{"title":"近似计算:用硬件软件协同设计解锁效率","authors":"L. Ceze, Adrian Sampson","doi":"10.1145/3036699.3036703","DOIUrl":null,"url":null,"abstract":"Generations of computer scientists and practitioners have worked under the assumption that computers will keep improving themselves: just wait a few years and Moore's Law will solve your scaling problems. This reliable march of electrical-engineering progress has sparked revolutions in the ways humans use computers and interact with the world and each other. But growth in computing power has protected outdated abstractions and encouraged layering even more abstractions, whatever the cost.","PeriodicalId":213775,"journal":{"name":"GetMobile Mob. Comput. Commun.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"APPROXIMATE COMPUTING: Unlocking Efficiency with Hardware-Software Co-Design\",\"authors\":\"L. Ceze, Adrian Sampson\",\"doi\":\"10.1145/3036699.3036703\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Generations of computer scientists and practitioners have worked under the assumption that computers will keep improving themselves: just wait a few years and Moore's Law will solve your scaling problems. This reliable march of electrical-engineering progress has sparked revolutions in the ways humans use computers and interact with the world and each other. But growth in computing power has protected outdated abstractions and encouraged layering even more abstractions, whatever the cost.\",\"PeriodicalId\":213775,\"journal\":{\"name\":\"GetMobile Mob. Comput. Commun.\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-01-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"GetMobile Mob. Comput. Commun.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3036699.3036703\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"GetMobile Mob. Comput. Commun.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3036699.3036703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
APPROXIMATE COMPUTING: Unlocking Efficiency with Hardware-Software Co-Design
Generations of computer scientists and practitioners have worked under the assumption that computers will keep improving themselves: just wait a few years and Moore's Law will solve your scaling problems. This reliable march of electrical-engineering progress has sparked revolutions in the ways humans use computers and interact with the world and each other. But growth in computing power has protected outdated abstractions and encouraged layering even more abstractions, whatever the cost.