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Pattern-driven Design of a Multiparadigm Parallel Programming Framework

Authors: Niculescu, Virginia; Loulergue, Frédéric; Bufnea, Darius; Sterca, Adrian;

Pattern-driven Design of a Multiparadigm Parallel Programming Framework

Abstract

Parallel programming is more complex than sequential programming. It is therefore more difficult to achieve the same software quality in a parallel context. High-level parallel programming approaches are intermediate approaches where users are offered simplified APIs. There is a trade-off between expressivity and programming productivity, while still offering good performance. By being less error-prone, high-level approaches can improve application quality. From the API user point of view, such approaches should provide ease of programming without hindering performance. From the API implementor point of view, such approaches should be portable across parallel paradigms and extensible. JPLF is a framework for the Java language based on the theory of Powerlists, which are parallel recursive data structures. It is a high-level parallel programming approach that possesses the qualities mentioned above. This paper reflects on the design of JPLF: it explains the design choices and highlights the design patterns and design principles applied to build JPLF.

Keywords

[INFO.INFO-SE] Computer Science [cs]/Software Engineering [cs.SE], [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-PL] Computer Science [cs]/Programming Languages [cs.PL]

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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!
2
Average
Average
Average
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