Predicated array data-flow analysis for run-time parallelization

Moon, Sungdo; Hall, Mary; Murphy, Brian R.

doi:10.1145/277830.277874

“…Predicated dataflow analysis [22] introduced the idea of using propositional logic predicates over runtime values to derive so-called optimistic dataflow values guarded by predicates. Such analyses are capable of producing multiple analysis versions and keeping them distinct during analysis much like our A3 and A4 analyses.…”

Section: Related Workmentioning

confidence: 99%

Intraprocedural Dataflow Analysis for Software Product Lines

Brabrand¹,

Ribeiro²,

Tolêdo³

et al. 2013

Lecture Notes in Computer Science

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Software product lines (SPLs) are commonly developed using annotative approaches such as conditional compilation that come with an inherent risk of constructing erroneous products. For this reason, it is essential to be able to analyze SPLs. However, as dataflow analysis techniques are not able to deal with SPLs, developers must generate and analyze all valid methods individually, which is expensive for non-trivial SPLs. In this paper, we demonstrate how to take any standard intraprocedural dataflow analysis and automatically turn it into a feature-sensitive dataflow analysis in three different ways. All are capable of analyzing all valid methods of an SPL without having to generate all of them explicitly. We have implemented all analyses as extensions of SOOT's intraprocedural dataflow analysis framework and experimentally evaluated their performance and memory characteristics on four qualitatively different SPLs. The results indicate that the feature-sensitive analyses are on average 5.6 times faster than the brute force approach on our SPLs, and that they have different time and space tradeoffs.

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“…Earlier, disabling infeasible dead statements has been exploited to improve the precision of constant propagation [29] by essentially running a deadcode analysis capable of tagging statements as executable or non-executable during constant propagation analysis. Predicated dataflow analysis [22] introduced the idea of using propositional logic predicates over runtime values to derive so-called optimistic dataflow values guarded by predicates. Such analyses are capable of producing multiple analysis versions and keeping them distinct during analysis much like our A3 and A4 analyses.…”

Section: Related Workmentioning

confidence: 99%

Intraprocedural dataflow analysis for software product lines

Brabrand

¹

,

Ribeiro

²

,

Tolêdo

³

et al. 2012

Proceedings of the 11th Annual International Conference on Aspect-Oriented Software Development

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Software product lines (SPLs) are commonly developed using annotative approaches such as conditional compilation that come with an inherent risk of constructing erroneous products. For this reason, it is essential to be able to analyze SPLs. However, as dataflow analysis techniques are not able to deal with SPLs, developers must generate and analyze all valid methods individually, which is expensive for non-trivial SPLs. In this paper, we demonstrate how to take any standard intraprocedural dataflow analysis and automatically turn it into a feature-sensitive dataflow analysis in three different ways. All are capable of analyzing all valid methods of an SPL without having to generate all of them explicitly. We have implemented all analyses as extensions of SOOT's intraprocedural dataflow analysis framework and experimentally evaluated their performance and memory characteristics on four qualitatively different SPLs. The results indicate that the feature-sensitive analyses are on average 5.6 times faster than the brute force approach on our SPLs, and that they have different time and space tradeoffs.

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“…These predicates are returned to the programmer for evaluation (for interactive compilation). Further research [6,7,5,2,13] showed how to extract simple scalar conditions from relatively simple array data dependence predicates for a limited number of cases.…”

Section: Automatic Parallelization -Current State Of the Artmentioning

confidence: 99%

Implementation of Sensitivity Analysis for Automatic Parallelization

Rus

¹

,

Pennings

²

,

Rauchwerger

³

2008

Languages and Compilers for Parallel Computing

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Abstract. Sensitivity Analysis (SA) is a novel compiler technique that complements, and integrates with, static automatic parallelization analysis for the cases when program behavior is input sensitive. SA can extract all the input dependent, statically unavailable, conditions for which loops can be dynamically parallelized. SA generates a sequence of sufficient conditions which, when evaluated dynamically in order of their complexity, can each validate the dynamic parallel execution of the corresponding loop. While SA's principles are fairly simple, implementing it in a real compiler and obtaining good experimental results on benchmark codes is a difficult task. In this paper we present some of the most important implementation issues that we had to overcome in order to achieve a fairly successful automatic parallelizer. We present techniques related to validating dependence removing transformations, e.g., privatization or pushback parallelization, and static and dynamic evaluation of complex conditions for loop parallelization. We concern ourselves with multi-version and parallel code generation as well as the use of speculative parallelization when other, less costly options fail. We present a summary table of the contributions of our techniques to the successful parallelization of 22 industry benchmark codes. We also report speedups and parallel coverage of these codes on two multicore based systems and compare them to results obtained by the Ifort compiler.

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Predicated array data-flow analysis for run-time parallelization

Cited by 24 publications

References 12 publications

Intraprocedural Dataflow Analysis for Software Product Lines

Intraprocedural Dataflow Analysis for Software Product Lines

Intraprocedural dataflow analysis for software product lines

Implementation of Sensitivity Analysis for Automatic Parallelization

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