{"title":"A reconfigurable data-driven ALU for Xputers","authors":"R. Hartenstein, R. Kress, H. Reinig","doi":"10.1109/FPGA.1994.315602","DOIUrl":null,"url":null,"abstract":"A reconfigurable data-driven datapath architecture for ALUs is presented which may be used for custom computing machines (CCMs), Xputers (a class of CCMs) and other adaptable computer systems as well as for rapid prototyping of high speed datapaths. Fine grained parallelism is achieved by using simple reconfigurable processing elements which are called datapath units (DPUs). The word-oriented datapath simplifies the mapping of applications onto the architecture. Pipelining is supported by the architecture. The programming environment allows automatic mapping of the operators from high level descriptions. Two implementations, one by FPGAs and one with standard cells are shown.<<ETX>>","PeriodicalId":138179,"journal":{"name":"Proceedings of IEEE Workshop on FPGA's for Custom Computing Machines","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of IEEE Workshop on FPGA's for Custom Computing Machines","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPGA.1994.315602","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26
Abstract
A reconfigurable data-driven datapath architecture for ALUs is presented which may be used for custom computing machines (CCMs), Xputers (a class of CCMs) and other adaptable computer systems as well as for rapid prototyping of high speed datapaths. Fine grained parallelism is achieved by using simple reconfigurable processing elements which are called datapath units (DPUs). The word-oriented datapath simplifies the mapping of applications onto the architecture. Pipelining is supported by the architecture. The programming environment allows automatic mapping of the operators from high level descriptions. Two implementations, one by FPGAs and one with standard cells are shown.<>