Eaft: Evolutionary Algorithms for Gcc Flag Tuning
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Date
2022
Authors
Çakar, Tuna
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Open Access Color
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
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.
Description
ORCID
Keywords
Particle swarm algorithm, Optimization, Genetic algorithm, Compiler optimization, Compiler flags, Autotuning, Optimization, Particle Swarm Algorithm, Genetic algorithm, Autotuning, Compiler optimization, Compiler flags
Turkish CoHE Thesis Center URL
Fields of Science
0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
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
WoS Q
N/A
Scopus Q
N/A

OpenCitations Citation Count
N/A
Source
2022 7th International Conference on Computer Science and Engineering (UBMK)
Volume
Issue
Start Page
444 - 449
End Page
449
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Citations
Scopus : 0


