Fueling Innovations

Tuesday Keynote 2019

John Shalf John Shalf

Department Head for Computer Science, Lawrence Berkeley National Laboratory


(Tuesday, June 18)

Moore’s Law is a techno-economic model that has enabled the Information Technology (IT) industry to nearly double the performance and functionality of digital electronics roughly every two years within a fixed cost, power and area. Within a decade, the technological underpinnings for the process Gordon Moore described will come to an end as lithography gets down to atomic scale. At that point, it will be feasible to create lithographically produced devices with characteristic dimensions in the 3nm5nm range. This range corresponds to a dozen or fewer Si atoms across critical device features and will therefore be a practical limit for controlling charge in a classical sense. The classical technological driver that has underpinned Moore’s law for the past 50 years is already failing and is anticipated to flatten by 2025. This talk provides an updated view of what a 2021-2023 system might look like and the challenges ahead, based on our most recent understanding of technology roadmaps. It also will discuss the tapering of historical improvements in lithography, and how it affects options available to continue scaling of successors to the first exascale machine. 


John Shalf is Department Head for Computer Science at Lawrence Berkeley National Laboratory, and recently was deputy director of Hardware Technology for the DOE Exascale Computing Project. Shalf is a coauthor of over 80 publications in the field of parallel computing software and HPC technology, including three best papers and the widely cited report “The Landscape of Parallel Computing Research: A View from Berkeley” (with David Patterson and others). He also coauthored the 2008 “ExaScale Software Study: Software Challenges in Extreme Scale Systems,” which set the Defense Advanced Research Project Agency’s (DARPA’s) information technology research investment strategy.  Prior to coming to Berkeley Laboratory, John worked at the National Center for Supercomputing Applications and the Max Planck Institute for Gravitation Physics/Albert Einstein Institute (AEI) where he was was co-creator of the Cactus Computational Toolkit.


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