22 citations · 27 across the 8 of their papers we have counts for
5 papers · 1 filter
GPU-Accelerated Multilevel Graph Clustering: A Parallel Perspective on Louvain and Leiden
Michael S. Gilbert, Kamesh Madduri
The sequential Louvain and Leiden algorithms are widely used techniques for modularity-optimizing clustering (or community detection) in large graphs. We present pLouvain and pLeid…
Scalable and Adaptive Parallel Training of Graph Transformer on Large Graphs
Jun-Liang Lin, Kamesh Madduri, Mahmut Taylan Kandemir
Graph foundation models have demonstrated remarkable adaptability across diverse downstream tasks through large-scale pretraining on graphs. However, existing implementations of th…
Jet: Multilevel Graph Partitioning on Graphics Processing Units
Michael S. Gilbert, Kamesh Madduri, Erik G. Boman +1
The multilevel heuristic is the dominant strategy for high-quality sequential and parallel graph partitioning. Partition refinement is a key step of multilevel graph partitioning.…
Shared-memory Graph Truss Decomposition
Humayun Kabir, Kamesh Madduri
We present PKT, a new shared-memory parallel algorithm and OpenMP implementation for the truss decomposition of large sparse graphs. A k-truss is a dense subgraph definition that c…
Distributed-Memory Breadth-First Search on Massive Graphs
Aydin Buluc, Scott Beamer, Kamesh Madduri +2
This chapter studies the problem of traversing large graphs using the breadth-first search order on distributed-memory supercomputers. We consider both the traditional level-synchr…