Petascale computing for large-scale graph problems

David A. Bader

doi:10.1007/978-3-540-68111-3_18

Petascale computing for large-scale graph problems

David A. Bader

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

4 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	Parallel Processing and Applied Mathematics - 7th International Conference, PPAM 2007, Revised Selected Papers
Pages	166-169
Number of pages	4
DOIs	https://doi.org/10.1007/978-3-540-68111-3_18
State	Published - 2008
Externally published	Yes
Event	7th International Conference on Parallel Processing and Applied Mathematics, PPAM 2007 - Gdansk, Poland Duration: Sep 9 2007 → Sep 12 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4967 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	7th International Conference on Parallel Processing and Applied Mathematics, PPAM 2007
Country/Territory	Poland
City	Gdansk
Period	9/9/07 → 9/12/07

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-540-68111-3_18

Cite this

Bader, D. A. (2008). Petascale computing for large-scale graph problems. In Parallel Processing and Applied Mathematics - 7th International Conference, PPAM 2007, Revised Selected Papers (pp. 166-169). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4967 LNCS). https://doi.org/10.1007/978-3-540-68111-3_18

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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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Bader, DA 2008, Petascale computing for large-scale graph problems. in Parallel Processing and Applied Mathematics - 7th International Conference, PPAM 2007, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4967 LNCS, pp. 166-169, 7th International Conference on Parallel Processing and Applied Mathematics, PPAM 2007, Gdansk, Poland, 9/9/07. https://doi.org/10.1007/978-3-540-68111-3_18

Petascale computing for large-scale graph problems. / Bader, David A.
Parallel Processing and Applied Mathematics - 7th International Conference, PPAM 2007, Revised Selected Papers. 2008. p. 166-169 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4967 LNCS).

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

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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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ER -

Petascale computing for large-scale graph problems

Abstract

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Conference

All Science Journal Classification (ASJC) codes

Access to Document

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