{"title":"喜鹊对OLC和H3的遗传改良","authors":"W. Langdon, Bradley J. Alexander","doi":"10.1109/GI59320.2023.00011","DOIUrl":null,"url":null,"abstract":"Magpie (Machine Automated General Performance Improvement via Evolution of software) has been recently developed by Aymeric Blot from PyGGI 2.0. Like PyGGI, it claims to be able to optimise computer source code written in arbitrary programming languages. So far it has been demonstrated on benchmarks written in Python and C. Recently we have used hill climbing to customise two industrial open source programs: Google's Open Location Code OLC and Uber's Hexagonal Hierarchical Spatial Index H3 [W. B. Langdon et al., “Genetic improvement of LLVM intermediate representation”, in EuroGP 2023]. Magpie found much faster improvements (reducing instruction counts by up to 15% v. 2%) which generalise. Various glitches in Magpie are also reported.","PeriodicalId":414492,"journal":{"name":"2023 IEEE/ACM International Workshop on Genetic Improvement (GI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Genetic Improvement of OLC and H3 with Magpie\",\"authors\":\"W. Langdon, Bradley J. Alexander\",\"doi\":\"10.1109/GI59320.2023.00011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Magpie (Machine Automated General Performance Improvement via Evolution of software) has been recently developed by Aymeric Blot from PyGGI 2.0. Like PyGGI, it claims to be able to optimise computer source code written in arbitrary programming languages. So far it has been demonstrated on benchmarks written in Python and C. Recently we have used hill climbing to customise two industrial open source programs: Google's Open Location Code OLC and Uber's Hexagonal Hierarchical Spatial Index H3 [W. B. Langdon et al., “Genetic improvement of LLVM intermediate representation”, in EuroGP 2023]. Magpie found much faster improvements (reducing instruction counts by up to 15% v. 2%) which generalise. Various glitches in Magpie are also reported.\",\"PeriodicalId\":414492,\"journal\":{\"name\":\"2023 IEEE/ACM International Workshop on Genetic Improvement (GI)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE/ACM International Workshop on Genetic Improvement (GI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GI59320.2023.00011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE/ACM International Workshop on Genetic Improvement (GI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GI59320.2023.00011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Magpie (Machine Automated General Performance Improvement via Evolution of software) has been recently developed by Aymeric Blot from PyGGI 2.0. Like PyGGI, it claims to be able to optimise computer source code written in arbitrary programming languages. So far it has been demonstrated on benchmarks written in Python and C. Recently we have used hill climbing to customise two industrial open source programs: Google's Open Location Code OLC and Uber's Hexagonal Hierarchical Spatial Index H3 [W. B. Langdon et al., “Genetic improvement of LLVM intermediate representation”, in EuroGP 2023]. Magpie found much faster improvements (reducing instruction counts by up to 15% v. 2%) which generalise. Various glitches in Magpie are also reported.
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