Data Locality in Graph Engines: Implications and Preliminary Experimental Results

The size of graphs has dramatically increased. Graph engines for a single machine have been emerged to process these graphs efficiently. However, existing engines have overlooked a data locality which is an imperative factor to improve the performance of these engines in the previous literature. In this paper, we show the importance of data locality with graph algorithms by running on graph engines based on a single machine.This work was supported by (1) Semiconductor Industry Collaborative Project between Hanyang University and Samsung Electronics Co. Ltd., (2) the National Research Foundation of Korea (NRF) grant funded by the Korea government (No. NRF2014R1A2A1A10054151), and (3) the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2015-H8501-15-1013) supervised by the IITP (Institute for Information and communication Technology Promotion)