1. SYSTEMS SUPPORT FOR GRAPHICAL LEARNING Ken Birman 1 CS6410 Fall 2014 9/18/2014

2. Graphical models and applications CS5412 Spring 2014 (Cloud Computing: Birman) 2  Artificial intelligence and machine learning is the core technology in many modern cloud settings  Support for social networking mechanisms  Creating product placement recommendations  Understanding the flow of “influence” within communities  Graphical processing can also matter in systems  Understand what to cache and what not to cache  Learning common patterns to optimize

3. What makes this hard? CS5412 Spring 2014 (Cloud Computing: Birman) 3  Prior generation of solutions was too general  Programming languages can do anything, but they aren’t at all specialized for graph structured data  Database systems are awesome for tabular data but much less optimized for graphical data  There is also an issue of scale  We’re good at what can be done on one computer  But a company like Facebook has billions of users and their infrastructure runs on massive data centers

4. Today’s papers CS5412 Spring 2014 (Cloud Computing: Birman) 4  TAO paper (I’ll start with this) gives a sense of the challenge Facebook confronts  Like an entire distributed operating system  But the whole role of the solution is to manage graphical data and support queries against it  Massive loads and surreal scale  Things to notice?  How does the architecture of the solution reflect the special environment in which it runs?  How did they identify and optimize the critical paths?

5. Dryad/LINQ CS5412 Spring 2014 (Cloud Computing: Birman) 5  Here we see two concepts combined  At Microsoft, LINQ has become very popular  It embeds a kind of query processing into C# code  Dryad takes this one step further  Given a LINQ expression, Dryad can run it on a distributed “computing engine” of their own design  Idea is to obtain massive parallelism

6. Basic architecture of Dryad CS5412 Spring 2014 (Cloud Computing: Birman) 6

7. Execution of a LINQ expression CS5412 Spring 2014 (Cloud Computing: Birman) 7

8. A join, done in two ways CS5412 Spring 2014 (Cloud Computing: Birman) 8

9. A join, done in two ways CS5412 Spring 2014 (Cloud Computing: Birman) 9

10. MapReduce in Dryad/LINQ CS5412 Spring 2014 (Cloud Computing: Birman) 10

11. Other major systems in this space CS5412 Spring 2014 (Cloud Computing: Birman) 11  Check out http://en.wikipedia.org/wiki/Graph_database http://en.wikipedia.org/wiki/Graph_database  They list 50 or so graphical databases and processing systems  Some popular ones in research settings are Pregel (from Google), GraphLab (CMU) and Vowpal Wabbit (“Fast Learning”) (Yahoo)

12. Take aways CS5412 Spring 2014 (Cloud Computing: Birman) 12  Computer systems need to be responsive to  Styles of use (what our “customers” are doing)  Common patterns of load (optimize for this case)  In today’s major cloud computing settings, graphical data and graphical learning solutions are becoming a highly dominant form of load and focus  Computer systems need to evolve to track this need