Incremental Vertex Processing Boosts PageRank Update Efficiency on Dynamic Graphs
22 Jan 2025
Dynamic Frontier updates PageRank efficiently on dynamic graphs, outperforming existing methods by up to 7.8× on a 64-core server.
Efficient PageRank Updates on Dynamic Graphs and Existing Approaches
22 Jan 2025
Explores PageRank computation, dynamic graphs, and methods like Naive-dynamic and Dynamic Traversal for efficient updates in evolving networks.
Key Insights and Future Directions for PageRank on Dynamic Graphs
22 Jan 2025
Dynamic Frontier improves PageRank updates on dynamic graphs, achieving up to 8.3× speedup and scalable performance on 64-core systems.
Dynamic Frontier PageRank Achieves Efficiency and Accuracy with Batch Updates and Parallel Computing
22 Jan 2025
Dynamic Frontier PageRank evaluation on large graphs reveals significant efficiency and accuracy improvements using batch updates and parallel computing.
Strong Scaling Achieves 15.2× Speedup for Dynamic Graph Updates with Multi-Threaded Efficiency
22 Jan 2025
Dynamic Frontier PageRank shows strong scaling, achieving a 15.2× speedup on 64 threads for dynamic graph updates, with efficient thread utilization.
Comparative Analysis of Incremental Methods for Updating PageRank on Dynamic Graphs
22 Jan 2025
Explore incremental methods for updating PageRank on dynamic graphs, comparing approaches like Monte Carlo, BFS, and hybrid CPU-GPU models.
Dynamic Frontier PageRank Efficiently Updates Ranks on Dynamic Graphs
22 Jan 2025
Dynamic Frontier PageRank efficiently updates ranks on dynamic graphs by incrementally processing affected vertices with controlled tolerance levels.