{"title":"针对粗粒度可重构架构的高效代码压缩","authors":"Moo-Kyoung Chung, Yeon-Gon Cho, Soojung Ryu","doi":"10.1109/ICCD.2012.6378687","DOIUrl":null,"url":null,"abstract":"Though Coarse Grained Reconfigurable Architecture (CGRA) is a flexible alternative for high performance computing, it has a crucial problem on instruction code whose size is so large that the instruction memory takes a significant portion of silicon area and power consumption. This article proposes an efficient dictionary-based compression method for the CGRA instruction code, where code bit-fields are rearranged and grouped together according to locality characteristics and the most efficient compression mode is selected for each group and kernel. The proposed method can reinstall the dictionary contents adaptively for each kernel. Experimental results show that the proposed method achieved an average compression ratio 0.56 in 4×4 array of function units for well-optimized applications.","PeriodicalId":313428,"journal":{"name":"2012 IEEE 30th International Conference on Computer Design (ICCD)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Efficient code compression for coarse grained reconfigurable architectures\",\"authors\":\"Moo-Kyoung Chung, Yeon-Gon Cho, Soojung Ryu\",\"doi\":\"10.1109/ICCD.2012.6378687\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Though Coarse Grained Reconfigurable Architecture (CGRA) is a flexible alternative for high performance computing, it has a crucial problem on instruction code whose size is so large that the instruction memory takes a significant portion of silicon area and power consumption. This article proposes an efficient dictionary-based compression method for the CGRA instruction code, where code bit-fields are rearranged and grouped together according to locality characteristics and the most efficient compression mode is selected for each group and kernel. The proposed method can reinstall the dictionary contents adaptively for each kernel. Experimental results show that the proposed method achieved an average compression ratio 0.56 in 4×4 array of function units for well-optimized applications.\",\"PeriodicalId\":313428,\"journal\":{\"name\":\"2012 IEEE 30th International Conference on Computer Design (ICCD)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE 30th International Conference on Computer Design (ICCD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCD.2012.6378687\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 30th International Conference on Computer Design (ICCD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCD.2012.6378687","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient code compression for coarse grained reconfigurable architectures
Though Coarse Grained Reconfigurable Architecture (CGRA) is a flexible alternative for high performance computing, it has a crucial problem on instruction code whose size is so large that the instruction memory takes a significant portion of silicon area and power consumption. This article proposes an efficient dictionary-based compression method for the CGRA instruction code, where code bit-fields are rearranged and grouped together according to locality characteristics and the most efficient compression mode is selected for each group and kernel. The proposed method can reinstall the dictionary contents adaptively for each kernel. Experimental results show that the proposed method achieved an average compression ratio 0.56 in 4×4 array of function units for well-optimized applications.