Parallel five-cycle counting algorithms
Name
1227275628-MIT.pdf
Size
1.08 MB
Format
Adobe PDF
Checksum (MD5)
4608e45d99fe6902752d5093e297c3f9
Author(s)
Huang, Louisa Ruixue.
Advisor(s)
Julian Shun.
Date Issued
2020
Publisher
Massachusetts Institute of Technology
Abstract
The frequency of given subgraphs in large graphs interests many research communities that use graphs to represent their data. However, subgraph counting is a challenging problem even with subgraph sizes as small as five due to combinatorial explosion. The first effort to count all five-vertex subgraphs in moderately large graphs of millions of edges did not occur until 2016. Among five-vertex patterns, the five-cycle is one of the most difficult to count. We design two new parallel five-cycle counting algorithms and prove that they are work-efficient and achieve polylogarithmic span. We implement the algorithms and perform a comprehensive evaluation of their performance. On a machine with 36 cores with two-way hyper-threading, our algorithm achieves 10-46x self-relative speed-up, and outperform the state-of-the-art serial algorithm by up to 818x.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, September, 2020
Cataloged from student-submitted PDF of thesis.
Includes bibliographical references (pages 49-53).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
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