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A divide-and-conquer parallel pattern implementation for multicores

Authors: Marco Danelutto; Tiziano De Matteis; Gabriele Mencagli; Massimo Torquati;

A divide-and-conquer parallel pattern implementation for multicores

Abstract

Divide-and-Conquer (DaC) is a sequential programming paradigm which models a large class of algorithms used in real-life applications. Although suitable to extract paral- lelism in a straightforward way, the parallel implementation of DaC algorithms still requires some expertise in parallel programming tools by the programmer. In this paper we aim at providing to non-expert program- mers a high-level solution for fast prototyping parallel DaC programs on multicores with minimal programming effort. Following the rationale of parallel design pattern method- ology, we design a C++11-compliant template interface for developing parallel DaC programs. The interface is imple- mented using different back-end frameworks (i.e. OpenMP, Intel TBB and FastFlow) supporting source code reuse and a certain amount of performance portability. Experiments on a 24-core Intel server show the effective- ness of our approach: with a reduced programming effort the programmer easily prototypes parallel versions with perfor- mance comparable with hand-made parallelizations.

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Italy
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Keywords

Divide and conquer; High-level parallel patterns

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selected citations
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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).
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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!
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