GraM: scaling graph computation to the trillions

  title={GraM: scaling graph computation to the trillions},
  author={Ming Wu and Fan Yang and Jilong Xue and Wencong Xiao and Youshan Miao and Lan Wei and Haoxiang Lin and Yafei Dai and Lidong Zhou},
GraM is an efficient and scalable graph engine for a large class of widely used graph algorithms. It is designed to scale up to multicores on a single server, as well as scale out to multiple servers in a cluster, offering significant, often over an order-of-magnitude, improvement over existing distributed graph engines on evaluated graph algorithms. GraM is also capable of processing graphs that are significantly larger than previously reported. In particular, using 64 servers (1,024 physical… CONTINUE READING
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