Shared-memory Graph Truss Decomposition

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.