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- W4312856512 abstract "Parallel computing takes advantage of modern processors to speed up software performances. However, it is arduous for developers to use parallelism in a large legacy application. One of the main difficulties consists in finding shared data to guard access to them. This paper proposes an innovative Java library that provides an API assisting developers to easily find data shared among methods. According to this, a classification approach for methods is proposed, which considers both data dependence and control dependence (in terms of call graph). Thanks to the provided API, developers can easily acquire knowledge on a system of classes, and then check whether parallelization is trivial, possible, or difficult, for some methods, once the shared variables have been revealed. The developed library has been put into use to analyse several open source projects, showing that the proposed classification is effective in real industrial systems." @default.
- W4312856512 created "2023-01-05" @default.
- W4312856512 creator A5011707033 @default.
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- W4312856512 date "2022-07-29" @default.
- W4312856512 modified "2023-10-16" @default.
- W4312856512 title "An API for Analysing and Classifying Data Dependence in View of Parallelism" @default.
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- W4312856512 doi "https://doi.org/10.1145/3556223.3556232" @default.
- W4312856512 hasPublicationYear "2022" @default.
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