SAPCo排序:优化幂律图的度排序

2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) Pub Date : 2022-05-01 DOI:10.1109/ISPASS55109.2022.00015

Mohsen Koohi Esfahani, Peter Kilpatrick, H. Vandierendonck

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引用次数: 1

摘要

我们介绍了结构感知参数计数(SAPCo)排序算法，该算法优化了度排序的性能，度排序是图分析中的一个关键操作。SAPCo利用倾斜度分布来加速分拣。对多达36亿个顶点的图的评估表明，SAPCo排序平均比计数排序、基数排序和样本排序等最先进的排序算法快1.7-33.5倍。

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SAPCo Sort: optimizing Degree-Ordering for Power-Law Graphs

We introduce the Structure-Aware Parattet Counting (SAPCo) Sort algorithm that optimizes performance of degree-ordering, a key operation in graph analytics. SAPCo leverages the skewed degree distribution to accelerate sorting. The evaluation for graphs of up to 3.6 billion vertices shows that SAPCo sort is, on average, 1.7-33.5 times faster than state-of-the-art sorting algorithms such as counting sort, radix sort, and sample sort.

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2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)

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