HiPC International Conference On High Performance Computing
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HiPC 2002 - Bangalore, India - December 18-21
Bangalore Palace
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2 :0 0 p m - 6 :0 0 p m
Data Grid Management Systems: Towards Knowledge Grid Networks

Arcot Rajasekar and Arun Jagatheesan
San Diego Supercomputer Center University of California, San Diego

Audience: Since the tutorial covers basics, open research issues and demonstration sessions, a wide variety of people fall into the category of "intended audience". Based on similar experiences before at NPACI (National Partnership for Advanced Computing Infrastructure), the following people would be benefited: Beginners, Students: The introductory sections will provide valuable information on Data Grids, Computational Grids and projects using these technologies. Researchers: Investigators who already are in HPC will be updated on new challenges and methodology in data management. System Developers: Information about data grid requirements and components will showcase future development challenges. Commercial Companies: The case studies would provide solutions to similar problems in the commercial world.

Course Description: Data grids handle large-scale, distributed, heterogeneous collections of data shared among virtual organizations. This tutorial provides insight into opportunities, components and case studies of data grids and explores their usage in high performance and large scale computing environments. Starting with challenges in data handling, the tutorial will also provide an overview of the data grid technology, design philosophy, best practices and services for the next generation commercial and scientific applications. It will introduce the burgeoning field of data grid management systems (DGMS), and illustrate real-life grids (GriPhyN, NVO, BIRN, etc.) and grid components (Storage Resource Broker, Grid Portal, etc.). If possible, a hands-on session to use and "feel" a working data grid system will be provided. The course outline is as follows: 1) Introduction to Data Grids (What?), 2) Requirement for Data Grids (Why?), 3) Data Grid Components (How?), 4) Case Studies (Where?), 5) SRB Demo/Hands On (Can I?), 6) Other Technologies (What else?), 7) Data Grid Management Systems, 8) Knowledge Grid Network (What next?), and 9) Uncharted Waters (New challenges?).

Lecturers: Dr. Arcot Rajasekar is the Director of the Data Grid Technologies Group at the San Diego Supercomputer Center at UCSD. His research interests include data grids, digital library systems, persistent archives and distributed data collection & metadata management. He is a key architect of the SDSC Storage Resource Broker, an intelligent data grid integrating distributed data archives, file repositories and digital collections. Dr. Rajasekar received his PhD from the University of Maryland and has more than 50 publications in artificial intelligence, databases and data grid systems. His email address is sekar@sdsc.edu.

Arun Jagatheesan is a Visiting Scholar at the San Diego Supercomputer Center and a member of the High Energy Physics Group at the University of Florida. His current research interests include Internet Computing, Data Grid Management, Semantic Web and Workflow Systems. He is involved in research and development of GriPhyN (Grid Physics Network), SRB Web Services and Data Grid Management Systems at SDSC. Jagatheesan received his M.S in Computer Science from the University of Florida. His email address is arun@sdsc.edu.