Fast Dynamic Graph Algorithms

  • Gaurav Malhotra
  • Hitish Chappidi
  • Rupesh NasreEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11403)


We show that dynamic graph algorithms are amenable to parallelism on graphics processing units (GPUs). Evolving graphs such as social networks undergo structural updates, and analyzing such graphs with the existing static graph algorithms is inefficient. To deal with such dynamic graphs, we present techniques to (i) represent evolving graphs, (ii) amortize the processing cost over multiple updates, and (iii) optimize graph analytic algorithms for GPUs. We illustrate the effectiveness of our proposed mechanisms with three dynamic graph algorithms: dynamic breadth-first search, dynamic shortest paths computation and dynamic minimum spanning tree maintenance. In particular, we show that the dynamic processing is beneficial up to a certain percentage of updates beyond which a static algorithm is more efficient.



We thank the reviewers and our shepherd Nancy Amato for their comments which considerably improved our work. This work is partially supported by IIT Madras Exploratory Research Grant CSE/16-17/837/RFER/RUPS.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Gaurav Malhotra
    • 1
  • Hitish Chappidi
    • 1
  • Rupesh Nasre
    • 1
    Email author
  1. 1.IIT MadrasChennaiIndia

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