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PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
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DTSTART:20151119T201500Z
DTEND:20151119T203000Z
LOCATION:Ballroom E
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: My dissertation research lies at the interface of high performance computing and big data analytics. Specifically, my work focuses on designing new parallel approaches for analyzing large real-world networks. The high complexity, scale, and variation of graph-structured data poses an immense challenge in the design of techniques to study and derive insight from such data. Optimizing graph analysis software for complex and heterogeneous modern HPC systems poses an additional set of challenges for algorithm designers to overcome. My primary research goals focus on tackling these problems through the optimization of graph analytics at all levels of hardware architecture, from thread to core to processor to single-node to multi-node to system-level scale. The fact that graph-structured data is so universal means that this research is useful to a large collection of data-intensive problems within both the social and physical sciences.
SUMMARY:Irregular Graph Algorithms on Parallel Processing Systems
PRIORITY:3
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