Hello,
Please join the eScience Institute Wednesday, February 13, 4:00 pm in EEB-303. Refreshments will be provided.
Gary M. Johnson (Computational Science Solutions)
Dr. Johnson specializes in: management of high performance computing, applied mathematics, and computational science research activities; advocacy, development, and management of high performance computing centers; development of national science and technology policy; and creation of education and research programs in computational engineering and science.
He has worked in Academia, Industry and Government. He has held full professorships at Colorado State University and George Mason University, been a researcher at United Technologies Research Center, and worked for the Department of Defense, NASA, and the Department of Energy.
He is a graduate of the U.S. Air Force Academy; holds advanced degrees from Caltech and the von Karman Institute; and has a Ph.D. in applied sciences from the University of Brussels.
Waiting for Exascale
By current estimates, we’re about a decade away from having exascale computing capability. That’s a pretty long time – especially in our world of HPC. What will the world be like in 2023? What form will exascale computing take when it’s real? These are difficult questions to answer. Never before has the HPC community focused so intensely on a machine so far beyond its grasp. Nevertheless, stalwart cadres around the globe are drafting strategies, plans, and roadmaps to get from here to exascale. So, what about the rest of us? Are there useful things we could do while waiting – or instead of waiting – for exascale? Perhaps there are. In this talk we’ll take a look at a few possibilities, including:
· Education
· eScience
· Big Data
· Broad HPC Deployment
· Computing in Industry
· Public Engagement
· Infrastructure Development and Build Out
· Success Metrics
Exascale computing may be a decade away, but there’s a lot to accomplish to be ready to exploit it. We’ll explore a few options here. We make no claim that these constitute the right agenda for the coming decade – nor do we suggest that we’ve given an exhaustive to-do list. Our intention is rather to open the conversation about what we should do while “waiting” for exascale.
So, come to the talk and let us know what you think.
Upcoming Seminars:
* March 13, 4 PM (EE303)
Carlos Guestrin (UW)
GraphLab: Making Fast Machine Learning on Big Data Accessible to Data Scientists
* April 11, 4 PM (EE303)
Barry Wark (Physion Consulting)
TBD
* May 1, 4 PM (EE303)
Jeff Gardner (UW)
Simulating the Universe on Google’s Exacycle Platform
* May 13, 4 PM (EE303)
Fernando Perez (Berkeley)
TBD