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REGULARIZED MARKOV CLUSTERING IN MPI AND MAP REDUCE

Varia, Siddharth

Abstract Details

2013, Master of Science, Ohio State University, Computer Science and Engineering.
The major objective of this thesis is to exploit parallelism in the clustering of graphs based on the simulation of stochastic flows and propose a scalable algorithm for the same. Over the past decade there has been a surge in the use of Map Reduce, MPI & CUDA for large scale graph mining. In this thesis, Map Reduce and MPI are being used to implement a parallel version of Regularized Markov Clustering (RMCL). RMCL is a variant of Markov clustering.
Srinivasan Parthasarathy, Prof. (Advisor)
P Sadayappan, Prof. (Committee Member)
58 p.

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Citations

  • Varia, S. (2013). REGULARIZED MARKOV CLUSTERING IN MPI AND MAP REDUCE [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1374153215

    APA Style (7th edition)

  • Varia, Siddharth. REGULARIZED MARKOV CLUSTERING IN MPI AND MAP REDUCE. 2013. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1374153215.

    MLA Style (8th edition)

  • Varia, Siddharth. "REGULARIZED MARKOV CLUSTERING IN MPI AND MAP REDUCE." Master's thesis, Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1374153215

    Chicago Manual of Style (17th edition)