NDLI: Automatic speculative parallelization of loops using polyhedral dependence analysis

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Automatic speculative parallelization of loops using polyhedral dependence analysis

Content Provider	ACM Digital Library
Author	Bhattacharyya, Arnamoy Amaral, José Nelson
Abstract	Speculative Execution (SE) runs loops in parallel even in the presence of a dependence. Using polyhedral dependence analysis, more speculation candidate loops can be discovered than normal OpenMP parallelization. In this research, a framework is implemented that can automatically perform speculative parallelization of loops using Polly's [15] polyhedral dependence analysis. The framework uses two different heuristics to find speculation candidates. The first heuristic allows loops with only may dependences to run speculatively in parallel while the second heuristic filters out cold loops and, using profile information, loops with actual run time dependences. The framework is fully automatic. Running SPEC2006 and the PolyBench/C benchmarks on the IBM BlueGene/Q [16] machine shows that the framework is able to discover more parallelization candidates than OpenMP parallelization and achieve better speedup.
Starting Page	1
Ending Page	9
Page Count	9
File Format	PDF
ISBN	9781450319713
DOI	10.1145/2446920.2446921
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-02-24
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Auto-parallelization Polyhedral model Thread level speculation
Content Type	Text
Resource Type	Article

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