Eaft: Evolutionary Algorithms for Gcc Flag Tuning

dc.contributor.author Tagtekin, Burak
dc.contributor.author Çakar, Tuna
dc.date.accessioned 2023-03-06T06:53:16Z
dc.date.available 2023-03-06T06:53:16Z
dc.date.issued 2022
dc.description.abstract Due 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.
dc.identifier.citation Tagtekin, 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/ubmk55850.2022.9919557
dc.identifier.doi 10.1109/UBMK55850.2022.9919557
dc.identifier.isbn 9781670000000
dc.identifier.scopus 2-s2.0-85141823745
dc.identifier.uri https://hdl.handle.net/20.500.11779/1907
dc.identifier.uri https://doi.org/10.1109/UBMK55850.2022.9919557
dc.language.iso tr
dc.publisher IEEE
dc.relation.ispartof 2022 7th International Conference on Computer Science and Engineering (UBMK)
dc.rights info:eu-repo/semantics/openAccess
dc.subject Particle swarm algorithm
dc.subject Optimization
dc.subject Genetic algorithm
dc.subject Compiler optimization
dc.subject Compiler flags
dc.subject Autotuning
dc.title Eaft: Evolutionary Algorithms for Gcc Flag Tuning
dc.type Conference Object
dspace.entity.type Publication
gdc.author.id Çakar, Tuna / 0000-0001-8594-7399
gdc.author.institutional Tagtekin, Burak, Çakar, Tuna
gdc.bip.impulseclass C5
gdc.bip.influenceclass C5
gdc.bip.popularityclass C5
gdc.coar.access open access
gdc.coar.type text::conference output
gdc.description.department Mühendislik Fakültesi, Bilgisayar Mühendisligi Bölümü
gdc.description.endpage 449
gdc.description.publicationcategory Konferans Öğesi - Ulusal - Kurum Öğretim Elemanı
gdc.description.scopusquality N/A
gdc.description.startpage 444 - 449
gdc.description.wosquality N/A
gdc.identifier.openalex W4308096248
gdc.index.type Scopus
gdc.oaire.diamondjournal false
gdc.oaire.impulse 0.0
gdc.oaire.influence 2.5942106E-9
gdc.oaire.isgreen true
gdc.oaire.keywords Optimization
gdc.oaire.keywords Particle Swarm Algorithm
gdc.oaire.keywords Genetic algorithm
gdc.oaire.keywords Autotuning
gdc.oaire.keywords Compiler optimization
gdc.oaire.keywords Compiler flags
gdc.oaire.popularity 2.19756E-9
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 02 engineering and technology
gdc.openalex.collaboration National
gdc.openalex.fwci 0.0
gdc.openalex.normalizedpercentile 0.15
gdc.opencitations.count 0
gdc.plumx.scopuscites 0
gdc.publishedmonth Eylül
gdc.relation.journal Proceedings - 7th International Conference on Computer Science and Engineering, Ubmk 2022
gdc.scopus.citedcount 0
gdc.virtual.author Çakar, Tuna
gdc.wos.publishedmonth Eylül
gdc.yokperiod YÖK - 2022-23
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relation.isAuthorOfPublication.latestForDiscovery 10f8ce3b-94c2-40f0-9381-0725723768fe
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