Distributed Multithreaded Breadth-First Search on Large Graphs Using DXGraph

Stefan Nothaas, Kevin Beineke, M. Schöttner
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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.
基于DXGraph的大型图的分布式多线程广度优先搜索
交互式图形应用程序经常在具有数万亿条边和数十亿个顶点的非常大的图形上生成不规则的访问模式。为了为交互式查询提供较短的响应时间,所有这些小数据对象都需要存储在内存中。DXRAM是一种分布式内存系统,可以有效地管理大量的小数据对象。在本文中,我们提出了DXGraph,一个允许在DXRAM存储节点上进行图形处理的扩展。对于一个自然的图表示,每个顶点被存储为一个对象。我们描述了DXGraph对宽度优先搜索(BFS)算法的实现,该算法由Graph500基准测试指定。对BFS算法的初步评估表明,DXGraph的实现比Grappa和GraphLab的实现快5倍,峰值吞吐量超过每秒3.23亿遍历边。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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