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[Colloquium] Scalable Data Services for Data-Intensive Computing Environments
March 26, 2009
- Date: Thursday, March 26th, 2009
- Time: 11 am — 12:15 pm
- Place: ME 218
Patrick Widener
Ph.D. Department of Computer Science University of New Mexico
Abstract: Future I/O systems for increasingly data-intensive computing environments face a challenging set of requirements. Data extraction must be efficient, fast, and flexible; on-demand data annotation — metadata creation and management — must be possible without modifying application code; and data products must be available for concurrent use by multiple applications (such as visualization and storage), requiring consistency management and scheduling. In this talk, I will present a collection of techniques (DataTaps, IOgraphs, and Metabots) designed to address these challenges by decoupling data operations in space and in time from core application codes. Our research results show that these techniques can extract data efficiently and without perturbing compute nodes, that they can be used to perform application-specific transformations while maintaining acceptable I/O bandwidth and avoiding back-pressure, and that they can exploit “in-band” and “out-of-band” decoupling to improve overall I/O performance. Our approach enables the creation of scalable data services which can keep pace with the next generation of data-intensive applications.
Bio: Patrick M. Widener is a Research Assistant Professor in the Department of Computer Science at the University of New Mexico. Dr. Widener’s research interests include experimental systems, I/O and storage software for large-data environments, middleware, and the generation and use of metadata. He focuses primarily on high-performance, enterprise, and pervasive application domains. Dr. Widener received his Ph.D. in Computer Science from the Georgia Institute of Technology in 2005. Prior to beginning his Ph.D. study, he was employed as a software developer by several companies which no longer exist. He also holds a Master of Computer Science degree from the University of Virginia (1992), and a Bachelor of Science in Computer Science from James Madison University (1990).