Automatic Parallelization Using OpenMP Based on STL Semantics [electronic resource]

Automatic parallelization of sequential applications using OpenMP as a target has been attracting significant attention recently because of the popularity of multicore processors and the simplicity of using OpenMP to express parallelism for shared-memory systems. However, most previous research has...

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Bibliographic Details
Online Access: Online Access
Corporate Author: Lawrence Livermore National Laboratory (Researcher)
Format: Government Document Electronic eBook
Language:English
Published: Washington, D.C : Oak Ridge, Tenn. : United States. Dept. of Energy ; distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2008.
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Summary:Automatic parallelization of sequential applications using OpenMP as a target has been attracting significant attention recently because of the popularity of multicore processors and the simplicity of using OpenMP to express parallelism for shared-memory systems. However, most previous research has only focused on C and Fortran applications operating on primitive data types. C++ applications using high level abstractions such as STL containers are largely ignored due to the lack of research compilers that are readily able to recognize high level object-oriented abstractions of STL. In this paper, we use ROSE, a multiple-language source-to-source compiler infrastructure, to build a parallelizer that can recognize such high level semantics and parallelize C++ applications using certain STL containers. The idea of our work is to automatically insert OpenMP constructs using extended conventional dependence analysis and the known domain-specific semantics of high-level abstractions with optional assistance from source code annotations. In addition, the parallelizer is followed by an OpenMP translator to translate the generated OpenMP programs into multi-threaded code targeted to a popular OpenMP runtime library. Our work extends the applicability of automatic parallelization and provides another way to take advantage of multicore processors.
Item Description:Published through the Information Bridge: DOE Scientific and Technical Information.
06/03/2008.
"llnl-conf-404412"
Presented at: Languages and Compilers for Parallel Computing (LCPC), Edmonton, Canada, Jul 31 - Aug 02, 2008.
Panas, T; Quinlan, D J; Liao, C; Willcock, J J.
Physical Description:PDF-file: 17 pages; size: 0.2 Mbytes.