Shared-memory Graph Truss Decomposition
Humayun Kabir, Kamesh Madduri

TL;DR
This paper introduces PKT, a shared-memory parallel algorithm for efficient truss decomposition of large sparse graphs, outperforming existing methods on multi-core systems.
Contribution
The paper presents PKT, a novel shared-memory parallel algorithm and OpenMP implementation for truss decomposition, based on a recent k-core decomposition algorithm.
Findings
PKT outperforms other truss decomposition methods on large graphs.
PKT is efficient on a 24-core shared-memory server.
PKT leverages a recent k-core decomposition algorithm.
Abstract
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 can be considered a relaxation of a clique. Truss decomposition refers to a partitioning of all the edges in the graph based on their k-truss membership. The truss decomposition of a graph has many applications. We show that our new approach PKT consistently outperforms other truss decomposition approaches for a collection of large sparse graphs and on a 24-core shared-memory server. PKT is based on a recently proposed algorithm for k-core decomposition.
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