You can find slides for the Ligra tutorial here.
Welcome! These documents will teach you about the Ligra Graph Processing Framework. Ligra is a lightweight framework for processing graphs in shared memory. It is particularly suited for implementing parallel graph traversal algorithms where only a subset of the vertices are processed in an iteration. The project was motivated by the fact that the largest publicly available real-world graphs all fit in shared memory. When graphs fit in shared-memory, processing them using Ligra can give performance improvements of up orders of magnitude compared to distributed-memory graph processing systems.
This document is split up into a number of sections.
Julian Shun and Guy Blelloch. Ligra: A Lightweight Graph Processing Framework for Shared Memory. Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), pp. 135-146, 2013.
Julian Shun, Laxman Dhulipala and Guy Blelloch. Smaller and Faster: Parallel Processing of Compressed Graphs with Ligra+. Proceedings of the IEEE Data Compression Conference (DCC), pp. 403-412, 2015.
Julian Shun. An Evaluation of Parallel Eccentricity Estimation Algorithms on Undirected Real-World Graphs. Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015.