Open PhD/Postdoc positions for large scale graph analytics

My colleague Oded Margalit from IBM Haifa sent me a note about an open position for a joint IBM/Technion funded PhD or Postdoc position in large scale distributed systems research.
Anyone who is interested is welcome to apply (the position is open only for researchers who where outside of Israel in the last 3 years).

Another open PhD position in KTH (Stockholm) for social network and graph processing researcher, I got from my previous collaborator Sarunas Girdzijauskas.

Amazon's CTO writes about GraphLab in his blog

I got the following from a former colleage of mine: Barak Merimovich from Gigaspaces. It seems that Amazon's CTO, Werner Vogel have written recently about GraphLab in his blog:

"I want to kick off the fall readings not with an historical paper but with two that detail GraphLab, an excellent framework for high performance machine learning that originally has been built by the Carlos Guestrin. GraphLab has been used to build several different data mining and graph processing toolkits and applications. The research in the papers has been performed on Amazon EC2. Instructions for running your own GraphLab Cluster on EC2 can be found here ..."

Additionally, I learned today from our man in O'Reilly Media, Ben Lorica, that has mentioned GraphLab in his blog post.

New report about Giraph's performance @ Facebook

I got from several sources, the following blog post about Giraph's performance at Facebook, which is an interesting read.

A couple of months ago, we have invited Avery Ching to give a talk about Giraph @ our 2nd GraphLab workshop. Here is a video of his talk:

The magnitude of Giraph deployment, using graphs with trillion edges, is definitely impressive, and is one of the largest graph deployment reports as far as I am aware.

And I like most the following sentence: "we selected a few promising graph-processing platforms including Apache Hive, GraphLab, and Apache Giraph for evaluation"

:-)

2nd GraphLab Workshop Talks Now Online!

We have just released most of the workshop talks. If you missed the workshop, you are encouraged to catch up! Here is the GraphLab Keynote talk by Prof. Carlos Guestrin, CEO of GraphLab & Prof. at University of Washington:

The rest of the talk videos are here.

Patrick Durusau sent me a link to his blog post where he linked all speakers and presenters to their DBLP publications. Thanks Patrick!

Benchmarking Machine Learning Frameworks

I am often contacted from different researchers (both universities and companies) who are trying to benchmark and compared different machine learning frameworks. I am trying to introduce them to each other, since basically everyone is compiling the same benchmark tests, and it will be a good idea to create uniform measures and practices for comparing systems. One such example is Intel Labs report I wrote about a couple of months ago in my blog.

A few days ago I got from my collaborator Aapo Kyrola a related paper: Li, Kevin; Gibson, Charles; Ho, David; Zhou, Qi; Kim, Jason; Buhisi, Omar; Brown, Donald E.; Gerber, Matthew, "Assessment of machine learning algorithms in cloud computing frameworks", Systems and Information Engineering Design Symposium (SIEDS), 2013 IEEE, pp.98,103, 26-26 April 2013. IEEExplore

The above paper performs some comparison tests on Amazon EC2, using the same hardware, and similar algorithms and datasets. And here is the bottom line:

As you can see, GraphLab is significantly faster, comparing two tasks: collaborative filtering (ALS) and text analysis (LDA). The paper claim that mahout is slightly more accurate.

Hopefully the construction in the paper is detailed enough so people will be able to reproduce it.

Large Scale Reommender Systems Workshop - LSRS 2013 - Call for papers

As part of Recsys 2013, we (Tao Ye from Pandora & Quan Yuan from Taobao) are organizing a large scale recommender system workshop.

Anyone working in this domain is encouraged to submit an abstract describing your work. 

Submission deadline is July 21st, 2013. Extended to July 25, 2013.

We have two confirmed keynotes:

• Aapo Kyrola, CMU will talk about GraphChi out of core graph computation framework
• Justin Basilico, Netflix will talk about collaborative filtering @ Netflix

Still a chance to win a Google Chrome book, iPad and Kindle!!

Only two days left to fill our online survey.

Looking forward to hear more what are you working on, which tools are you using and what data magnitudes.

We will announce in a couple of days of the winners (by emailing the winners directly, and also using this blog)


Additionally, we have 3 local GraphLab users meetup groups:

San Francisco: http://www.meetup.com/San-Francisco-GraphLab-Users/
Atlanta: http://www.meetup.com/Atlanta-GraphLAB-Users-Group/
Seattle: http://www.meetup.com/Seattle-GraphLab-Users/
New York: http://www.meetup.com/New-York-GraphLab-Users/

We plan to hold occasional meetups with tutorials, demo and new feature releases of GraphLab.

Everyone is welcome to join!