RCE - Super Computers Brock Palen

Steven G. Johnson is a Professor of Applied Mathematics and Physics at MIT. He works in the field of nanophotonics—electromagnetism in media structured on the wavelength scale, especially in the infrared and optical regimes—where he works on many aspects of the theory, design, and computational modeling of nanophotonic devices, both classical and quantum. He is coauthor of over 200 papers and over 25 patents, including the second edition of the textbook Photonic Crystals: Molding the Flow of Light. In addition to traditional publications, he distributes several widely used free-software packages for scientific computation, including the MPB and Meep electromagnetic simulation tools and the FFTW fast Fourier transform library (for which he received the 1999 J. H. Wilkinson Prize for Numerical Software).

http://math.mit.edu/~stevenj/

https://github.com/stevengj/meep
https://github.com/stevengj/mpb

Ardavan Oskooi is the Founder/CEO of Simpetus, a San Francisco based startup with a mission to propel simulations to the forefront of research and development in electromagnetics. Simpetus is a reference to our vision for simulations being an impetus for new discoveries and technologies. Ardavan received his Sc.D. from MIT where he worked with Professor Steven G. Johnson (thesis: Computation & Design for Nanophotonics) to develop Meep. Ardavan has published 13 first-author articles in peer-reviewed journals and a book "Advances in FDTD Computational Electrodynamics: Photonics and Nanotechnology". Ardavan has a master in Computation for Design and Optimization from MIT and completed his undergraduate studies, with honors, in Engineering Science at the University of Toronto. Prior to launching Simpetus, Ardavan worked as a postdoctoral researcher with Professors Susumu Noda at Kyoto University and Stephen R. Forrest at the University of Michigan on leveraging Meep to push the frontier of optoelectronic device design.

Company: www.simpetus.com

Dr. Ralph H. Castain is a Principal Engineer at Intel, where he focuses on the development of control system technologies for exascale computing systems. Dr. Castain received his B.S. degree in physics from Harvey Mudd College and multiple graduate level degrees (M.S. in solid-state physics, M.S.E.E. degree in robotics, and Ph.D. in nuclear physics) from Purdue University. He has served in government, academia, and industry for over 30 years as a contributing scientist and business leader in fields ranging from HPC to nuclear physics, particle accelerator design, remote sensing, autonomous pattern recognition, and decision analysis. He currently is the founder and leader of the PMIx community (https://pmix.github.io/pmix)

Brian Granger is an associate professor of physics and data science at
Cal Poly State University in San Luis Obispo, CA. His research focuses
on building open-source tools for interactive computing, data science,
and data visualization. Brian is a leader of the IPython project,
co-founder of Project Jupyter, co-founder of the Altair project for
statistical visualization, and an active contributor to a number of
other open-source projects focused on data science in Python. He is an
advisory board member of NumFOCUS and a faculty fellow of the Cal Poly
Center for Innovation and Entrepreneurship.

Dr. Bill Nitzberg is the CTO of PBS Works at Altair and “acting” community manager for the PBS Pro Open Source Project (www.pbspro.org). With over 25 years in the computer industry, spanning commercial software development to high-performance computing research, Dr. Nitzberg is an internationally recognized expert in parallel and distributed computing. Dr. Nitzberg served on the board of the Open Grid Forum, co-architected NASA’s Information Power Grid, edited the MPI-2 I/O standard, and has published numerous papers on distributed shared memory, parallel I/O, PC clustering, job scheduling, and cloud computing. When not focused on HPC, Bill tries to improve his running economy for his long-distance running adventures.

http://www.pbspro.org/

NetCDF is a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data.

Shifter is a prototype implementation that NERSC is developing and experimenting with as a scalable way of deploying containers in an HPC environment. It works by converting user or staff generated images in Docker, Virtual Machines, or CHOS (another method for delivering flexible environments) to a common format. This common format then provides a tunable point to allow images to be scalably distributed on the Cray supercomputers at NERSC. The user interface to shifter enables a user to select an image from their dockerhub account and then submit jobs which run entirely within the container.