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Fork/Join Parallelism in the Wild: Documenting Patterns and Anti-Patterns in Java Programs using the Fork/Join Framework

De Wael, Mattias and Marr, Stefan and Van Cutsem, Tom (2014) Fork/Join Parallelism in the Wild: Documenting Patterns and Anti-Patterns in Java Programs using the Fork/Join Framework. In: Proceedings of the 2014 International Conference on Principles and Practices of Programming on the Java platform: Virtual machines, Languages, and Tools. PPPJ Principles and Practice of Programming in Java . ACM, New York, USA, pp. 39-50. ISBN 978-1-4503-2926-2. (doi:10.1145/2647508.2647511)

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Abstract

Now that multicore processors are commonplace, developing parallel software has escaped the confines of high-performance computing and enters the mainstream. The Fork/Join framework, for instance, is part of the standard Java platform since version 7. Fork/Join is a high-level parallel programming model advocated to make parallelizing recursive divide-and-conquer algorithms particularly easy. While, in theory, Fork/Join is a simple and effective technique to expose parallelism in applications, it has not been investigated before whether and how the technique is applied in practice. We therefore performed an empirical study on a corpus of 120 open source Java projects that use the framework for roughly 362 different tasks. On the one hand, we confirm the frequent use of four best-practice patterns (Sequential Cutoff, Linked Subtasks, Leaf Tasks, and avoiding unnecessary forking) in actual projects. On the other hand, we also discovered three recurring anti-patterns that potentially limit parallel performance: sub-optimal use of Java collections when splitting tasks into subtasks as well as when merging the results of subtasks, and finally the inappropriate sharing of resources between tasks. We document these anti-patterns and study their impact on performance.

Item Type: Book section
DOI/Identification number: 10.1145/2647508.2647511
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Sciences > School of Computing
Depositing User: Stefan Marr
Date Deposited: 08 Nov 2017 23:04 UTC
Last Modified: 23 Sep 2019 11:38 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/63829 (The current URI for this page, for reference purposes)
Marr, Stefan: https://orcid.org/0000-0001-9059-5180
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