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Phoenix: A Scalable Streaming Hypergraph Analysis Framework...

by Kuldeep R Kurte, Neena Imam, S M Shamimul Hasan, Ramakrishnan Kannan
Publication Type
Conference Paper
Book Title
Advances in Data Science and Information Engineering
Publication Date
Page Numbers
3 to 25
Publisher Location
Cham, Switzerland
Conference Name
16th Int. Conference on Data Science (ICDATA’20)
Conference Location
Las Vegas, Nevada, United States of America
Conference Sponsor
American Council on Science and Education
Conference Date
-

We present Phoenix, a scalable hypergraph analytics framework for data analytics and knowledge discovery that was implemented on the leadership class computing platforms at Oak Ridge National Laboratory (ORNL). Our software framework comprises a distributed implementation of a streaming server architecture which acts as a gateway for various hypergraph generators/external sources to connect. Phoenix has the capability to utilize diverse hypergraph generators, including HyGen, a very large-scale hypergraph generator developed by ORNL. Phoenix incorporates specific algorithms for efficient data representation by exploiting hidden structures of the hypergraphs. Our experimental results demonstrate Phoenix’s scalable and stable performance on massively parallel computing platforms. Phoenix’s superior performance is due to the merging of high-performance computing with data analytic.