{"title":"进化、熵和并行计算","authors":"K. Thearling","doi":"10.1109/PHYCMP.1994.363674","DOIUrl":null,"url":null,"abstract":"The relationship between evolution and entropy is described for a model of self-reproducing parallel computation. As was recently shown by Thearling and Ray (1994), the performance of some types of parallel computation can be increased though a process analogous to evolution by natural selection. The work discussed in this paper explores the process by which evolution manipulates the entropy of instruction sequences in a population of parallel programs in an effort to discover more efficient uses of parallelism.<<ETX>>","PeriodicalId":378733,"journal":{"name":"Proceedings Workshop on Physics and Computation. PhysComp '94","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Evolution, entropy, and parallel computation\",\"authors\":\"K. Thearling\",\"doi\":\"10.1109/PHYCMP.1994.363674\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The relationship between evolution and entropy is described for a model of self-reproducing parallel computation. As was recently shown by Thearling and Ray (1994), the performance of some types of parallel computation can be increased though a process analogous to evolution by natural selection. The work discussed in this paper explores the process by which evolution manipulates the entropy of instruction sequences in a population of parallel programs in an effort to discover more efficient uses of parallelism.<<ETX>>\",\"PeriodicalId\":378733,\"journal\":{\"name\":\"Proceedings Workshop on Physics and Computation. PhysComp '94\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Workshop on Physics and Computation. PhysComp '94\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PHYCMP.1994.363674\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Workshop on Physics and Computation. PhysComp '94","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PHYCMP.1994.363674","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The relationship between evolution and entropy is described for a model of self-reproducing parallel computation. As was recently shown by Thearling and Ray (1994), the performance of some types of parallel computation can be increased though a process analogous to evolution by natural selection. The work discussed in this paper explores the process by which evolution manipulates the entropy of instruction sequences in a population of parallel programs in an effort to discover more efficient uses of parallelism.<>
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