2015 Ieee 6th International Workshop On Program Comprehension Through Dynamic Analysis Pcoda
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Program Comprehension Through Dynamic Analysis Pcoda 2015 Ieee 6th International Workshop On
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Author :
language : en
Publisher:
Release Date : 2015
Program Comprehension Through Dynamic Analysis Pcoda 2015 Ieee 6th International Workshop On written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
2015 Ieee 6th International Workshop On Program Comprehension Through Dynamic Analysis Pcoda
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 2015
2015 Ieee 6th International Workshop On Program Comprehension Through Dynamic Analysis Pcoda written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computer programs categories.
2015 Ieee 6th International Workshop On Program Comprehension Through Dynamic Analysis Pcoda
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 2015
2015 Ieee 6th International Workshop On Program Comprehension Through Dynamic Analysis Pcoda written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computer programs categories.
Musterbasierte Parallelisierung Sequenzieller Anwendungen
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Author : Korbinian Molitorisz
language : de
Publisher: Springer-Verlag
Release Date : 2016-07-25
Musterbasierte Parallelisierung Sequenzieller Anwendungen written by Korbinian Molitorisz and has been published by Springer-Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-25 with Computers categories.
Diese Arbeit präsentiert AutoPar, ein neuartiges Verfahren zur Transformation bestehender Software, welches sequenzielle Ausgangsmuster bestimmt und in parallele Softwarearchitekturen umwandelt. Die Evaluierung belegt, dass AutoPar dieselbe Leistung erreicht wie erfahrene Entwickler. AutoPar benötigt dafür lediglich wenige Minuten statt mehrerer Tage intensiver Arbeit im manuellen Fall. Eine empirische Studie mit Softwareentwicklern zeigt darüber hinaus, dass AutoPar in kürzerer Zeit signifikant mehr Parallelisierungspotenzial zutage fördert als existierende Parallelisierungswerkzeuge.