{"title":"Parallel placement on reduced array architecture","authors":"C. Ravikumar, S. Sastry","doi":"10.1109/DAC.1988.14746","DOIUrl":null,"url":null,"abstract":"The authors present a hardware accelerator for a module placement algorithm based on the divide-and-conquer paradigm. They consider a partitioning algorithm for the approximate solution of a large placement problem. This algorithm divides the set of logic modules into small clusters and generates an optimal placement for each cluster. Finally, in a pasting step, the algorithm combines the optimal solutions for the smaller problems into a near-optimal solution for the original placement problem. The algorithm lends itself very naturally to a parallel realization, and maps nicely onto an SIMD (single-instruction, multiple data-stream) organization. Considerations such as cost-effectiveness and suitability to VLSI implementation led to the selection of the reduced array architecture as the target architecture for the placement accelerator.<<ETX>>","PeriodicalId":230716,"journal":{"name":"25th ACM/IEEE, Design Automation Conference.Proceedings 1988.","volume":"103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"25th ACM/IEEE, Design Automation Conference.Proceedings 1988.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DAC.1988.14746","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
The authors present a hardware accelerator for a module placement algorithm based on the divide-and-conquer paradigm. They consider a partitioning algorithm for the approximate solution of a large placement problem. This algorithm divides the set of logic modules into small clusters and generates an optimal placement for each cluster. Finally, in a pasting step, the algorithm combines the optimal solutions for the smaller problems into a near-optimal solution for the original placement problem. The algorithm lends itself very naturally to a parallel realization, and maps nicely onto an SIMD (single-instruction, multiple data-stream) organization. Considerations such as cost-effectiveness and suitability to VLSI implementation led to the selection of the reduced array architecture as the target architecture for the placement accelerator.<>