Date: Wednesday, 8 November 2006, 6:30 PM
Location: SAP LABS, Building D, 3410 Hillview Avenue,
Palo Alto, CA (Google
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Cost: Free and open to all who wish to attend, but membership is
only $10/year.
Topic
We are at the beginning of the multicore era. Computers will have increasingly many cores (processors), but there is still no good programming framework for these architectures, and thus no simple and unified way for machine learning to take advantage of the potential speedup afforded by multicore. We devise a certain "summation form," which allows conforming algorithms to be easily parallelized on multicore computers. We adapt Google's map-reduce paradigm to demonstrate this parallel speedup technique on a wide variety of machine learning and computer vision algorithms. We show that this programming framework is pragmatic and easy to learn for taking advantage of multicore parallelism. Our experimental results show basically linear speedup with an increasing number of processors.
About the Speaker
Dr.
Gary Rost Bradski is a Principle Engineer leading machine learning
and computer vision research for Intel Labs. He has a joint appointment
as consulting Professor at Stanford University. His basic goal is to
enable and accelerate AI internally and externally. Some external tools
he started for this are the Probabilistic
Network Library (PNL) and the
Open Source
Computer Vision Library (OpenCV) available open, for free
on Source Forge. The vision library is used around the world and has
become a notable part of the commercial Intel performance library (IPP)
products. A statistical machine learning library (MLL) is also available
at the OpenCV download site.
Gary received a B.S. degree from U.C. Berkeley and a Ph.D. in Cognitive
and Neural Systems (mathematical modeling of biological perception) in
May, 1994 from Boston University Center
for Adaptive Systems. Gary has
worked in the fields of: proximity security systems; medical electronics;
computerized EEG; and as a quantitative analyst at First Union's Derivatives
Trading Group. Gary also worked as a consultant to the medical electronics
industry (NeuroSoft) and in assembly line automation. He is on the advisory
board of some local startups in ID theft prevention.