{"title":"Distributed Multithreaded Breadth-First Search on Large Graphs Using DXGraph","authors":"Stefan Nothaas, Kevin Beineke, M. Schöttner","doi":"10.1109/HPGDMP.2016.5","DOIUrl":null,"url":null,"abstract":"Interactive graph applications are often generating irregular access patterns on very large graphs with trillions of edges and billions of vertices. In order to provide short response times for interactive queries, all these small data objects need to be stored in memory. DXRAM is a distributed in-memory system optimized to efficiently manage large amounts of small data objects. In this paper, we present DXGraph, an extension to allow graph processing on DXRAM storage nodes. For a natural graph representation, each vertex is stored as an object. We describe DXGraph's implementation of a breadth-first search (BFS) algorithm, as specified by the Graph500 benchmark. The preliminary evaluation of the BFS algorithm shows that DXGraph's implementation is up to five times faster than Grappa's and GraphLab's with a peak throughput of over 323 million traversed edges per second.","PeriodicalId":189262,"journal":{"name":"2016 High Performance Graph Data Management and Processing Workshop (HPGDMP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 High Performance Graph Data Management and Processing Workshop (HPGDMP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPGDMP.2016.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Interactive graph applications are often generating irregular access patterns on very large graphs with trillions of edges and billions of vertices. In order to provide short response times for interactive queries, all these small data objects need to be stored in memory. DXRAM is a distributed in-memory system optimized to efficiently manage large amounts of small data objects. In this paper, we present DXGraph, an extension to allow graph processing on DXRAM storage nodes. For a natural graph representation, each vertex is stored as an object. We describe DXGraph's implementation of a breadth-first search (BFS) algorithm, as specified by the Graph500 benchmark. The preliminary evaluation of the BFS algorithm shows that DXGraph's implementation is up to five times faster than Grappa's and GraphLab's with a peak throughput of over 323 million traversed edges per second.