The Emergence of the Data Center as a Scientific Instrument

New laboratory devices, sensor networks, high throughput instruments, and numerical simulation systems are producing data at rates that are both without precedent and rapidly growing. The resulting increases in the volume, velocity, and variety of data are revolutionizing scientific practice. These changes demand new computing infrastructures and tools. Until recently, most laboratories and collaborations managed their own data, operated their own computers, and rarely, if ever, used remote high performance computers. We are moving to a paradigm in which data will primarily be located and managed on remote clusters, grids, and data centers.

In contrast to much of high performance computing in which data is scattered to scarce high performance resources, a computation is done, and the data is returned; in the era of data intensive computing, managing the data is much of the challenge, as is integrating the data management services with the high performance computing services.

In this talk, we will examine the computing infrastructure designed to serve this emerging era of data-intensive computing, from three perspectives: The first perspective is that of data centers, which are transitioning to providers of integrated storage, data, compute, and collaboration services. The offering of one or more of these (integrated) services over the Internet is beginning to be called cloud computing. The second perspective is that of grid computing, which enables the creation of virtual organizations that can share remote and distributed resources over the Internet. The third perspective is that of e-science, in which grids, Web 2.0 technologies, and new collaboration and analysis services are merging and changing the way science is conducted.

Robert Grossman is the Director of the Laboratory for Advanced Computing (LAC) and the National Center for Data Mining (NCDM) at the University of Illinois at Chicago

The Lab and Center perform research, sponsor standards, manage an international data mining testbed, and engage in outreach activities in the areas of data mining and data intensive computing.

Robert Grossman became a faculty member at the University of Illinois at Chicago in 1988 and is currently Professor of Mathematics, Statistics, and Computer Science and Professor of Computer Science. From 1984-1988 he was a faculty member at the University of California at Berkeley. He received a Ph.D. from Princeton in 1985 and a B.A. from Harvard in 1980. He currently holds a part time appointment at UIC.

Robert Grossman is also the Founder and Managing Partner of Open Data Group, which provides strategic, consulting, and data services so that businesses can use their data more effectively.

Prior to founding the Open Data Partners, he founded Magnify, Inc. in 1996. Magnify provides data mining solutions to the insurance industry. Grossman was Magnify's CEO until 2001 and its Chairman until it was sold to ChoicePoint in 2005. In addition, he founded Magnify Research, which provides data mining solutions to the federal government. Magnify Research was sold to Baesch Computer Consulting in 2002, and is now part of Unisys.

Grossman is the spokesperson for the Data Mining Group (DMG), an industry consortium responsible for the Predictive Model Markup Language (PMML), an XML language for data mining and predictive modeling.

Grossman is on the advisory board of InfoBlox, a company providing network appliances.

He has published over 125 papers in refereed journals and proceedings on data mining, internet technologies, high performance computing, e-business, and related areas and edited six books. He is a frequent speaker and often participates on panels at conferences and shows about data mining, internet technologoies, grid computing, high performance computing and networking, data warehousing, knowledge discovery, and e-business.

http://www.rgrossman.com/