Linear Algebraic Formulation of Edge-centric K-truss Algorithms with Adjacency Matrices
Tze Meng Low, Daniele G. Spampinato, Anurag Kutuluru, Upasana Sridhar, Doru Thom Popovici, Franz Franchetti, Scott McMillan · 2018
Edge-centric algorithms using the linear algebraic approach typically require the use of both the incidence and adjacency matrices. Due to the two different data formats, the information contained in the graph is replicated, thereby incurring both time and space for the replication. Using K-truss as an example, we demonstrate that an edge-centric K-truss algorithm, the Eager K-truss algorithm, can be identified from a linear algebraic formulation using only the adjacency matrix. In addition, we demonstrate that our implementation of the linear algebraic edge-centric K-truss algorithm out-performs a Galois' K-truss implementation by an average (over 53 graphs) of more than 13 times, and up to 71 times.