Michael Pehl, Tobias Massier, H. Graeb, Ulf Schlichtmann
{"title":"具有非均匀离散参数的模拟电路尺寸的随机和伪梯度方法","authors":"Michael Pehl, Tobias Massier, H. Graeb, Ulf Schlichtmann","doi":"10.1109/ICCD.2008.4751860","DOIUrl":null,"url":null,"abstract":"Many methods for analog circuit sizing are available as commercial, in-house and academic tools. They are based on continuous optimization, e.g., of transistor geometries, although the subsequent layout step requires values on a pre-defined grid. In addition, sizing of transistors for bipolar and RF circuits frequently necessitates the use of multiples of predefined values for the design parameters. This paper presents a novel method for solving this type of discrete optimization problem. An iterative approach is presented, which is based on pseudo-gradients and a randomized calculation of search regions and steps. Experimental comparisons with simulated annealing and a continuous sizing approach with subsequent discretization clearly show the effectivity and efficiency of the presented method.","PeriodicalId":345501,"journal":{"name":"2008 IEEE International Conference on Computer Design","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A random and pseudo-gradient approach for analog circuit sizing with non-uniformly discretized parameters\",\"authors\":\"Michael Pehl, Tobias Massier, H. Graeb, Ulf Schlichtmann\",\"doi\":\"10.1109/ICCD.2008.4751860\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many methods for analog circuit sizing are available as commercial, in-house and academic tools. They are based on continuous optimization, e.g., of transistor geometries, although the subsequent layout step requires values on a pre-defined grid. In addition, sizing of transistors for bipolar and RF circuits frequently necessitates the use of multiples of predefined values for the design parameters. This paper presents a novel method for solving this type of discrete optimization problem. An iterative approach is presented, which is based on pseudo-gradients and a randomized calculation of search regions and steps. Experimental comparisons with simulated annealing and a continuous sizing approach with subsequent discretization clearly show the effectivity and efficiency of the presented method.\",\"PeriodicalId\":345501,\"journal\":{\"name\":\"2008 IEEE International Conference on Computer Design\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Conference on Computer Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCD.2008.4751860\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Computer Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCD.2008.4751860","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A random and pseudo-gradient approach for analog circuit sizing with non-uniformly discretized parameters
Many methods for analog circuit sizing are available as commercial, in-house and academic tools. They are based on continuous optimization, e.g., of transistor geometries, although the subsequent layout step requires values on a pre-defined grid. In addition, sizing of transistors for bipolar and RF circuits frequently necessitates the use of multiples of predefined values for the design parameters. This paper presents a novel method for solving this type of discrete optimization problem. An iterative approach is presented, which is based on pseudo-gradients and a randomized calculation of search regions and steps. Experimental comparisons with simulated annealing and a continuous sizing approach with subsequent discretization clearly show the effectivity and efficiency of the presented method.