{"title":"面向可重构片上系统设计的区域高效指令集综合","authors":"P. Brisk, A. Kaplan, M. Sarrafzadeh","doi":"10.1145/996566.996679","DOIUrl":null,"url":null,"abstract":"Silicon compilers are often used in conjunction with Field Programmable Gate Arrays (FPGAs) to deliver flexibility, fast prototyping, and accelerated time-to-market. Many of these compilers produce hardware that is larger than necessary, as they do not allow instructions to share hardware resources. This study presents an efficient heuristic which transforms a set of custom instructions into a single hardware datapath on which they can execute. Our approach is based on the classic problems of finding the longest common subsequence and substring of two (or more) sequences. This heuristic produces circuits which are as much as 85.33% smaller than those synthesized by integer linear programming (ILP) approaches which do not explore resource sharing. On average, we obtained 55.41% area reduction for pipelined datapaths, and 66.92% area reduction for VLIW datapaths. Our solution is simple and effective, and can easily be integrated into an existing silicon compiler.","PeriodicalId":115059,"journal":{"name":"Proceedings. 41st Design Automation Conference, 2004.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"103","resultStr":"{\"title\":\"Area-efficient instruction set synthesis for reconfigurable system-on-chip designs\",\"authors\":\"P. Brisk, A. Kaplan, M. Sarrafzadeh\",\"doi\":\"10.1145/996566.996679\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Silicon compilers are often used in conjunction with Field Programmable Gate Arrays (FPGAs) to deliver flexibility, fast prototyping, and accelerated time-to-market. Many of these compilers produce hardware that is larger than necessary, as they do not allow instructions to share hardware resources. This study presents an efficient heuristic which transforms a set of custom instructions into a single hardware datapath on which they can execute. Our approach is based on the classic problems of finding the longest common subsequence and substring of two (or more) sequences. This heuristic produces circuits which are as much as 85.33% smaller than those synthesized by integer linear programming (ILP) approaches which do not explore resource sharing. On average, we obtained 55.41% area reduction for pipelined datapaths, and 66.92% area reduction for VLIW datapaths. Our solution is simple and effective, and can easily be integrated into an existing silicon compiler.\",\"PeriodicalId\":115059,\"journal\":{\"name\":\"Proceedings. 41st Design Automation Conference, 2004.\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"103\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 41st Design Automation Conference, 2004.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/996566.996679\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 41st Design Automation Conference, 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/996566.996679","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Area-efficient instruction set synthesis for reconfigurable system-on-chip designs
Silicon compilers are often used in conjunction with Field Programmable Gate Arrays (FPGAs) to deliver flexibility, fast prototyping, and accelerated time-to-market. Many of these compilers produce hardware that is larger than necessary, as they do not allow instructions to share hardware resources. This study presents an efficient heuristic which transforms a set of custom instructions into a single hardware datapath on which they can execute. Our approach is based on the classic problems of finding the longest common subsequence and substring of two (or more) sequences. This heuristic produces circuits which are as much as 85.33% smaller than those synthesized by integer linear programming (ILP) approaches which do not explore resource sharing. On average, we obtained 55.41% area reduction for pipelined datapaths, and 66.92% area reduction for VLIW datapaths. Our solution is simple and effective, and can easily be integrated into an existing silicon compiler.