With the rise of graph-based algorithms in many applications, dynamic graphs have become critical for applications that work with real-time or time-series relationship data. Due to their large storage footprint, these applications require high parallelism and locality. Many-core architectures offer high parallelism for both static and dynamic graphs. However, systems operating on dynamic graphs must continuously repartition graph data across storage units to achieve good locality, load balancing, and performance. In this work, we examine the effectiveness and efficiency of different vertex-pressure repartitioning schemes, which move vertices so to co-locate them near their most relevant neighbors. We describe key repartitioning design choices and provide a thorough evaluation of the impact of a range of design features with different datasets. Our evaluation indicates that optimized dynamic repartitioning techniques can often provide over 2x performance speedup over state-of-the-art static solutions.

中文翻译：

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在多核系统中优化顶点压力动态图分区

随着基于图形的算法在许多应用程序中的兴起，动态图形对于使用实时或时间序列关系数据的应用程序已变得至关重要。由于它们的存储空间很大，因此这些应用程序需要高度的并行性和局部性。多核体系结构为静态图和动态图提供了高度的并行性。但是，在动态图上运行的系统必须跨存储单元连续重新划分图数据，以实现良好的局部性，负载平衡和性能。在这项工作中，我们研究了不同顶点压力重新分配方案的有效性和效率，这些方案会移动顶点，以便将它们共同定位在最相关的邻居附近。我们描述了关键的重新分区设计选择，并提供了对具有不同数据集的一系列设计功能的影响的全面评估。