWR, and 2.51-8.46 times on Connected Components respectively comparedwith PEGASUS.

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