{"title":"关联缓存的设计和实现","authors":"A. Mallik, M. Wildrick, G. Memik","doi":"10.1145/1013235.1013255","DOIUrl":null,"url":null,"abstract":"We introduce a new cache architecture that can be used to increase performance and reduce energy consumption in Network Processors. This new architecture is based on the observation that there is a strong correlation between different memory accesses. In other words, if load X and load Y are two consecutively executed load instructions, the offset between the source addresses of these instructions remain usually constant between different iterations. We utilize this information by building a correlating cache architecture. This architecture consists of a Dynamic Correlation Extractor, a Correlation History Table, and a Correlation Buffer. We first show simulation results investigating the frequency of correlating loads. Then, we evaluate our architecture using SimpleScalar/ARM. For a set of representative applications, the correlating cache architecture is able to reduce the average data access time by as much as 52.7% and 36.1/% on average, while reducing the energy consumption of the caches by as much as 49.2% and 25.7% on average.","PeriodicalId":120002,"journal":{"name":"Proceedings of the 2004 International Symposium on Low Power Electronics and Design (IEEE Cat. No.04TH8758)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2004-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Design and implementation of correlating caches\",\"authors\":\"A. Mallik, M. Wildrick, G. Memik\",\"doi\":\"10.1145/1013235.1013255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce a new cache architecture that can be used to increase performance and reduce energy consumption in Network Processors. This new architecture is based on the observation that there is a strong correlation between different memory accesses. In other words, if load X and load Y are two consecutively executed load instructions, the offset between the source addresses of these instructions remain usually constant between different iterations. We utilize this information by building a correlating cache architecture. This architecture consists of a Dynamic Correlation Extractor, a Correlation History Table, and a Correlation Buffer. We first show simulation results investigating the frequency of correlating loads. Then, we evaluate our architecture using SimpleScalar/ARM. For a set of representative applications, the correlating cache architecture is able to reduce the average data access time by as much as 52.7% and 36.1/% on average, while reducing the energy consumption of the caches by as much as 49.2% and 25.7% on average.\",\"PeriodicalId\":120002,\"journal\":{\"name\":\"Proceedings of the 2004 International Symposium on Low Power Electronics and Design (IEEE Cat. No.04TH8758)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2004 International Symposium on Low Power Electronics and Design (IEEE Cat. No.04TH8758)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1013235.1013255\",\"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 of the 2004 International Symposium on Low Power Electronics and Design (IEEE Cat. No.04TH8758)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1013235.1013255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We introduce a new cache architecture that can be used to increase performance and reduce energy consumption in Network Processors. This new architecture is based on the observation that there is a strong correlation between different memory accesses. In other words, if load X and load Y are two consecutively executed load instructions, the offset between the source addresses of these instructions remain usually constant between different iterations. We utilize this information by building a correlating cache architecture. This architecture consists of a Dynamic Correlation Extractor, a Correlation History Table, and a Correlation Buffer. We first show simulation results investigating the frequency of correlating loads. Then, we evaluate our architecture using SimpleScalar/ARM. For a set of representative applications, the correlating cache architecture is able to reduce the average data access time by as much as 52.7% and 36.1/% on average, while reducing the energy consumption of the caches by as much as 49.2% and 25.7% on average.