Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11779/1907
Title: Eaft: Evolutionary Algorithms for Gcc Flag Tuning
Authors: Tagtekin, Burak
Çakar, Tuna
Keywords: Particle swarm algorithm
Optimization
Genetic algorithm
Compiler optimization
Compiler flags
Autotuning
Publisher: IEEE
Source: 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
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.
URI: https://hdl.handle.net/20.500.11779/1907
https://doi.org/10.1109/UBMK55850.2022.9919557
ISBN: 9781670000000
Appears in Collections:Bilgisayar Mühendisliği Bölümü Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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