The 2nd GraphLab Workshop will take place on Monday July 1st at the Nikko Hotel, in downtown San Francisco. Join us for a full day to learn about state-of-the-art development in Graph analytics solutions. Registration is now open – enjoy early bird discount rates! The aim of the workshop is to bring together researchers from
So it’s been a while … We know, but we’ve been busy! We are putting the finishing touches on GraphLab 2.2 and expect to release it in early July at the GraphLab workshop. What you can expect in this next release of GraphLab is: Substantially improved loading and runtime performance through new partitioning and layout
Many thanks to Mark Levy (last.fm) for contributing implementation of the CLiMF algorithm to our growing collaborative filtering toolkit: read more.
Many thanks to Dhruv Batra from Virginia Tech for kindly donating this implementation to our growing graphical models toolkit. Full documentation is here.
We just presented our work on PowerGraph at OSDI! PowerGraph is the system and abstraction that forms the foundation of the current version of GraphLab. The PowerGraph research effort attempts to answer the question: “How can we efficiently design and implement distributed computation on the large-scale natural-graphs graphs found in settings ranging from social networks to
We have two papers accepted to OSDI 2012! One on GraphLab: PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs. Joseph Gonzalez, Yucheng Low, Haijie Gu, Danny Bickson and Carlos Guestrin. [pdf][bib/abs] And another on GraphChi: GraphChi: Large-Scale Graph Computation on Just a PC. Aapo Kyrola, Guy Blelloch, and Carlos Guestrin. [pdf] [bib]
Carlos introduced the next generation of the GraphLab abstraction including the exciting new GraphChi project. Checkout the slides: Download Keynote Slides
We want to thank everyone who attended the GraphLab 2012 workshop on BigLearning. It was a great success! We had over 300 attendees and a density of exciting talks that rivals top tier conferences. For those who missed it, we will be posting the slides and posters as well as the video lectures as soon
We have been collaborating with Intel to develop the new GraphBuilder library which provides tools to construct large-scale graphs on top of Apache Hadoop. The library provides function for: Pre-processing – Feature selection/Tokenization, and Tabulation Graph construction – Edge and Vertex lists Graph Normalization – Compression techniques for sparse graph labels Graph Transformation – Optional filters for
Too celebrate the 2.1 release of the GraphLab API and to better communicate the exciting new features.