sponsored byACMIEEE The International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 15-20, 2015

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Benchmarking High Performance Graph Analysis Systems with Graph Mining and Pattern Matching Workloads

SESSION: Regular & ACM Student Research Competition Poster Reception

EVENT TYPE: Posters, Receptions, ACM Student Research Competition

EVENT TAG(S): HPC Beginner Friendly, Regular Poster

TIME: 5:15PM - 7:00PM

SESSION CHAIR(S): Michela Becchi, Manish Parashar, Dorian C. Arnold

AUTHOR(S):Seokyong Hong, Seung-Hwan Lim, Sangkeun Lee, Sreenivas R. Sukumar, Ranga R. Vatsavai

ROOM:Level 4 - Lobby


The increases in volume and inter-connectivity of graph data result in the emergence of recent scalable and high performance graph analysis systems. Those systems provide different graph representation models, a variety of querying interfaces and libraries, and several underlying computation models. As a consequence, such diversities complicate in-situ choices of optimal platforms for data scientists given graph analysis workloads. In this poster presentation, we compare recent high performance and scalable graph analysis systems in distributed and supercomputer-based processing environments with two important graph analysis workloads: graph mining and graph pattern matching. We also compare those systems in terms of expressiveness and suitability of their querying interfaces for the two distinct workloads.

Chair/Author Details:

Michela Becchi, Manish Parashar, Dorian C. Arnold (Chair) - University of Missouri|Rutgers University|University of New Mexico|

Seokyong Hong - North Carolina State University

Seung-Hwan Lim - Oak Ridge National Laboratory

Sangkeun Lee - Oak Ridge National Laboratory

Sreenivas R. Sukumar - Oak Ridge National Laboratory

Ranga R. Vatsavai - North Carolina State University

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