Intel Research Seminar

DATE: Thursday, January 22, 2004
TIME: Noon - 1:30 pm
PLACE: Intel Seminar (417 S. Craig Street - 3rd Floor)

Didi Yao
University of Southern California

Scalable Randomization for Dynamic Data Storage

A scalable storage architecture is important in systems that store and access growing data sets. Storage scalability enables the increase or decrease of the overall storage bandwidth and capacity as needed. A truly scalable system should accept any amount of growth in data size without hindering system

This talk will describe a scalable randomization algorithm to enable an efficient, dynamically expandable storage system. While previous techniques can support a balanced load and quick data retrieval, they fail in efficiency of data relocation during scaling. Other techniques provide minimal relocation, but do not offer incremental scaling. The challenge is to find a scaling solution that maintains a balanced load and provides fast data access without costly data reorganization. Finally, advances in technology inevitably result in the replacement of old homogeneous storage devices with new heterogeneous devices; thus, heterogeneous scaling is also supported.

Didi Yao received his Ph.D. and M.S. in Computer Science in 2003 and 2000, respectively, from the University of Southern California (USC). He received his B.S. in Electrical Engineering and Computer Science in 1997 from the University of California, Berkeley. His research interests include scalable storage architectures, multimedia servers, and distributed systems. At USC, he co-architected a distributed, continuous media server called Yima, implemented its storage subsystem, and researched several storage scaling techniques. He was a co-founder of the Graduate Tech Alliance at USC's Marshall School of Business, which actively assisted in commercializing USC technologies. Prior to USC, he was a bioinformatics researcher for the Berkeley Drosophila Genome Project. Dr. Yao is a recipient of the Intel Ph.D. Fellowship.

For Further Seminar Info:
Contact Kim Kaan, 412-605-1203, or visit

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