The Pittsburgh Supercomputing Center (PSC) and YarcData have announced the deployment of "Sherlock," a uRiKA graph-analytics appliance from YarcData for efficiently discovering unknown relationships or patterns hidden in extremely large and complex bodies of information.

Funded through the Strategic Technologies for Cyberinfrastructure program of the National Science Foundation, Sherlock features innovative hardware and software, as well as PSC-specific enhancements, designed to extend the range of applicability to scales not otherwise feasible.

The project complements ongoing leadership in data-intensive computing at Carnegie Mellon University. "We're very pleased that the PSC will have this new capability for analyzing large-scale, unstructured graphs," said Randal E. Bryant, dean of the School of Computer Science.

"Such data structures pervade many of the big data applications being investigated by researchers," he explained. These areas are as diverse as biology (e.g., the connectivity between molecules in a protein), networks (e.g., the structure of the world-wide web), and artificial intelligence (e.g., the relationships between different concepts.) "The uRiKA system will enable scientists to deal with far more complex graphs than would otherwise be possible," he added.

More information is available at www.psc.edu/sherlock