Blockus: Big Graph Computations

The Blockus project is creating new understanding and technologies to enable large-scale graph computations.  Efforts include, understanding the behavior of graph algorithms and graph processing systems, scaling out and vertically (to use SSD's and other novel non-volatile memories), and exploring graph computations on with realistic application data usage restrictions.

  • Understanding the behavior of graph computations and algorithms - how diverse as a function of algorithm and graph?  how can we systematically explore the performance space?
  • Vertical scalability using new storage-class memories -- can we achieve intelligent storage-hierarchy management to achieve dramatically better cost-performance and programming flexibility for big data computations?
  • Exploring realistic data sharing and privacy contraints in graph computations -- can we maintain good scalability and performance in the face of such constraints?
We are currently working with GraphX and Graphlab systems.  Our early work was with  researchers at HP Labs, who have created an extension of the R programming system, called Presto, that supports scale-out parallelism in an extended R language. In Presto, users express computation on (possibly sparse) matrix partitions, and the system takes care of the distribution of data and computation. The work at Chicago focuses on building on the Presto programming model and engine, enhancing it to scale vertically: that is creating a cost-effective, flexible and easy to program system that handles big data using secondary storage.


People: Fan Yang,  Andrew A. Chien (UChicago)     Alumni:  Erik Bodzsar, Indrajit Roy, Rob Schreiber, Partha Ranganathan (HP Labs)

We gratefully acknowledge support from Hewlett-Packard for the Blockus project.

The LSSG is part of the Systems Group in the University of Chicago's   Department of Computer Science, and also affiliated with Chicago's Computation Institute, and Argonne National Laboratory's Mathematics and Computer Science Division.
Andrew A. Chien,
Jun 6, 2015, 7:48 AM