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DC poleHodnotaJazyk
dc.contributor.authorvan Wagensveld, Remko
dc.contributor.authorMargull, Ulrich
dc.contributor.editorPinker, Jiří
dc.date.accessioned2019-10-17T05:30:31Z
dc.date.available2019-10-17T05:30:31Z
dc.date.issued2017
dc.identifier.citation2017 International Conference on Applied Electronics: Pilsen, 5th – 6th September 2017, Czech Republic, p.257-262.en
dc.identifier.isbn978–80–261–0641–8 (Print)
dc.identifier.isbn978–80–261–0642–5 (Online)
dc.identifier.issn1803–7232 (Print)
dc.identifier.issn1805–9597 (Online)
dc.identifier.urihttp://hdl.handle.net/11025/35449
dc.format6 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherZápadočeská univerzita v Plznics
dc.rights© Západočeská univerzita v Plznics
dc.subjectjazyk C++cs
dc.subjectsystémy v reálném časecs
dc.subjectparalelní zpracovánícs
dc.subjectsouběžné výpočtycs
dc.subjectstandardycs
dc.subjectvícejádrové zpracovánícs
dc.titleExperiences with HPX on embedded real-time systemsen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedRecently more and more embedded devices use multi-core processors. For example, the current generation of high-end engine-control units exhibit triple-core processors. To reliably exploit the parallelism of these cores, an advanced programming environment is needed, such as the current C++17 Standard, as well as the upcoming C++20 Standard. Using C++ to cooperatively parallelize software is comprehensively investigated, but not in the context of embedded multi-core devices with real-time requirements. For this paper we used two algorithms from Continental AG's powertrain which are characteristic for real-time embedded devices and examined the effect of parallelizing them with C++17/20, represented by HPX as a C++17/20 runtime implementation. Different data sizes were used to increase the execution times of the parallel sections. According to Gustafson's Law, with these increased data sizes, the benefit of parallelization increases and greater speed-ups are possible. When keeping Continental AG's original data sizes, HPX is not able to reduce the execution time of the algorithms.en
dc.subject.translatedC++ languagesen
dc.subject.translatedreal-time systemsen
dc.subject.translatedparallel processingen
dc.subject.translatedconcurrent computingen
dc.subject.translatedstandardsen
dc.subject.translatedmulticore processingen
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:Applied Electronics 2017
Applied Electronics 2017

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