OpenMPCon  next month aims to bring a stellar lineup of the latest industry gurus, users and developers together with the language designers. As such we have 3 keynotes along with two full day tutorial and a day and a half of talks. You cans see the first keynote, tutorial and the first of three talks here. I like to take this chance to describe the second of three keynotes by Professor William Tang of Princeton University.

A major challenge for supercomputing today is to demonstrate how advances in HPC technology
translate to accelerated progress in key application domains – especially with respect to reduction
in “time-to-solution” and also “energy to solution” of advanced codes that model complex physical
systems. In order to effectively address the extreme concurrency present in modern
supercomputing hardware, one of the most efficient algorithmic approaches has been to adopt
OpenMP to facilitate efficient multi-threading approaches. This presentation describes the
deployment of Open-MP-enabled scalable scientific software for extreme scale applications – with
focus on Fusion Energy Science as an illustrative application domain.
Computational advances in magnetic fusion energy research have produced particle-in-cell (PIC)
simulations of turbulent kinetic dynamics for which computer run-time and problem size scale very
well with the number of processors on massively parallel many-core supercomputers. For
example, the GTC-Princeton (GTC-P) code, which has been developed with a “co-design” focus,
has demonstrated the effective usage of the full power of current leadership class computational
platforms worldwide at the petascale and beyond to produce efficient nonlinear PIC simulations
that have advanced progress in understanding the complex nature of plasma turbulence and
confinement in fusion systems. Results have provided great encouragement for being able to
include increasingly realistic dynamics in extreme-scale computing campaigns with the goal of
enabling predictive simulations characterized by unprecedented physics realism needed to help
accelerate progress in delivering clean energy. In particular, OpenMP usage experience and
associated best practices in achieving these advances will be described.

Prof. William Tang of Princeton University’s Department of Astrophysical Science serves on the
Executive Board for the University’s interdisciplinary “Princeton Institute for Computational Science
and Engineering (PICSciE)” which he helped establish as Associate Director (2003-2009). He is
also a Principal Research Physicist at the Princeton Plasma Physics Laboratory [the DOE national
laboratory for Fusion Energy Research for which he served as Chief Scientist (1997-2009)] and
was recently appointed Distinguished Visiting Professor at the Shanghai Jiao Tong University’s
HPC Center and NVIDIA Center of Excellence. He is a Fellow of the American Physical Society
and has received the Chinese Institute of Engineers-USA Distinguished Achievement Award
(2005) and the HPC Innovation Excellence Award from the International Data Corporation (2013).
He is internationally recognized for expertise in the mathematical formalism as well as associated
computational applications dealing with electromagnetic kinetic plasma behavior in complex
geometries, and has an “h-index” or “impact factor” of more than 45 on the Web of Science,
including well over 7000 citations. Prof. Tang has taught for over 30 years at Princeton U. and has
supervised numerous Ph.D. students, including recipients of the Presidential Early Career Award
for Scientists and Engineers in 2000 and 2005.

Please consider attending by signing up here. In the mean time, we are looking for student and volunteers to help with the conference. Please connect with OpenMPCon if you wish to help.