Ranking programming languages by energy efficiency

Detalhes bibliográficos
Autor(a) principal: Pereira, Rui Alexandre Afonso
Data de Publicação: 2020
Outros Autores: Couto, Marco, Ribeiro, Francisco José Torres, Rua, Rui António Ramada, Cunha, Jácome, Fernandes, João Paulo Sousa Ferreira, Saraiva, João
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/1822/69044
Resumo: This paper compares a large set of programming languages regarding their efficiency, including from an energetic point-of-view. Indeed, we seek to establish and analyze different rankings for programming languages based on their energy efficiency. The goal of being able to rank languages with energy in mind is a recent one, and certainly deserves further studies. We have taken 19 solutions to well defined programming problems, expressed in (up to) 27 programming languages, from well know repositories such as the Computer Language Benchmark Game and Rosetta Code. We have also built a framework to automatically, and systematically, run, measure and compare the efficiency of such solutions. Ultimately, it is based on such comparison that we propose a serious of efficiency rankings, based on multiple criteria. Our results show interesting findings, such as, slower/faster languages consuming less/more energy, and how memory usage influences energy consumption. We also show how to use our results to provide software engineers support to decide which language to use when energy efficiency is a concern
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spelling Ranking programming languages by energy efficiencyEnergy efficiencyProgramming LanguagesLanguage BenchmarkingGreen SoftwareCiências Naturais::Ciências da Computação e da InformaçãoThis paper compares a large set of programming languages regarding their efficiency, including from an energetic point-of-view. Indeed, we seek to establish and analyze different rankings for programming languages based on their energy efficiency. The goal of being able to rank languages with energy in mind is a recent one, and certainly deserves further studies. We have taken 19 solutions to well defined programming problems, expressed in (up to) 27 programming languages, from well know repositories such as the Computer Language Benchmark Game and Rosetta Code. We have also built a framework to automatically, and systematically, run, measure and compare the efficiency of such solutions. Ultimately, it is based on such comparison that we propose a serious of efficiency rankings, based on multiple criteria. Our results show interesting findings, such as, slower/faster languages consuming less/more energy, and how memory usage influences energy consumption. We also show how to use our results to provide software engineers support to decide which language to use when energy efficiency is a concern(University of Porto) for the help that he provided. This work is financed by the ERDF – European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme within project POCI-01-0145-FEDER-006961, and by National Funds through the Portuguese funding agency, FCT - Funda¸c˜ao para a Ciˆencia e a Tecnologia within project POCI-01-0145-FEDER-016718 and UID/EEA/50014/2013. The first and second authors are also sponsored by FCT grants SFRH/BD/112733/2015 and SFRH/BD/132485/2017ElsevierUniversidade do MinhoPereira, Rui Alexandre AfonsoCouto, MarcoRibeiro, Francisco José TorresRua, Rui António RamadaCunha, JácomeFernandes, João Paulo Sousa FerreiraSaraiva, João2020-122020-12-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/69044eng0167-6423info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:16:58Zoai:repositorium.sdum.uminho.pt:1822/69044Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:09:31.102339Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Ranking programming languages by energy efficiency
title Ranking programming languages by energy efficiency
spellingShingle Ranking programming languages by energy efficiency
Pereira, Rui Alexandre Afonso
Energy efficiency
Programming Languages
Language Benchmarking
Green Software
Ciências Naturais::Ciências da Computação e da Informação
title_short Ranking programming languages by energy efficiency
title_full Ranking programming languages by energy efficiency
title_fullStr Ranking programming languages by energy efficiency
title_full_unstemmed Ranking programming languages by energy efficiency
title_sort Ranking programming languages by energy efficiency
author Pereira, Rui Alexandre Afonso
author_facet Pereira, Rui Alexandre Afonso
Couto, Marco
Ribeiro, Francisco José Torres
Rua, Rui António Ramada
Cunha, Jácome
Fernandes, João Paulo Sousa Ferreira
Saraiva, João
author_role author
author2 Couto, Marco
Ribeiro, Francisco José Torres
Rua, Rui António Ramada
Cunha, Jácome
Fernandes, João Paulo Sousa Ferreira
Saraiva, João
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Pereira, Rui Alexandre Afonso
Couto, Marco
Ribeiro, Francisco José Torres
Rua, Rui António Ramada
Cunha, Jácome
Fernandes, João Paulo Sousa Ferreira
Saraiva, João
dc.subject.por.fl_str_mv Energy efficiency
Programming Languages
Language Benchmarking
Green Software
Ciências Naturais::Ciências da Computação e da Informação
topic Energy efficiency
Programming Languages
Language Benchmarking
Green Software
Ciências Naturais::Ciências da Computação e da Informação
description This paper compares a large set of programming languages regarding their efficiency, including from an energetic point-of-view. Indeed, we seek to establish and analyze different rankings for programming languages based on their energy efficiency. The goal of being able to rank languages with energy in mind is a recent one, and certainly deserves further studies. We have taken 19 solutions to well defined programming problems, expressed in (up to) 27 programming languages, from well know repositories such as the Computer Language Benchmark Game and Rosetta Code. We have also built a framework to automatically, and systematically, run, measure and compare the efficiency of such solutions. Ultimately, it is based on such comparison that we propose a serious of efficiency rankings, based on multiple criteria. Our results show interesting findings, such as, slower/faster languages consuming less/more energy, and how memory usage influences energy consumption. We also show how to use our results to provide software engineers support to decide which language to use when energy efficiency is a concern
publishDate 2020
dc.date.none.fl_str_mv 2020-12
2020-12-01T00:00:00Z
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url https://hdl.handle.net/1822/69044
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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