{"title":"遗传算法与指令调度","authors":"S. Beaty","doi":"10.1145/123465.123507","DOIUrl":null,"url":null,"abstract":"Many difficulties are encountered when developing an instruction scheduler to produce efficacious code for multiple architectures. Heuristic-based methods were found to produce disappointing results; indeed the goals of validity and length compete. This lead to the introduction of another method to search the solution space of valid schedules: genetic algorithms. Their application to this domain proved fruitful.","PeriodicalId":118572,"journal":{"name":"MICRO 24","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"41","resultStr":"{\"title\":\"Genetic algorithms and instruction scheduling\",\"authors\":\"S. Beaty\",\"doi\":\"10.1145/123465.123507\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many difficulties are encountered when developing an instruction scheduler to produce efficacious code for multiple architectures. Heuristic-based methods were found to produce disappointing results; indeed the goals of validity and length compete. This lead to the introduction of another method to search the solution space of valid schedules: genetic algorithms. Their application to this domain proved fruitful.\",\"PeriodicalId\":118572,\"journal\":{\"name\":\"MICRO 24\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"41\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MICRO 24\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/123465.123507\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MICRO 24","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/123465.123507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Many difficulties are encountered when developing an instruction scheduler to produce efficacious code for multiple architectures. Heuristic-based methods were found to produce disappointing results; indeed the goals of validity and length compete. This lead to the introduction of another method to search the solution space of valid schedules: genetic algorithms. Their application to this domain proved fruitful.