Improving High-Performance GPU Graph Traversal with Compression

Abstract

Traversing huge graphs is a crucial part of many real-world problems, including graph databases. We show how to apply Fixed Length lightweight compression method for traversing graphs stored in the GPU global memory. This approach allows for a significant saving of memory space, improves data alignment, cache utilization and, in many cases, also processing speed. We tested our solution against the state-of-the-art implementation of BFS for GPU and obtained very promising results. © Springer International Publishing Switzerland 2015.