VENUS: Vertex-centric streamlined graph computation on a single PC
Refereed conference paper presented and published in conference proceedings


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AbstractRecent studies show that disk-based graph computation on just a single PC can be as highly competitive as cluster-based computing systems on large-scale problems. Inspired by this remarkable progress, we develop VENUS, a disk-based graph computation system which is able to handle billion-scale problems efficiently on a commodity PC. VENUS adopts a novel computing architecture that features vertex-centric 'streamlined' processing - the graph is sequentially loaded and the update functions are executed in parallel on the fly. VENUS deliberately avoids loading batch edge data by separating read-only structure data from mutable vertex data on disk. Furthermore, it minimizes random IOs by caching vertex data in main memory. The streamlined processing is realized with efficient sequential scan over massive structure data and fast feeding a large number of update functions. Extensive evaluation on large real-world and synthetic graphs has demonstrated the efficiency of VENUS. For example, VENUS takes just 8 minutes with hard disk for PageRank on the Twitter graph with 1.5 billion edges. In contrast, Spark takes 8.1 minutes with 50 machines and 100 CPUs, and GraphChi takes 13 minutes using fast SSD drive.
All Author(s) ListCheng J., Liu Q., Li Z., Fan W., Lui J.C.S., He C.
Name of Conference2015 31st IEEE International Conference on Data Engineering, ICDE 2015
Start Date of Conference13/04/2015
End Date of Conference17/04/2015
Place of ConferenceSeoul
Country/Region of ConferenceSouth Korea
Detailed description This conference was considered as a tier-A conference venue as classified by the external visiting committee in FoE in 2011.
Year2015
Month1
Day1
Volume Number2015-May
Pages1131 - 1142
ISBN9781479979639
ISSN1084-4627
LanguagesEnglish-United Kingdom

Last updated on 2020-04-08 at 03:03