HIPS 2020, 25th International Workshop on High-Level Parallel Programming Models and Supportive Environments, held in Conjunction With 34th IEEE International Parallel and Distributed Processing Symposium, published in Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 375-384, DOI: 10.1109/IPDPSW50202.2020.00072, 18-22 May, 2020, New Orleans, LA, USA.
Cite as
1 |
V. Niculescu, D. Bufnea and A. Sterca, "Enhancing Java Streams API with PowerList Computation", 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2020, pp. 375-384, doi: 10.1109/IPDPSW50202.2020.00072 |
Full paper
Enhancing Java Streams API with PowerList Computation
Authors
Virginia Niculescu*, Darius Bufnea*, Adrian Sterca*
* Department of Computer Science, Faculty of Mathematics and Computer Science, Babeș-Bolyai University of Cluj-Napoca, Romania
Copyright
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Abstract
Since they were introduced, Java streams were very fast embraced by the industry, being currently used at a large scale. The parallelism enabled by them is very easy to achieve, but it is constrained either by the used parallelism model (in some cases), or by the set of operations that could be specified using streams. We investigate in this paper the possibility to enhance the computation types that could be defined using the Java streams API by introducing into this infrastructure the PowerList theory based computation. Powerlists are recursive data structures that together with their associated algebraic theory offer both abstractions in order to ease the development of parallel applications, and also a methodology to design parallel algorithms. The Java streaming infrastructure could be adapted to support them in a great measure. We present here such an adaptation, and we analyse and discuss the advantages and constraints. This analysis is exemplified by application examples.
Key words
parallel programming; streams; recursive structures; Java; performance; models.
BibTeX bib file
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@INPROCEEDINGS{niculescu2020b, author={Virginia {Niculescu} and Darius {Bufnea} and Adrian {Sterca}}, booktitle={2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)}, title={Enhancing Java Streams API with PowerList Computation}, year={2020}, volume={}, number={}, pages={375-384}, } |
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