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Automatic Parallel Pattern Detection in the Algorithm Structure Design Space

Authors: Zia Ul Huda; Rohit Atre; Ali Jannesari; Felix Wolf 0001;

Automatic Parallel Pattern Detection in the Algorithm Structure Design Space

Abstract

Parallel design patterns have been developed to help programmers efficiently design and implement parallel applications. However, identifying a suitable parallel pattern for a specific code region in a sequential application is a difficult task. Transforming an application according to support structures applicable to these parallel patterns is also very challenging. In this paper, we present a novel approach to automatically find parallel patterns in the algorithm structure design space of sequential applications. In our approach, we classify code blocks in a region according to the appropriate supportstructure of the detected pattern. This classification eases the transformation of a sequential application into its parallel version. Weevaluated our approach on 17 applications from four different benchmark suites. Our method identified suitable algorithm structure patterns in the sequential applications. We confirmed our results by comparing them with the existing parallel versions of these applications. We also implemented the patterns we detected in cases in which parallel implementations were not available and achieved speedups of up to 14x.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Top 10%
Top 10%
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