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    Reevaluating Amdahl's Law in the Multicore Era
    Update time: 2009-08-11
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    Speaker: Prof. Xian-He Sun, Illinois Institute of Technology, USA
    Time: 10:00am—11:30am, Aug. 26, 2009 (Wednesday)
    Place: Room 446, 4th Floor, ICT
    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.
    Dr. Xian-He Sun is a professor and the chairman of the Department of Computer Science, and the director of the Scalable Computing Software laboratory at Illinois Institute of Technology (IIT). He 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.

    Center for Advanced Computing Research, ICT
    August, 2009


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