F. Carloni, Davide Conficconi, Ilaria Moschetto, M. Santambrogio
{"title":"异构系统中正则表达式匹配的一种表征方法","authors":"F. Carloni, Davide Conficconi, Ilaria Moschetto, M. Santambrogio","doi":"10.1109/ISCAS46773.2023.10181547","DOIUrl":null,"url":null,"abstract":"The continuous growth of data pushes novel and efficient approaches for information retrieval. In this context, Regular Expression (RE) matching is widely employed and represents a relevant computational kernel that carries control-and memory-related issues. Among the several solutions to relieve these burdens, accelerators seem a promising alternative to general-purpose systems. However, state-of-the-art benchmarking presents a highly fragmented scenario without consensus on the approach and lacks an open-source strategy. Therefore, to fairly characterize existing execution engines, this work presents YARB, an open benchmarking methodology. It builds upon literature solutions, a comprehensive approach, and an in-depth characterization of heterogeneous systems. Moreover, YARB's openness will enable future integrations and engines comparison.","PeriodicalId":177320,"journal":{"name":"2023 IEEE International Symposium on Circuits and Systems (ISCAS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"YARB: a Methodology to Characterize Regular Expression Matching on Heterogeneous Systems\",\"authors\":\"F. Carloni, Davide Conficconi, Ilaria Moschetto, M. Santambrogio\",\"doi\":\"10.1109/ISCAS46773.2023.10181547\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The continuous growth of data pushes novel and efficient approaches for information retrieval. In this context, Regular Expression (RE) matching is widely employed and represents a relevant computational kernel that carries control-and memory-related issues. Among the several solutions to relieve these burdens, accelerators seem a promising alternative to general-purpose systems. However, state-of-the-art benchmarking presents a highly fragmented scenario without consensus on the approach and lacks an open-source strategy. Therefore, to fairly characterize existing execution engines, this work presents YARB, an open benchmarking methodology. It builds upon literature solutions, a comprehensive approach, and an in-depth characterization of heterogeneous systems. Moreover, YARB's openness will enable future integrations and engines comparison.\",\"PeriodicalId\":177320,\"journal\":{\"name\":\"2023 IEEE International Symposium on Circuits and Systems (ISCAS)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Symposium on Circuits and Systems (ISCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCAS46773.2023.10181547\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Symposium on Circuits and Systems (ISCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAS46773.2023.10181547","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
YARB: a Methodology to Characterize Regular Expression Matching on Heterogeneous Systems
The continuous growth of data pushes novel and efficient approaches for information retrieval. In this context, Regular Expression (RE) matching is widely employed and represents a relevant computational kernel that carries control-and memory-related issues. Among the several solutions to relieve these burdens, accelerators seem a promising alternative to general-purpose systems. However, state-of-the-art benchmarking presents a highly fragmented scenario without consensus on the approach and lacks an open-source strategy. Therefore, to fairly characterize existing execution engines, this work presents YARB, an open benchmarking methodology. It builds upon literature solutions, a comprehensive approach, and an in-depth characterization of heterogeneous systems. Moreover, YARB's openness will enable future integrations and engines comparison.