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Parallel Data-Flow Analysis for Multi-Core Machines
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.ORCID iD: 0000-0001-9775-4594
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.ORCID iD: 0000-0002-7565-3714
2011 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Static program analysis supporting software development is often part of edit-compile-cycles, and precise program analysis is time consuming. Points-to analysis is a data-flow-based static program analysis used to find object references in programs. Its applications include test case generation, compiler optimizations and program understanding, etc. Recent increases in processing power of desktop computers comes mainly from multiple cores. Parallel algorithms are vital for simultaneous use of multiple cores. An efficient parallel points-to analysis requires sufficient work for each processing unit.

The present paper presents a parallel points-to analysis of object-oriented programs. It exploits that (1) different target methods of polymorphic calls and (2) independent control-flow branches can be analyzed in parallel. Carefully selected thresholds guarantee that each parallel thread has sufficient work to do and that only little work is redundant with other threads. Our experiments show that this approach achieves a maximum speed-up of 4.5.

Place, publisher, year, edition, pages
2011.
Keywords [en]
Parallel algorithms, Static program analysis
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-7128OAI: oai:DiVA.org:lnu-7128DiVA, id: diva2:343126
Conference
High-Performance and Embedded Architectures and Compilers (HiPEAC'11)
Available from: 2010-08-12 Created: 2010-08-12 Last updated: 2018-05-17Bibliographically approved

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Edvinsson, MarcusLundberg, JonasLöwe, Welf

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