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Distributed Multithreaded Breadth-First Search on Large Graphs Using DXGraph

机译:使用DXGraph分布多线程宽度首次搜索大图

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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:交互图形应用通常在非常大的图形上产生不规则的访问模式,其中万亿边缘和数十亿顶点。为了提供交互式查询的短响应时间,所有这些小数据对象都需要存储在内存中。 DXRAM是一个分布式内存系统,优化,以有效地管理大量的小数据对象。在本文中,我们呈现DXGraph,一个允许在DXRAM存储节点上进行图形处理的扩展。对于自然图表示,每个顶点都被存储为对象。我们描述了DXGraph的宽度第一搜索(BFS)算法的实现,如图500基准测试所指定的。 BFS算法的初步评估表明,DXGraph的实现比Grappa和GraphLab的速度快5倍,并且峰值吞吐量超过32300多000秒。

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