Accelerating processing of scale-free graphs on massively-parallel architectures

Abstract

Processing of big scale-free graphs on parallel architectures with high parallelization opportunities connected with a lot of overheads. Due to skewed degree distribution each thread receives different amount of computational workload. In this paper we present a method devoted to address this challenge by modificating CSR data structure and redistributing work across threads. The method was implemented in breadth-first search and single source shortest path algorithms for GPU architecture.