Invited Speakers
Keynote – Douglas Kothe, Oak Ridge National Laboratory
– Tuesday, May 9, 2017
What are the Opportunities and Challenges for a new Class of Exascale Applications? What Challenge Problems can these Applications Address through Modeling and Simulation & Data Analytic Computing Solutions?
Abstract: The Department of Energy’s (DOE) Exascale Computing Project (ECP) is a partnership between the DOE Office of Science and the National Nuclear Security Administration. Its mission is to transform today’s high performance computing (HPC) ecosystem by executing a multi-faceted plan: developing mission critical applications of unprecedented complexity; supporting U.S. national security initiatives; partnering with the U.S. HPC industry to develop exascale computer architectures; collaborating with U.S. software vendors to develop a software stack that is both exascale-capable and usable on U.S. industrial and academic scale systems, and training the next-generation workforce of computer and computational scientists, engineers, mathematicians, and data scientists. The ECP aims to accelerate delivery of a capable exascale computing ecosystem that will enable breakthrough modeling and simulation (M&S) and data analytic computing (DAC) solutions to the most critical challenges in scientific research, energy assurance, economic competitiveness, and national security.
The computer and computational science and engineering communities in the public, private, and government sectors have been arguably thinking about exascale-class modeling and simulation technologies and capabilities for almost a decade. With exascale platforms becoming more certain and finally within sight, application developers and users must “get real” now to adequately take advantage of this opportunity. The hardware and software technologies currently envisioned in exascale platforms will present new challenges for application developers that could be disruptive relative to current approaches. New algorithms, for example, that communicate infrequently and store very little, may be critical for applications to move forward or even “hold pace”. Hybrid node architectures with hierarchical memory and compute technologies will likely be the norm, and applications may face comprehensive restructuring to exploit more appropriate task-based programming models and new data structures.
Given these challenges, tremendous opportunity nevertheless exists for science-based computational applications that can deliver, through effective exploitation of exascale HPC technology, breakthrough M&S and DAC solutions that yield high-confidence insights and answers to the nation’s most critical problems and challenges in scientific discovery, energy assurance, economic competitiveness, and national security. While reflecting on some of my own person R&D experiences, I will survey these application opportunities, where I will also touch upon challenges, decadal challenge problems, and prospective outcomes and impact.
Bio: Douglas B. Kothe (Doug) has over three decades of experience in conducting and leading applied R&D in computational applications designed to simulate complexphysical phenomena in the energy, defense, and manufacturing sectors. Doug is currently the Deputy Associate Laboratory Director of the Computing and Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL). Prior positions for Doug at ORNL, where he has been since 2006, were Director of the Consortium for Advanced Simulation of Light Water Reactors, DOE’s first Energy Innovation Hub (2010-2015), and Director of Science at the National Center for Computational Sciences (2006-2010).
Before coming to ORNL, Doug spent 20 years at Los Alamos National Laboratory, where he held a number of technical and line and program management positions, with a common theme being the development and application of modeling and simulation technologies targeting multi-physics phenomena characterized in part by the presence of compressible or incompressible interfacial fluid flow. Doug also spent one year at Lawrence Livermore National Laboratory in the late 1980s as a physicist in defense sciences.
Doug holds a Bachelor in Science in Chemical Engineering from the University of Missouri – Columbia (1983) and a Masters in Science (1986) and Doctor of Philosophy (1987) in Nuclear Engineering from Purdue University.
Invited Talk – Perspectives on HPC and Enterprise High Performance Data Analytics, Arno Kolster, Providentia Worldwide
– Wednesday, May 10, 2017
Abstract: Mr. Kolster will present his experience of blending HPC and enterprise architectures to solve real-time, web-scale analytics problems and discuss the need to bridge the gap between HPC and enterprise. His unique perspective illustrates the need for enterprise to embrace HPC technologies and vice versa.
Bio: Arno was born in The Netherlands and grew up in Canada where he received a degree in Computer Science from The University Of Calgary. Currently residing in San Francisco, his main career focus over the past 30 years has been database architecture, database administration and operations architecture for industries that include oil and gas, emergency services, finance and until recently, 14 years at PayPal. His extensive knowledge of relational databases has expanded to include new database technologies such as NoSQL and graph databases. An interest in HPC and technical computing came about as a result of finding solutions to solving real time data analytics across distributed systems at web scale. Arno and his colleague, Ryan Quick, have received IDC Innovation Excellence Awards at both Super-Computing 2012 and 2104 as well as numerous HPC Wire Reader’s Choice Awards. He’s been invited to speak domestically and internationally on HPC and its deployment at PayPal. He is co-founder of independent consulting firm Providentia Worldwide.
