MeLoPPR

This repository is the implementation of the paper MELOPPR: Software/Hardware Co-design for Memory-efficientLow-latency Personalized PageRank published at DAC'21. The paper can be found here

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Prerequisites

• Python3 preferred
• Networkx package

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Datasets:

MeLoPPR is tested on six graphs: citeseer, cora, pubmed, dblp, amazon, and youtube.

This repository contains the first three, and you may download the others from SNAP

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Code description

• equation_validation.py: validates the stage decomposition and linear decomposition equations
• toy_example.py: validates the algorithm on the citeseer graph
• PPR.py: include the optimizations discussed in the paper (with memory and CPU time measuring code commented)

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Bugs

If you experience bugs, or have suggestions for improvements, please use the issue tracker to report them.

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Publication

If this code has been useful to your research, please consider citing us:

BibTeX:

@inproceedings{meloppr,
  title={MeLoPPR: Software/Hardware Co-design for Memory-efficientLow-latency Personalized PageRank},
  author={Lixiang Li, Yao Chen, Zacharie Zirnheld, Pan Li, and Cong Hao},
  booktitle={2021 58th ACM/IEEE Design Automation Conference (DAC'21)},
  year={2021}
}