The STAPL pView

Antal Buss; Adam Fidel; Harshvardhan; Timmie Smith; Gabriel Tanase; Nathan Thomas; Xiabing Xu; Mauro Bianco; Nancy M. Amato; Lawrence Rauchwerger

doi:10.1007/978-3-642-19595-2_18

The STAPL pView

Antal Buss, Adam Fidel, Harshvardhan, Timmie Smith, Gabriel Tanase, Nathan Thomas, Xiabing Xu, Mauro Bianco, Nancy M. Amato, Lawrence Rauchwerger

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

6 Scopus citations

Abstract

The Standard Template Adaptive Parallel Library (STAPL) is a C++ parallel programming library that provides a collection of distributed data structures (pContainers) and parallel algorithms (pAlgorithms) and a generic methodology for extending them to provide customized functionality. STAPL algorithms are written in terms of pViews, which provide a generic access interface to pContainer data by abstracting common data structure concepts. Briefly, pViews allow the same pContainer to present multiple interfaces, e.g., enabling the same pMatrix to be 'viewed' (or used) as a row-major or column-major matrix, or even as a vector. In this paper, we describe the stapl pView concept and its properties. pViews generalize the iterator concept and enable parallelism by providing random access to, and an ADT for, collections of elements. We illustrate how pViews provide support for managing the tradeoff between expressivity and performance and examine the performance overhead incurred when using pViews. © 2011 Springer-Verlag Berlin Heidelberg.

Original language	English (US)
Title of host publication	Languages and Compilers for Parallel Computing
Publisher	Springer Nature
Pages	261-275
Number of pages	15
ISBN (Print)	9783642195945
DOIs	https://doi.org/10.1007/978-3-642-19595-2_18
State	Published - 2011
Externally published	Yes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUS-C1-016-04
Acknowledgements: This research supported in part by NSF awards CRI-0551685, CCF-0833199, CCF-0830753, IIS-096053, IIS-0917266, NSF/DNDO award 2008-DN-077-ARI018-02, bythe DOE NNSA under the Predictive Science Academic Alliances Program by grantDE-FC52-08NA28616, by THECB NHARP award 000512-0097-2009, by Chevron,IBM, Intel, Oracle/Sun and by Award KUS-C1-016-04, made by King AbdullahUniversity of Science and Technology (KAUST). This research used resources of theNational Energy Research Scientific Computing Center, which is supported by theOffice of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. Tanase is now a Research Staff Member at IBM T.J. Watson ResearchCenter. Bianco is now a scientist at the Swiss National Supercomputing Centre.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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10.1007/978-3-642-19595-2_18

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title = "The STAPL pView",

abstract = "The Standard Template Adaptive Parallel Library (STAPL) is a C++ parallel programming library that provides a collection of distributed data structures (pContainers) and parallel algorithms (pAlgorithms) and a generic methodology for extending them to provide customized functionality. STAPL algorithms are written in terms of pViews, which provide a generic access interface to pContainer data by abstracting common data structure concepts. Briefly, pViews allow the same pContainer to present multiple interfaces, e.g., enabling the same pMatrix to be 'viewed' (or used) as a row-major or column-major matrix, or even as a vector. In this paper, we describe the stapl pView concept and its properties. pViews generalize the iterator concept and enable parallelism by providing random access to, and an ADT for, collections of elements. We illustrate how pViews provide support for managing the tradeoff between expressivity and performance and examine the performance overhead incurred when using pViews. {\textcopyright} 2011 Springer-Verlag Berlin Heidelberg.",

author = "Antal Buss and Adam Fidel and Harshvardhan and Timmie Smith and Gabriel Tanase and Nathan Thomas and Xiabing Xu and Mauro Bianco and Amato, {Nancy M.} and Lawrence Rauchwerger",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledged KAUST grant number(s): KUS-C1-016-04 Acknowledgements: This research supported in part by NSF awards CRI-0551685, CCF-0833199, CCF-0830753, IIS-096053, IIS-0917266, NSF/DNDO award 2008-DN-077-ARI018-02, bythe DOE NNSA under the Predictive Science Academic Alliances Program by grantDE-FC52-08NA28616, by THECB NHARP award 000512-0097-2009, by Chevron,IBM, Intel, Oracle/Sun and by Award KUS-C1-016-04, made by King AbdullahUniversity of Science and Technology (KAUST). This research used resources of theNational Energy Research Scientific Computing Center, which is supported by theOffice of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. Tanase is now a Research Staff Member at IBM T.J. Watson ResearchCenter. Bianco is now a scientist at the Swiss National Supercomputing Centre. This publication acknowledges KAUST support, but has no KAUST affiliated authors.",

year = "2011",

doi = "10.1007/978-3-642-19595-2_18",

language = "English (US)",

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AU - Thomas, Nathan

AU - Xu, Xiabing

AU - Bianco, Mauro

AU - Amato, Nancy M.

AU - Rauchwerger, Lawrence

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledged KAUST grant number(s): KUS-C1-016-04 Acknowledgements: This research supported in part by NSF awards CRI-0551685, CCF-0833199, CCF-0830753, IIS-096053, IIS-0917266, NSF/DNDO award 2008-DN-077-ARI018-02, bythe DOE NNSA under the Predictive Science Academic Alliances Program by grantDE-FC52-08NA28616, by THECB NHARP award 000512-0097-2009, by Chevron,IBM, Intel, Oracle/Sun and by Award KUS-C1-016-04, made by King AbdullahUniversity of Science and Technology (KAUST). This research used resources of theNational Energy Research Scientific Computing Center, which is supported by theOffice of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. Tanase is now a Research Staff Member at IBM T.J. Watson ResearchCenter. Bianco is now a scientist at the Swiss National Supercomputing Centre. This publication acknowledges KAUST support, but has no KAUST affiliated authors.

PY - 2011

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N2 - The Standard Template Adaptive Parallel Library (STAPL) is a C++ parallel programming library that provides a collection of distributed data structures (pContainers) and parallel algorithms (pAlgorithms) and a generic methodology for extending them to provide customized functionality. STAPL algorithms are written in terms of pViews, which provide a generic access interface to pContainer data by abstracting common data structure concepts. Briefly, pViews allow the same pContainer to present multiple interfaces, e.g., enabling the same pMatrix to be 'viewed' (or used) as a row-major or column-major matrix, or even as a vector. In this paper, we describe the stapl pView concept and its properties. pViews generalize the iterator concept and enable parallelism by providing random access to, and an ADT for, collections of elements. We illustrate how pViews provide support for managing the tradeoff between expressivity and performance and examine the performance overhead incurred when using pViews. © 2011 Springer-Verlag Berlin Heidelberg.

AB - The Standard Template Adaptive Parallel Library (STAPL) is a C++ parallel programming library that provides a collection of distributed data structures (pContainers) and parallel algorithms (pAlgorithms) and a generic methodology for extending them to provide customized functionality. STAPL algorithms are written in terms of pViews, which provide a generic access interface to pContainer data by abstracting common data structure concepts. Briefly, pViews allow the same pContainer to present multiple interfaces, e.g., enabling the same pMatrix to be 'viewed' (or used) as a row-major or column-major matrix, or even as a vector. In this paper, we describe the stapl pView concept and its properties. pViews generalize the iterator concept and enable parallelism by providing random access to, and an ADT for, collections of elements. We illustrate how pViews provide support for managing the tradeoff between expressivity and performance and examine the performance overhead incurred when using pViews. © 2011 Springer-Verlag Berlin Heidelberg.

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BT - Languages and Compilers for Parallel Computing

PB - Springer Nature

ER -

The STAPL pView

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