Case Study

Information Sciences Institute maximizes distributed data resources with Univa Grid Engine

ISI's VISTA lab conducts machine learning research faster, more efficiently, and with lower overall costs

The Information Sciences Institute (ISI) is a unit of the University of Southern California's highly ranked Viterbi School of Engineering. ISI is one of the nation's largest, most successful university-affiliated computer research institutes.
The Video, Image, Speech and Text Analytics (VISTA) group at ISI has spent the past three years advancing the state of research for facial recognition, a technology with significant implications for security and commerce. As compute demand increased, the challenge was to build an infrastructure that could scale and optimize comprehensive data simulations.

VISTA selected Univa Grid Engine as the workload management platform to manage infrastructure and accelerate its machine learning research. ISI cites key contributing factors over other vendors: built-in advanced GPU support, detailed documentation, ongoing product upgrades and customer support. Now the organization operates at 95% capacity with lower overall costs.

"We needed a reliable, powerful workload management platform that would enhance performance and have the ability to run complex, diverse workloads across multiple users within the entire ISI organization," said Stephen Rawls, programmer and research analyst, ISI.

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