{"title":"A uniform optimization technique for offset assignment problems","authors":"R. Leupers, Fabian David","doi":"10.1109/ISSS.1998.730589","DOIUrl":null,"url":null,"abstract":"A number of different algorithms for optimized offset assignment in DSP code generation have been developed recently. These algorithms aim at constructing a layout of local variables in memory, such that the addresses of variables can be computed efficiently in most cases. This is achieved by maximizing the use of auto-increment operations on address registers. However, the algorithms published in previous work only consider special cases of offset assignment problems, characterized by fixed parameters such as register file sizes and auto-increment ranges. In contrast, this paper presents a genetic optimization technique capable of simultaneously handling arbitrary register file sizes and auto-increment ranges. Moreover, this technique is the first that integrates the allocation of modify registers into offset assignment. Experimental evaluation indicates a significant improvement in the quality of constructed offset assignments, as compared to previous work.","PeriodicalId":305333,"journal":{"name":"Proceedings. 11th International Symposium on System Synthesis (Cat. No.98EX210)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"81","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 11th International Symposium on System Synthesis (Cat. No.98EX210)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSS.1998.730589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 81
Abstract
A number of different algorithms for optimized offset assignment in DSP code generation have been developed recently. These algorithms aim at constructing a layout of local variables in memory, such that the addresses of variables can be computed efficiently in most cases. This is achieved by maximizing the use of auto-increment operations on address registers. However, the algorithms published in previous work only consider special cases of offset assignment problems, characterized by fixed parameters such as register file sizes and auto-increment ranges. In contrast, this paper presents a genetic optimization technique capable of simultaneously handling arbitrary register file sizes and auto-increment ranges. Moreover, this technique is the first that integrates the allocation of modify registers into offset assignment. Experimental evaluation indicates a significant improvement in the quality of constructed offset assignments, as compared to previous work.