Florentin Dörre, Alexander Krause, Dirk Habich, Martin Junghanns
{"title":"纯Java中的GraphBLAS实现","authors":"Florentin Dörre, Alexander Krause, Dirk Habich, Martin Junghanns","doi":"10.1145/3461837.3464627","DOIUrl":null,"url":null,"abstract":"Analyzing connected data in forms of graphs is more relevant than ever. To allow users to write their own custom graph algorithms, graph computation models such as GraphBLAS have been developed. Unfortunately, the popular Java programming language was mostly neglected by existing GraphBLAS implementations so far. To overcome that issue, we present our implementation of essential GraphBLAS concepts in the Java programming language in this paper. For our purpose, we extended the linear algebra library Efficient Java Matrix Library (EJML). To show the benefits of our implementation, we compare us against existing graph algorithm libraries in Java using real world graphs and three graph algorithms.","PeriodicalId":102703,"journal":{"name":"Proceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)","volume":"201 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A GraphBLAS implementation in pure Java\",\"authors\":\"Florentin Dörre, Alexander Krause, Dirk Habich, Martin Junghanns\",\"doi\":\"10.1145/3461837.3464627\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Analyzing connected data in forms of graphs is more relevant than ever. To allow users to write their own custom graph algorithms, graph computation models such as GraphBLAS have been developed. Unfortunately, the popular Java programming language was mostly neglected by existing GraphBLAS implementations so far. To overcome that issue, we present our implementation of essential GraphBLAS concepts in the Java programming language in this paper. For our purpose, we extended the linear algebra library Efficient Java Matrix Library (EJML). To show the benefits of our implementation, we compare us against existing graph algorithm libraries in Java using real world graphs and three graph algorithms.\",\"PeriodicalId\":102703,\"journal\":{\"name\":\"Proceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)\",\"volume\":\"201 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3461837.3464627\",\"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 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3461837.3464627","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analyzing connected data in forms of graphs is more relevant than ever. To allow users to write their own custom graph algorithms, graph computation models such as GraphBLAS have been developed. Unfortunately, the popular Java programming language was mostly neglected by existing GraphBLAS implementations so far. To overcome that issue, we present our implementation of essential GraphBLAS concepts in the Java programming language in this paper. For our purpose, we extended the linear algebra library Efficient Java Matrix Library (EJML). To show the benefits of our implementation, we compare us against existing graph algorithm libraries in Java using real world graphs and three graph algorithms.