We are working 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. Our 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: Erik Bodzsar, Andrew A. Chien (UChicago), Indrajit Roy, Rob Schreiber, Partha Ranganathan (HP Labs)
We gratefully acknowledge support from Hewlett-Packard for the Blockus project.