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Strong Scaling Achieves 15.2× Speedup for Dynamic Graph Updates with Multi-Threaded Efficiency by@pagerank

Strong Scaling Achieves 15.2× Speedup for Dynamic Graph Updates with Multi-Threaded Efficiency

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January 22nd, 2025
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Dynamic Frontier PageRank demonstrates robust strong-scaling behavior for batch updates, achieving an average speedup of 10.3× with 16 threads and 15.2× with 64 threads. It gains a 1.8× performance boost with every doubling of threads but faces NUMA limitations at higher thread counts. The method efficiently handles dynamic graph updates, scaling well across datasets and graph sizes.
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Author:

(1) Subhajit Sahu, IIIT Hyderabad, Hyderabad, Telangana, India (subhajit.sahu@research.iiit.ac.in).

Abstract and 1 Introduction

2 Related Work

3 Preliminaries

4 Approach

5.1 Experimental Setup

5.2 Performance of Dynamic Frontier PageRank

5.3 Strong Scaling of Dynamic Frontier PageRan

6 Conclusion, Acknowledgments, and References

5.3 Strong Scaling of Dynamic Frontier PageRan

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This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license.


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