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Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable
2018
Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA '18
There has been significant interest in parallel graph processing recently due to the need to quickly analyze the large graphs available today. Many graph codes have been designed for distributed memory or external memory. However, today even the largest publicly-available real-world graph (the Hyperlink Web graph with over 3.5 billion vertices and 128 billion edges) can fit in the memory of a single commodity multicore server. Nevertheless, most experimental work in the literature report
doi:10.1145/3210377.3210414
dblp:conf/spaa/DhulipalaBS18
fatcat:kjoegz2o65ab3oppglhc4bl6fu