Reevaluating Amdahl's Law in the Multicore Era

Speaker:	Professor Xian-He SUN
		Department of Computer Science
		Illinois Institute of Technology
		USA

Title:		"Reevaluating Amdahl's Law in the Multicore Era"

Date:		Tuesday, 9 June 2009

Time:		11:00am to 12 noon

Venue:		Room 1505 (near lifts 25/26), HKUST


ABSTRACT:

Multicore architecture has become the trend of high performance
processors. While it is generally accepted that we have entered the
multicore era, concerns exist on when or will moving into the manycore
stage. Recently, Hill and Marty presented a pessimistic view of multicore
scalability, citing Amdahl's law and the memory-wall problem. Technology
is available, but major vendors are hesitant in making processors that
have a large number of cores. This is a very interesting phenomenon, where
history seems to repeat itself on the scalability debate of parallel
processing that occurred 20 years ago. In this introductory keynote talk
we first review the history and concepts of scalable computing, and review
the current technologies and the memory-wall problem. We then use the same
hardware cost model of multicore chips used by Hill and Marty to introduce
two performance models from the scalable computing point of view. These
models show that there is no inherent, immovable upper bound on the
scalability of multicore architectures. Finally, we conclude with proposed
solutions to the memory-wall problem to make the potential scalability of
multicore reachable in practice.


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Biography:

Dr. Xian-He Sun is a professor of computer science and the director of the
Scalable Computing Software laboratory at Illinois Institute of Technology
(IIT), and is a guest faculty in the Mathematics and Computer Science
Division and Computing Division at the Argonne and Fermi National
Laboratory, respectively. Before joining IIT, he worked at DoE Ames
National Laboratory, at ICASE, NASA Langley Research Center, at Louisiana
State University, Baton Rouge, and was an ASEE fellow at Navy Research
Laboratories. Dr. Sun's research interests include parallel and
distributed processing, high-end computing, software systems, and
performance evaluation.