{"title":"评估并行算法","authors":"Yu. M. Baskakov, I. Golubev","doi":"10.1109/SCM.2015.7190460","DOIUrl":null,"url":null,"abstract":"Various existing performance metrics within the parallel systems domain are analyzed. These include the different flavors of speedup, efficiency, and isoefficiency. Execution time still remains the most widely used metric. A new method to automatically estimate algorithmic cost is provided.","PeriodicalId":106868,"journal":{"name":"2015 XVIII International Conference on Soft Computing and Measurements (SCM)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessing parallel algorithms\",\"authors\":\"Yu. M. Baskakov, I. Golubev\",\"doi\":\"10.1109/SCM.2015.7190460\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Various existing performance metrics within the parallel systems domain are analyzed. These include the different flavors of speedup, efficiency, and isoefficiency. Execution time still remains the most widely used metric. A new method to automatically estimate algorithmic cost is provided.\",\"PeriodicalId\":106868,\"journal\":{\"name\":\"2015 XVIII International Conference on Soft Computing and Measurements (SCM)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 XVIII International Conference on Soft Computing and Measurements (SCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCM.2015.7190460\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 XVIII International Conference on Soft Computing and Measurements (SCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCM.2015.7190460","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Various existing performance metrics within the parallel systems domain are analyzed. These include the different flavors of speedup, efficiency, and isoefficiency. Execution time still remains the most widely used metric. A new method to automatically estimate algorithmic cost is provided.
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