{"title":"关于信息流和排序:VLSI电路的新上下限","authors":"R. Cole, A. Siegel","doi":"10.1109/SFCS.1985.39","DOIUrl":null,"url":null,"abstract":"This work comprises two parts: lower bounds and upper bounds in VLSI circuits. The upper bounds are for the sorting problem: we describe a large number of constructions for sorting N numbers in the range [0,M] for the standard VLSI bit model. Among other results, we attain: • VLSI sorter constructions that are within a constant factor of optimal size for almost all number ranges M (including M = N), and running times T. • A fundamentally new merging network for sorting numbers in a bit model. • New organizational approaches for optimal tuning of merging networks and the proper management of data flow. The lower bounds apply to a variety of problems. We present two new techniques for establishing lower bounds on the information flow in VLSI circuits. They are: • An averaging technique, which is easy to apply to a variety of problems, including a long standing question regarding the AT2 complexity for sorting. • A technique for constructing fooling sets in instances where our averaging method is unlikely to provide an adequate bound.","PeriodicalId":296739,"journal":{"name":"26th Annual Symposium on Foundations of Computer Science (sfcs 1985)","volume":"88 8","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1985-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"On information flow and sorting : New upper and lower bounds for VLSI circuits\",\"authors\":\"R. Cole, A. Siegel\",\"doi\":\"10.1109/SFCS.1985.39\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work comprises two parts: lower bounds and upper bounds in VLSI circuits. The upper bounds are for the sorting problem: we describe a large number of constructions for sorting N numbers in the range [0,M] for the standard VLSI bit model. Among other results, we attain: • VLSI sorter constructions that are within a constant factor of optimal size for almost all number ranges M (including M = N), and running times T. • A fundamentally new merging network for sorting numbers in a bit model. • New organizational approaches for optimal tuning of merging networks and the proper management of data flow. The lower bounds apply to a variety of problems. We present two new techniques for establishing lower bounds on the information flow in VLSI circuits. They are: • An averaging technique, which is easy to apply to a variety of problems, including a long standing question regarding the AT2 complexity for sorting. • A technique for constructing fooling sets in instances where our averaging method is unlikely to provide an adequate bound.\",\"PeriodicalId\":296739,\"journal\":{\"name\":\"26th Annual Symposium on Foundations of Computer Science (sfcs 1985)\",\"volume\":\"88 8\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1985-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"26th Annual Symposium on Foundations of Computer Science (sfcs 1985)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SFCS.1985.39\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"26th Annual Symposium on Foundations of Computer Science (sfcs 1985)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SFCS.1985.39","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On information flow and sorting : New upper and lower bounds for VLSI circuits
This work comprises two parts: lower bounds and upper bounds in VLSI circuits. The upper bounds are for the sorting problem: we describe a large number of constructions for sorting N numbers in the range [0,M] for the standard VLSI bit model. Among other results, we attain: • VLSI sorter constructions that are within a constant factor of optimal size for almost all number ranges M (including M = N), and running times T. • A fundamentally new merging network for sorting numbers in a bit model. • New organizational approaches for optimal tuning of merging networks and the proper management of data flow. The lower bounds apply to a variety of problems. We present two new techniques for establishing lower bounds on the information flow in VLSI circuits. They are: • An averaging technique, which is easy to apply to a variety of problems, including a long standing question regarding the AT2 complexity for sorting. • A technique for constructing fooling sets in instances where our averaging method is unlikely to provide an adequate bound.