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.

- Getting Started - Set up your machine to use Ligra
- Tutorial: BFS - Develop a simple breadth-first search in Ligra
- Tutorial: KCore - Develop an app to compute the KCores of a graph
- API - Comprehensive API reference
- Examples - Overview of example Ligra applications

Julian Shun and Guy E. 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 E. 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), pp. 1095-1104, 2015.

Julian Shun, Farbod Roosta-Khorasani, Kimon Fountoulakis, and Michael
W. Mahoney. *Parallel Local Graph Clustering*. Proceedings of the
International Conference on Very Large Data Bases (VLDB), 9(12),
pp. 1041-1052, 2016.

Laxman Dhulipala, Guy E. Blelloch, and Julian Shun. *Julienne: A Framework for Parallel Graph Algorithms using Work-efficient Bucketing*. Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), pp. 293-304, 2017.