DBR: A Depth-Branch-Resorting Algorithm for Locality Exploration in Graph Processing

Abstract

Unstructured and irregular graph data causes strong randomness and poor locality of data access in graph processing. In order to alleviate this problem, this paper proposes a Depth-Branch-Resorting (DBR) Algorithm for locality exploration in graph processing, and the corresponding graph data compression format DBR_DCSR. The DBR algorithm and DBR_DCSR format are tested and verified on the framework GraphBIG. The results show that in terms of execution time, the DBR algorithm and DBR_DCSR format reduce GraphBIG execution time by 55.6% compared with the original GraphBIG framework, and 71.7%, 11.46% less than the frameworks of Ligra, Gemini respectively. While compared with the original GraphBIG framework, the optimized GraphBIG framework in DBR_DCSR format has a maximum reduction of 87.9% in data movement and 52.3% in data computation. Compared to the Ligra, Genimi, the amount of data movement are reduced by 33.5% and 49.7%, the amount of data calculation reduced by 54.3% and 43.9% respectively.