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General Keynote - Prof. David A. Patterson

Last modified 2008-05-31 01:59

The Parallel Computing Landscape: A Berkeley View 2.0
Professor David A. Patterson
University of California at Berkeley, California, USA
Member, National Academy of Engineering
Member, National Academy of Sciences
Fellow of IEEE, ACM, and AAAS
Shared (with John Hennessy) the IEEE John von Neumann Medal

Date: July 14, 2008
Time: TBA
Location: Lance Burton Theater


    In December 2006 we published a broad survey of the issues for the whole field concerning the multicore/manycore sea change (see We view the ultimate goal as being able to productively create efficient and correct software that smoothly scales when the number of cores per chip doubles biennially. This talk covers the specific research agenda that a large group of us at Berkeley are going to follow (see

    To take a fresh approach to the longstanding parallel computing problem, our research agenda will be driven by compelling applications developed by domain experts. Historically, past efforts to resolve these challenges have often been driven "bottom-up" from the hardware, with applications an afterthought. We will focus on exciting new applications that need much more computing horsepower to run well rather than on legacy programs that already run well on today's computers. Our applications are in the areas of personal health, image retrieval, music, speech understanding, and browsers.

    The development of parallel software is the heart of the research agenda. The task will be divided into two layers: an efficiency layer that aims at low overhead for 10 percent of the best programmers, and a productivity layer for the rest of the programming community--including domain experts--that reuses the parallel software developed at the efficiency layer. Key to this approach is a layer of libraries and programming frameworks centered around the 13 computational bottlenecks ("dwarfs") that we identified in the Berkeley View report. We will also create a Composition and Coordination Language to make it easier to compose these components. Finally, we will rely on autotuning to map the software efficiently to a particular parallel computer. Past attempts have often relied on a single programming abstraction and language for everyone and on parallelizing compilers.

    The role of the operating systems and the architecture in this project is to support software and applications in achieving the ultimate goal, rather than the conventional approach of fixing the environment in which parallel software must survive. Examples include primitives like thin hypervisors and libraries for the operating system and hardware support for partitioning and fast barrier synchronization.

    We will prototype the hardware of the future using field programmable gate arrays (FPGAs), which we believe are fast enough to be interesting to parallel software researchers yet flexible enough to "tape out" new designs every day while being cheap enough that university researchers can afford to construct systems containing hundreds of processors. This prototyping infrastructure is called RAMP (Research Accelerator for Multiple Processors), which is being developed by a consortium of universities and companies (see

Academic Co-Sponsors

Computational Biology and Functional Genomics Laboratory, Harvard University, Cambridge, Massachusetts, USA

International Society of Intelligent Biological Medicine

Horvath Laboratory, University of California, Los Angeles (UCLA), USA
Minnesota Supercomputing Institute, University of Minnesota, USA
Functional Genomics Laboratory, University of Illinois at Urbana-Champaign, USA
BioMedical Informatics & Bio-Imaging Laboratory, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA
Intelligent Data Exploration and Analysis Laboratory, University of Texas at Austin, Austin, Texas, USA
Biomedical Cybernetics Laboratory, HST of Harvard University and MIT, USA
Center for the Bioinformatics and Computational Genomics, Georgia Institute of Technology, Atlanta, Georgia, USA
Harvard Statistical Genomics and Computational Laboratory, Harvard University, Cambridge, Massachusetts, USA
Bioinformatics & Computational Biology Program, George Mason University, Virginia, USA
Hawkeye Radiology Informatics, Department of Radiology, College of Medicine, University of Iowa, Iowa, USA
Medical Image HPC & Informatics Lab (MiHi Lab), University of Iowa, Iowa, USA
The University of North Dakota, Grand Forks, North Dakota, USA
PSU - Prince Sultan University, Saudi Arabia
Institute for Informatics Problems of the Russian Academy of Sciences, Moscow, Russia.
NEMO/European Union at Institute of Discrete Mathematics and Geometry, TU Vienna

Corporate Sponsors

Other Co-Sponsors

High Performance Computing for Nanotechnology (HPCNano)

International Technology Institute (ITI)



Hodges' Health


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