References#

Architecture#

2-D Data Partitioning

Kang, S., Fender, A., Eaton, J., & Rees, B. (2020, September) Computing PageRank Scores of Web Crawl Data Using DGX A100 Clusters. In 2020 IEEE High Performance Extreme Computing Conference (HPEC) (pp. 1-4). IEEE.
S. Kang, J. Nke and B. Rees, (2022 September) Analyzing Multi-trillion Edge Graphs on Large GPU Clusters: A Case Study with PageRank, In 2022 IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, USA, 2022, pp. 1-7, doi: 10.1109/HPEC55821.2022.9926341.

Brandes, U. (2001). A faster algorithm for betweenness centrality. Journal of mathematical sociology, 25(2), 163-177.
Brandes, U. (2008). On variants of shortest-path betweenness centrality and their generic computation. Social Networks, 30(2), 136-145.
McLaughlin, A., & Bader, D. A. (2018). Accelerating GPU betweenness centrality. Communications of the ACM, 61(8), 85-92.

Katz, L. (1953). A new status index derived from sociometric analysis. Psychometrika, 18(1), 39-43.
Foster, K.C., Muth, S.Q., Potterat, J.J. et al. A faster Katz status score algorithm. Computational & Mathematical Organization Theory (2001) 7: 275.

J. Cohen, Trusses: Cohesive subgraphs for social network analysis National security agency technical report, 2008
O. Green, J. Fox, E. Kim, F. Busato, et al. Quickly Finding a Truss in a Haystack IEEE High Performance Extreme Computing Conference (HPEC), 2017 https://doi.org/10.1109/HPEC.2017.8091038
O. Green, P. Yalamanchili, L.M. Munguia, Fast Triangle Counting on GPU Irregular Applications: Architectures and Algorithms (IA3), 2014

Date, K., & Nagi, R. (2016). GPU-accelerated Hungarian algorithms for the Linear Assignment Problem. Parallel Computing, 57, 52-72.

Traag, V. A., Waltman, L., & Van Eck, N. J. (2019). From Louvain to Leiden: guaranteeing well-connected communities. Scientific reports, 9(1), 1-12.

VD Blondel, J-L Guillaume, R Lambiotte and E Lefebvre. Fast unfolding of community hierarchies in large networks. J Stat Mech P10008 (2008)

Hricik, T., Bader, D., & Green, O. (2020, September). Using RAPIDS AI to Accelerate Graph Data Science Workflows. In 2020 IEEE High Performance Extreme Computing Conference (HPEC) (pp. 1-4). IEEE.