Bilkent University
Department of Computer Engineering


Scalable Layout of Large Graphs on Disk


Abdurrahman Yaşar
MSc Student
Computer Engineering Department
Bilkent University

We are witnessing an enormous growth in social networks as well as in the volume of data generated by them. As a consequence, processing this massive amount of data has become a major problem. An important portion of this data is in the form of graphs. In recent years, several graph processing and management systems emerged to handle large-scale graphs. The primary goal of these systems is to run graph algorithms in an efficient and scalable manner. Unlike relational data, graphs are semi-structured in nature. Thus, storing and accessing graph data using secondary storage requires new solutions that can provide locality of access for graph processing workloads. In this work, we propose a novel scalable disk layout technique for graphs, which aims at reducing the I/O cost of disk-based graph processing algorithms. To achieve this goal, we designed a scalable Map/Reduce-style method called ICBP, which can divide the graph into a series of disk blocks that contain sub-graphs with high locality. Furthermore, ICBP can order the resulting blocks on the disk to further reduce non-local accesses. We experimentally evaluated ICBP to showcase its scalability, layout quality, as well as the effectiveness of automatic parameter tuning for ICBP.


DATE: 15 June, 2015, Monday @ 10:00