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.
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.
Publications:
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.
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