The Next Peak in HPC


National Center for Computational Sciences
Oak Ridge National Laboratory
Oak Ridge, TN, USA


Hybrid CPU+GPU architectures are a response to power limitations imposed by the end in the last decade of processor clock-rate scaling. This limitation continues to drive supercomputer architecture designs toward massively parallel, hierarchical, and/or hybrid systems, and we expect that, for the foreseeable future, large leadership computing systems will continue this trajectory in order to address science and engineering challenges for government, academia, and industry. Consistent with this trend, the U.S. Department of Energy’s (DOE) Oak Ridge Leadership Computing Facility (OLCF) has signed a contract with IBM to bring a next-generation supercomputer to the Oak Ridge National Laboratory (ORNL) in 2017. This new supercomputer, named Summit, will provide on science applications at least five times the performance of Titan, the OLCF’s current hybrid CPU+GPU leadership system, and become the next peak in leadership-class computing systems for open science. To deliver this new capability, IBM has formed a partnership with NVIDIA and Mellanox, all members of the OpenPOWER Foundation, and each will provide system components for Summit. In addition, OLCF will partner with eight application software development teams to jointly prepare their science applications for the Summit architecture, and carry out early science campaign to demonstrate the Summit’s new capabilities for science. These application-readiness partnerships, with support from the IBM/NVIDIA Center of Excellence at Oak Ridge, will exercise Summit’s programming models and harden its software tools. In order to meet DOE’s broad science and energy missions, DOE procurements continue to support diversity in architectures. And in this context, more mature programming environments, enabling performance portable software engineering, become a requirement for DOE supercomputing facilities. To prepare mission-critical scientific applications now and for the next generation systems, our center continues to advance open-standards and work closely with ecosystem partners to address needs of our users. These efforts will be outlined in this talk.


Tjerk Straatsma
Jim Rogers
Adam Simpson
Ashley Barker
Fernanda Foertter
Jack Wells

Speaker Bio

Jack C. Wells, Ph.D.
Director of Science
National Center for Computational Science
Oak Ridge National Laboratory

Jack Wells is the Director of Science for the National Center for Computational Sciences (NCCS) at Oak Ridge National Laboratory (ORNL). He is responsible for devising the strategy to ensure cost-effective, state-of-the-art scientific computing at the NCCS, which hosts the Department of Energy’s Oak Ridge Leadership Computing Facility (OLCF), a DOE Office of Science national user facility, and Titan, currently the faster supercomputer in the United States.

In ORNL’s Computing and Computational Sciences Directorate, Wells has previously lead both the Computational Materials Sciences group in the Computer Science and Mathematics Division and the Nanomaterials Theory Institute in the Center for Nanophase Materials Sciences. During an off-site assignment from 2006 to 2008, he served as a legislative fellow for U.S. Senator Lamar Alexander of Tennessee, providing information about high-performance computing, energy technology, and science, technology, engineering, and mathematics education policy issues.

Wells began his ORNL career in 1990 for resident research on his Ph.D. in Physics from Vanderbilt University.  Following a three-year postdoctoral fellowship at the Harvard-Smithsonian Center for Astrophysics, he returned to ORNL as a staff scientist in 1997 as a Wigner fellow.  Jack is an accomplished practitioner of computational physics and has been sponsored in his research by the Department of Energy’s Office of Basic Energy Sciences.

Jack has authored or co-authored over 70 scientific papers and edited 1 book, spanning nanoscience, materials science and engineering, nuclear and atomic physics computational science, and applied mathematics.


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