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Online dynamic dependence analysis for speculative polyhedral parallelization
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
2013 (English)In: Euro-Par 2013 Parallel Processing, Springer Berlin/Heidelberg, 2013, 191-202 p.Conference paper, Published paper (Refereed)
Abstract [en]

We present a dynamic dependence analyzer whose goal is to compute dependencies from instrumented execution samples of loop nests. The resulting information serves as a prediction of the execution behavior during the remaining iterations and can be used to select and apply a speculatively optimizing and parallelizing polyhedral transformation of the target sequential loop nest. Thus, a parallel lock-free version can be generated which should not induce any rollback if the prediction is correct. The dependence analyzer computes distance vectors and linear functions interpolating the memory addresses accessed by each memory instruction, and the values of some scalars. Phases showing a changing memory behavior are detected thanks to a dynamic adjustment of the instrumentation frequency.

The dependence analyzer takes part of a whole framework dedicated to speculative parallelization of loop nests which has been implemented with extensions of the LLVM compiler and an x86-64 runtime system.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2013. 191-202 p.
Series
Lecture Notes in Computer Science, 8097
National Category
Computer Science
Identifiers
URN: urn:nbn:se:uu:diva-206800DOI: 10.1007/978-3-642-40047-6_21ISI: 000341243100021ISBN: 978-3-642-40046-9 (print)OAI: oai:DiVA.org:uu-206800DiVA: diva2:645482
Conference
Euro-Par 2013, August 26–30, Aachen, Germany
Projects
UPMARC
Available from: 2013-09-04 Created: 2013-09-04 Last updated: 2014-11-12Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
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Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
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Output format
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