Multi-way Divide and Conquer Parallel Programming based on PLists

Niculescu, Virginia; Bufnea, Darius; Sterca, Adrian; Silimon, Robert

doi:10.23919/softcom.2019.8903794

Cited by 2 publications

(3 citation statements)

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“…The first argument is a list of arities: PosList, and the second is the PList argument (if there is more than one PList argument they all must have the same length). Functions over PList are only defined for certain pairs of these input values; to express the valid pairs, it is required that the specification of the function defines the following predicate: def ined : ((P osList × P List) → X) × P osList × P List → Bool (4) to characterize where the function is defined.…”

Section: Plist Data Structuresmentioning

confidence: 99%

“…Due to its flexible design, other execution models can be added to the framework. This paper is an extended version of our work [4] which presents an extension of the JPLF framework by adding PLists support. PLists are a generalization of PowerLists introduced by J.…”

Section: Introductionmentioning

confidence: 99%

“…The current paper emphasizes the applicability of the framework to a larger set of parallel solvable problems through different data division strategies. We outline and review the JPLF extension from [4], define and add another application example of the extension (i.e. Fast Fourier Transform) and we specify new implementation details for achieving bounded parallelism in the JPLF PList extension.…”

Section: Introductionmentioning

confidence: 99%

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PList-based Divide and Conquer Parallel Programming

Niculescu

Bufnea

Sterca

2020

J. commun. softw. syst. (Online)

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This paper details an extension of a Java parallel programming framework – JPLF. The JPLF framework is a programming framework that helps programmers build parallel programs using existing building blocks. The framework is based on {\em PowerLists} and PList Theories and it naturally supports multi-way Divide and Conquer. By using this framework, the programmer is exempted from dealing with all the complexities of writing parallel programs from scratch. This extension to the JPLF framework adds PLists support to the framework and so, it enlarges the applicability of the framework to a larger set of parallel solvable problems. Using this extension, we may apply more flexible data division strategies. In addition, the length of the input lists no longer has to be a power of two – as required by the PowerLists theory. In this paper we unveil new applications that emphasize the new class of computations that can be executed within the JPLF framework. We also give a detailed description of the data structures and functions involved in the PLists extension of the JPLF, and extended performance experiments are described and analyzed.

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Section: Plist Data Structuresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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