NDLI: Designing Hybrid Architectures for Massive-Scale Graph Analysis

Content Provider	IEEE Xplore Digital Library
Author	Ediger, D. Bader, D.A.
Copyright Year	2013
Description	Author affiliation: Georgia Inst. of Technol., Atlanta, GA, USA (Ediger, D.; Bader, D.A.)
Abstract	Turning large volumes of data into actionable knowledge is a top challenge in high performance computing. Our previous work in this area demonstrated algorithmic techniques for massively parallel graph analysis on multithreaded systems. This work led to the development of GraphCT, the first end-to-end graph analytics platform for the Cray XMT and x86-class systems with OpenMP, and STINGER, a high performance, multithreaded, dynamic graph data structure and algorithms. Both of these packages are freely available as open source software. This dissertation research culminates in experimental and analytical techniques to study the marriage of disk-based systems, such as Hadoop, with shared memory-based systems, such as the Cray XMT, for data-intensive applications. David Ediger is a fifth year PhD candidate in Electrical and Computer Engineering.
Starting Page	2262
Ending Page	2265
File Size	183996
Page Count	4
File Format	PDF
e-ISBN	9780769549798
DOI	10.1109/IPDPSW.2013.172
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Databases Computational modeling Memory management Data warehouses Data models
Content Type	Text
Resource Type	Article

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