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Distributed Multithreaded Breadth-First Search on Large Graphs Using DXGraph

机译:使用DXGraph在大型图上进行分布式多线程广度优先搜索

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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.
机译:交互式图形应用程序通常在具有数万亿个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。为了缩短交互式查询的响应时间,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,经过优化可有效管理大量小数据对象。在本文中,我们介绍了DXGraph,它是允许在DXRAM存储节点上进行图形处理的扩展。对于自然图形表示,每个顶点都存储为一个对象。我们将根据Graph500基准测试描述DXGraph的广度优先搜索(BFS)算法的实现。 BFS算法的初步评估表明,DXGraph的实现速度比Grappa和GraphLab快5倍,峰值吞吐率超过每秒3.23亿遍。

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