{"title":"Random projection: a new approach to VLSI layout","authors":"S. Vempala","doi":"10.1109/SFCS.1998.743489","DOIUrl":null,"url":null,"abstract":"We show that random projection, the technique of projecting a set of points to a randomly chosen low-dimensional subspace, can be used to solve problems in VLSI layout. Specifically, for the problem of laying out a graph on a 2-dimensional grid so as to minimize the maximum edge length, we obtain an O(log/sup 3.5/ n) approximation algorithm (this is the first o(n) approximation), and for the bicriteria problem of minimizing the total edge length while keeping the maximum length bounded, we obtain an O(log/sup 3/ n, log/sup 3.5/ n) approximation. Our algorithms also work for d-dimensional versions of these problems (for any fixed d) with polylog approximation guarantees. Besides random projection, the main components of the algorithms are a linear programming relaxation, and volume-respecting Euclidean embeddings.","PeriodicalId":228145,"journal":{"name":"Proceedings 39th Annual Symposium on Foundations of Computer Science (Cat. No.98CB36280)","volume":"372 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"47","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 39th Annual Symposium on Foundations of Computer Science (Cat. No.98CB36280)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SFCS.1998.743489","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 47
Abstract
We show that random projection, the technique of projecting a set of points to a randomly chosen low-dimensional subspace, can be used to solve problems in VLSI layout. Specifically, for the problem of laying out a graph on a 2-dimensional grid so as to minimize the maximum edge length, we obtain an O(log/sup 3.5/ n) approximation algorithm (this is the first o(n) approximation), and for the bicriteria problem of minimizing the total edge length while keeping the maximum length bounded, we obtain an O(log/sup 3/ n, log/sup 3.5/ n) approximation. Our algorithms also work for d-dimensional versions of these problems (for any fixed d) with polylog approximation guarantees. Besides random projection, the main components of the algorithms are a linear programming relaxation, and volume-respecting Euclidean embeddings.