{"title":"Distributed processing network architecture for reconfigurable computing","authors":"F. M. Vallina, E. Oruklu, J. Saniie","doi":"10.1109/EIT.2005.1627046","DOIUrl":null,"url":null,"abstract":"This paper introduces a set of rules and guidelines for the implementation of a distributed processing network (DPN) as the basis for a dynamic reconfigurable architecture targeted at improving the performance of microprocessor (muP) based systems in computationally intensive application domains. In order to provide the computation gains needed to improve upon the performance of the muP, the DPN architecture offers: 1) A low reconfiguration overhead, 2) A simple control interface, 3) Dynamic resource allocation, 4) Concurrent execution with dynamic reconfiguration, 5) Lower power dissipation than a muP executing the same computation kernel and, 6) Scalability to tackle tasks of varying resource requirements. DPN is currently targeted at realtime computationally intensive application domains such as compression, and signal transformations","PeriodicalId":358002,"journal":{"name":"2005 IEEE International Conference on Electro Information Technology","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 IEEE International Conference on Electro Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIT.2005.1627046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper introduces a set of rules and guidelines for the implementation of a distributed processing network (DPN) as the basis for a dynamic reconfigurable architecture targeted at improving the performance of microprocessor (muP) based systems in computationally intensive application domains. In order to provide the computation gains needed to improve upon the performance of the muP, the DPN architecture offers: 1) A low reconfiguration overhead, 2) A simple control interface, 3) Dynamic resource allocation, 4) Concurrent execution with dynamic reconfiguration, 5) Lower power dissipation than a muP executing the same computation kernel and, 6) Scalability to tackle tasks of varying resource requirements. DPN is currently targeted at realtime computationally intensive application domains such as compression, and signal transformations