Week 11: Graph Computing — Bulk Synchronous Parallel & Pregel

Lecture notes:
Other parallel computing frameworks - Lecture slides (6 per page)
Supplemental notes:
Grzegorz Malewicz, Matthew H. Austern, Aart J. C. Bik, James C. Dehnert, Ilan Horn, Naty Leiser, and Grzegorz Czajkowski, Pregel: A System for Large-Scale Graph Processing, SIGMOD 2010 Proceedings of the 2010 ACM SIGMOD International Conference on Management of data, pages 135-146.
The definitive paper on Pregel. It's about 8.4 pages of text. If you don't have the stamina to read the whole thing, read the first six pages, up to section 5. Section 5 covers examples of Pregel in action.
Avery Ching, Scaling Apache Giraph to a trillion edges, August 14, 2013.
A short article discussing how Facebook adopted Giraph and thier experiences of using it on a one trillion edge social graph.
Grzegorz Czajkowski, Large-scale graph computing at Google, Google Research Blog, June 15, 2009
A really short (under one page) introduction to Pregel in the Research at Google blog. Worth reading to get an idea of what the whole point of Pregel is.
Apache Hama Project
Apache's BSP (Bulk Synchronous Parallel) computing framework
Processing large-scale graph data: A guide to current technology
An IBM developerWorks article discussing large-scale graph processing.
Bulk Synchronous Parallel (BSP) framework, supersteps, barrier synchronization, Pregel, vertex, edge, vote to halt, aggregator, combiner, topology modification, master, workers, checkpointing.