{"title":"Haskell中的延迟图形处理","authors":"Philip Dexter, Yu David Liu, K. Chiu","doi":"10.1145/2976002.2976014","DOIUrl":null,"url":null,"abstract":"This paper presents a Haskell library for graph processing: DeltaGraph. One unique feature of this system is that intentions to perform graph updates can be memoized in-graph in a decentralized fashion, and the propagation of these intentions within the graph can be decoupled from the realization of the updates. As a result, DeltaGraph can respond to updates in constant time and work elegantly with parallelism support. We build a Twitter-like application on top of DeltaGraph to demonstrate its effectiveness and explore parallelism and opportunistic computing optimizations.","PeriodicalId":20669,"journal":{"name":"Proceedings of the 9th International Symposium on Haskell","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Lazy graph processing in Haskell\",\"authors\":\"Philip Dexter, Yu David Liu, K. Chiu\",\"doi\":\"10.1145/2976002.2976014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a Haskell library for graph processing: DeltaGraph. One unique feature of this system is that intentions to perform graph updates can be memoized in-graph in a decentralized fashion, and the propagation of these intentions within the graph can be decoupled from the realization of the updates. As a result, DeltaGraph can respond to updates in constant time and work elegantly with parallelism support. We build a Twitter-like application on top of DeltaGraph to demonstrate its effectiveness and explore parallelism and opportunistic computing optimizations.\",\"PeriodicalId\":20669,\"journal\":{\"name\":\"Proceedings of the 9th International Symposium on Haskell\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 9th International Symposium on Haskell\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2976002.2976014\",\"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 9th International Symposium on Haskell","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2976002.2976014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a Haskell library for graph processing: DeltaGraph. One unique feature of this system is that intentions to perform graph updates can be memoized in-graph in a decentralized fashion, and the propagation of these intentions within the graph can be decoupled from the realization of the updates. As a result, DeltaGraph can respond to updates in constant time and work elegantly with parallelism support. We build a Twitter-like application on top of DeltaGraph to demonstrate its effectiveness and explore parallelism and opportunistic computing optimizations.
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