The STAPL pView

Authors:
Antal Buss;Adam Fidel;Harshvardhan Harshvardhan;Timmie Smith;Gabriel Tanase;Nathan Thomas;Xiabing Xu;Mauro Bianco;Nancy M. Amato;Lawrence Rauchwerger
Affiliations:
Parasol Lab, Dept. of Computer Science and Engineering, Texas A&M University;Parasol Lab, Dept. of Computer Science and Engineering, Texas A&M University;Parasol Lab, Dept. of Computer Science and Engineering, Texas A&M University;Parasol Lab, Dept. of Computer Science and Engineering, Texas A&M University;Parasol Lab, Dept. of Computer Science and Engineering, Texas A&M University;Parasol Lab, Dept. of Computer Science and Engineering, Texas A&M University;Parasol Lab, Dept. of Computer Science and Engineering, Texas A&M University;Parasol Lab, Dept. of Computer Science and Engineering, Texas A&M University;Parasol Lab, Dept. of Computer Science and Engineering, Texas A&M University;Parasol Lab, Dept. of Computer Science and Engineering, Texas A&M University
Venue:
LCPC'10 Proceedings of the 23rd international conference on Languages and compilers for parallel computing
Year:
2010

Citing 12
Cited 1

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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.