{"title":"基于亲和力的哈希表","authors":"Brian Gernhardt, Rahman Lavaee, C. Ding","doi":"10.1145/2618128.2618135","DOIUrl":null,"url":null,"abstract":"From a trace of data accesses, it is possible to calculate an affinity hierarchy that groups related data together. Combining this hierarchy with the extremely common hash table, there is an opportunity to both improve cache performance and enable novel applications. This paper describes both the construction of the affinity hierarchy and its application to hash tables.","PeriodicalId":181419,"journal":{"name":"Proceedings of the workshop on Memory Systems Performance and Correctness","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Affinity-based hash tables\",\"authors\":\"Brian Gernhardt, Rahman Lavaee, C. Ding\",\"doi\":\"10.1145/2618128.2618135\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"From a trace of data accesses, it is possible to calculate an affinity hierarchy that groups related data together. Combining this hierarchy with the extremely common hash table, there is an opportunity to both improve cache performance and enable novel applications. This paper describes both the construction of the affinity hierarchy and its application to hash tables.\",\"PeriodicalId\":181419,\"journal\":{\"name\":\"Proceedings of the workshop on Memory Systems Performance and Correctness\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the workshop on Memory Systems Performance and Correctness\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2618128.2618135\",\"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 workshop on Memory Systems Performance and Correctness","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2618128.2618135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
From a trace of data accesses, it is possible to calculate an affinity hierarchy that groups related data together. Combining this hierarchy with the extremely common hash table, there is an opportunity to both improve cache performance and enable novel applications. This paper describes both the construction of the affinity hierarchy and its application to hash tables.
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