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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