Friday, February 04, 2011

Teaching Cloud Computing to Google

Professor Jeffrey Ullman will sepak on Map-Reduce and its Children, 21st February 2011 in Canberra.
Professor Jeffrey Ullman
Map-Reduce and Its Children

Since its publication by Google researchers in 2004, Map-reduce has proven to be a significant
advance in programming methodology that offers resilient, easy-to-code parallel computation on
a modern computing cluster or "cloud." It has led to a variety of systems that improve it in different ways. One direction is raising the level of abstraction, especially to support relational-database operations. A second direction is increasing the generality, while maintaining the programmability and resiliency in the face of partial failures. We shall review the environment of a map-reduce system, give some examples of how it works, and discuss the various extensions and the technical problems they posed.

Jeff Ullman is one of the world's best known computer scientists. His contributions to theoretical London Circuit, Canberra computer science and its applications to compilers, parallelism, and databases, as well as his
textbooks in those areas have been widely acknowledged, notably by the 2000 Knuth Prize and the 2010 IEEE John von Neumann Medal. He was the advisor of an entire generation of PhD students, including Sergey Brin, one of the co-founders of Google. Currently, Jeff Ullman is the Stanford W. Ascherman Professor of Computer Science (Emeritus) as well as CEO of Gradiance, a corporation which he founded to provide online homework and programming lab support for College students. Prof. Ullman’s research interests include database theory, database integration,
data mining, and education using the information infrastructure.

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