Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11779/1907
Full metadata record
DC FieldValueLanguage
dc.contributor.authorTagtekin, Burak-
dc.contributor.authorÇakar, Tuna-
dc.date.accessioned2023-03-06T06:53:16Z
dc.date.available2023-03-06T06:53:16Z
dc.date.issued2022-
dc.identifier.citationTagtekin, B., & Cakar, T. (2022). EAFT: Evolutionary Algorithms for GCC Flag Tuning. 2022 7th International Conference on Computer Science and Engineering (UBMK). https://doi.org/10.1109/ubmk55850.2022.9919557en_US
dc.identifier.isbn9781670000000-
dc.identifier.urihttps://hdl.handle.net/20.500.11779/1907-
dc.identifier.urihttps://doi.org/10.1109/UBMK55850.2022.9919557-
dc.description.abstractDue to limited resources, some methods come to the fore in finding and applying the factors that affect the working time of the code. The most common one is choosing the correct GCC flags using heuristic algorithms. For the codes compiled with GCC, the selection of optimization flags directly affects the speed of the processing, however, choosing the right one among hundreds of markers during this process is a resource consuming problem. This article explains how to solve the GCC flag optimization problem with EAFT. Rather than other autotuner tools such as Opentuner, EAFT is an optimized tool for GCC marker selection. Search infrastructure has been developed with particle swarm optimization and genetic algorithm with diffent submodels rather than using only Genetic Algorithm like FOGA. © 2022 IEEE.en_US
dc.language.isotren_US
dc.publisherIEEEen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAutotuningen_US
dc.subjectCompiler flagsen_US
dc.subjectCompiler optimizationen_US
dc.subjectGenetic algorithmen_US
dc.subjectOptimizationen_US
dc.subjectParticle Swarm Algorithmen_US
dc.titleEAFT: Evolutionary Algorithms for GCC Flag Tuningen_US
dc.typeConference Objecten_US
dc.identifier.doi10.1109/UBMK55850.2022.9919557-
dc.identifier.scopus2-s2.0-85141823745en_US
dc.authoridÇakar, Tuna / 0000-0001-8594-7399-
dc.relation.publicationcategoryKonferans Öğesi - Ulusal - Kurum Öğretim Elemanıen_US
dc.identifier.startpage444 - 449en_US
dc.departmentMühendislik Fakültesi, Bilgisayar Mühendisligi Bölümüen_US
dc.relation.journalProceedings - 7th International Conference on Computer Science and Engineering, Ubmk 2022en_US
dc.institutionauthorTagtekin, Burak, Çakar, Tuna-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextopen-
item.languageiso639-1tr-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.openairetypeConference Object-
crisitem.author.dept02.02. Department of Computer Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Files in This Item:
File Description SizeFormat 
EAFT_Evolutionary_Algorithms_for_GCC_Flag_Tuning.pdfFull Text - Article303.35 kBAdobe PDFThumbnail
View/Open
Show simple item record



CORE Recommender

Page view(s)

6
checked on Jun 26, 2024

Download(s)

2
checked on Jun 26, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.