Petascale computing for large-scale graph problems

David A. Bader

doi:10.1109/IPDPS.2007.370556

Petascale computing for large-scale graph problems

David A. Bader

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Graph theoretic problems are representative of fundamental kernels in traditional and emerging computational sciences such as chemistry, biology, and medicine, as well as applications in national security. Yet they pose serious challenges for parallel machines due to non-contiguous, concurrent accesses to global data structures with low degrees of locality. Few parallel graph algorithms outperform their best sequential implementation due to long memory latencies and high synchronization costs. In this talk, we consider several graph theoretic kernels for connectivity and centrality and discuss how the features of petascale architectures will affect algorithm development, ease of programming, performance, and scalability.

Original language	English (US)
Title of host publication	Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM
DOIs	https://doi.org/10.1109/IPDPS.2007.370556
State	Published - 2007
Externally published	Yes
Event	21st International Parallel and Distributed Processing Symposium, IPDPS 2007 - Long Beach, CA, United States Duration: Mar 26 2007 → Mar 30 2007

Publication series

Name	Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM

Other

Other	21st International Parallel and Distributed Processing Symposium, IPDPS 2007
Country/Territory	United States
City	Long Beach, CA
Period	3/26/07 → 3/30/07

All Science Journal Classification (ASJC) codes

Hardware and Architecture
Software
General Mathematics

Access to Document

10.1109/IPDPS.2007.370556

Cite this

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title = "Petascale computing for large-scale graph problems",

abstract = "Graph theoretic problems are representative of fundamental kernels in traditional and emerging computational sciences such as chemistry, biology, and medicine, as well as applications in national security. Yet they pose serious challenges for parallel machines due to non-contiguous, concurrent accesses to global data structures with low degrees of locality. Few parallel graph algorithms outperform their best sequential implementation due to long memory latencies and high synchronization costs. In this talk, we consider several graph theoretic kernels for connectivity and centrality and discuss how the features of petascale architectures will affect algorithm development, ease of programming, performance, and scalability.",

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year = "2007",

doi = "10.1109/IPDPS.2007.370556",

language = "English (US)",

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booktitle = "Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM",

note = "21st International Parallel and Distributed Processing Symposium, IPDPS 2007 ; Conference date: 26-03-2007 Through 30-03-2007",

}

Bader, DA 2007, Petascale computing for large-scale graph problems. in Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM., 4228284, Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM, 21st International Parallel and Distributed Processing Symposium, IPDPS 2007, Long Beach, CA, United States, 3/26/07. https://doi.org/10.1109/IPDPS.2007.370556

Petascale computing for large-scale graph problems. / Bader, David A.
Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM. 2007. 4228284 (Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - Graph theoretic problems are representative of fundamental kernels in traditional and emerging computational sciences such as chemistry, biology, and medicine, as well as applications in national security. Yet they pose serious challenges for parallel machines due to non-contiguous, concurrent accesses to global data structures with low degrees of locality. Few parallel graph algorithms outperform their best sequential implementation due to long memory latencies and high synchronization costs. In this talk, we consider several graph theoretic kernels for connectivity and centrality and discuss how the features of petascale architectures will affect algorithm development, ease of programming, performance, and scalability.

AB - Graph theoretic problems are representative of fundamental kernels in traditional and emerging computational sciences such as chemistry, biology, and medicine, as well as applications in national security. Yet they pose serious challenges for parallel machines due to non-contiguous, concurrent accesses to global data structures with low degrees of locality. Few parallel graph algorithms outperform their best sequential implementation due to long memory latencies and high synchronization costs. In this talk, we consider several graph theoretic kernels for connectivity and centrality and discuss how the features of petascale architectures will affect algorithm development, ease of programming, performance, and scalability.

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Y2 - 26 March 2007 through 30 March 2007

ER -

Petascale computing for large-scale graph problems

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

Access to Document

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