Sandia Labs News Releases

Exascale Computing Project awards $39.8 million for application development

ALBUQUERQUE, N.M. — Improved computer climate models of the Earth’s clouds and more accurate simulations of the combustion engine are goals for two projects led by Sandia National Laboratories that were funded in the first round of activities from the Department of Energy’s Exascale Computing Project (ECP).

The Exascale Computing Project ... Click on the thumbnail for a high-resolution image.

The multiyear mission of the Exascale Computing Project is to maximize the benefits of high-performance computing for U.S. economic competitiveness, national security and scientific discovery. (Image courtesy of the Department of Energy) Click on the thumbnail for a high-resolution image.

Sandia also will conduct research with other laboratories on three projects whose goals range from developing physics models for more efficient wind energy production to getting a better understanding of materials at the molecular level and simulating quantum mechanical effects in materials.

Total funding for 22 exascale computing projects chosen by the ECP is $39.8 million. Winning projects were selected for their significance to society and their ability to advance through exascale computing.

Researcher Jackie Chen at Sandia’s Livermore, California, site leads one of 15 fully funded projects: Transforming Combustion Science and Technology with Exascale Simulations. Sandia researcher Mark Taylor, chief computational scientist for the DOE’s Accelerated Climate Modeling for Energy executive council, will lead a project titled Cloud-Resolving Climate Modeling of the Earth’s Water Cycle.

Other projects supported by Sandia computer scientists, engineers and other researchers include Exascale Predictive Wind Plant Flow Physics Modeling, led by the National Renewable Energy Laboratory, with Oak Ridge National Laboratory and the University of Texas, Austin, as partners; Molecular Dynamics at the Exascale: Spanning the Accuracy, Length and Time Scales for Critical Problems in Materials Science, led by Los Alamos National Laboratory, with the University of Tennessee; and QMCPACK: A Framework for Predictive and Systematically Improvable Quantum‐Mechanics Based Simulations of Materials, led by Oak Ridge National Laboratory and five partners.

Exascale refers to high-performance computing systems capable of at least a billion calculations per second, which is 50 to 100 times faster than the most powerful supercomputers in use today.

All 15 fully funded projects and seven others that received seed funding involve partners from a total of 45 universities, national labs and private companies.

Bruce Hendrickson, director of Sandia’s Center for Computing Research, said “Sandia’s exascale applications will help lead the way to breakthroughs in science and applied energy while also leveraging Sandia’s advances in computer science, software and algorithms providing a technology ecosystem for the future of high-performance computing.”

Chen said the development of an exascale high-fidelity combustion simulation capability has tremendous potential scientific, technological and societal impact. “Due to the unrivaled energy density of liquid hydrocarbon fuels, combustion will continue to provide much of the world’s energy for at least the next 50 years,” she said. “Combustion needs to be understood and optimized to prevent further climate change, to reduce emissions harmful to human health and to ensure U.S. energy security.”

Taylor said his project team will develop a cloud-resolving Earth system model for multi-decade climate simulations that realistically treat  storms. “This will improve our ability to assess regional impacts of climate change on the water cycle that directly affect multiple sectors of the U.S. and global economies, especially agriculture and energy production,” he said.

The application efforts will help guide DOE’s development of a U.S. exascale ecosystem as part of President Barack Obama’s National Strategic Computing Initiative (NSCI). DOE, the Department of Defense and the National Science Foundation have been designated as NSCI lead agencies, and the ECP is the primary DOE contribution to the initiative.

“These application development awards are a major first step toward achieving mission-critical application readiness on the path to exascale,” said ECP director Paul Messina. “A key element of the ECP’s mission is to deliver breakthrough high-performance computing modeling and simulation solutions that confidently deliver insight and predict answers to the most critical U.S. problems and challenges in scientific discovery, energy assurance, economic competitiveness and national security. Application readiness is a strategic aspect of our project and foundational to the development of holistic, capable exascale computing environments.”

The ECP’s multiyear mission is to maximize the benefits of high-performance computing for U.S. economic competitiveness, national security and scientific discovery. In addition to applications, the ECP addresses hardware, software, platforms and workforce development needs critical to the effective development and deployment of future exascale systems.

The ECP will fund projects in energy security, economic security, scientific discovery, climate and environmental science and healthcare. It is led by six DOE national laboratories: the Office of Science’s Oak Ridge, Argonne and Lawrence Berkeley national labs, and National Nuclear Security Administration’s Lawrence Livermore, Los Alamos and Sandia national labs.

Developing a broad set of modeling and simulation applications that support the scientific, engineering and nuclear security programs of the DOE is one of four primary ECP goals. Its other major goals are to develop productive exascale computing (hardware and software); prepare two or more DOE facilities to house exascale machines by 2023; and maximize the benefits of high-performance computing  to U.S. science and commerce.

The full list of application development awards follows:

 Full funding:

  • Computing the Sky at Extreme Scales, Salman Habib (ANL) with LANL, LBNL
  • Exascale Deep Learning and Simulation Enabled Precision Medicine for Cancer, Rick Stevens (ANL) with LANL, LLNL, ORNL, NIH/NCI
  • Exascale Lattice Gauge Theory Opportunities and Requirements for Nuclear and High Energy Physics, Paul Mackenzie (FNAL) with BNL, TJNAF, Boston University, Columbia University, University of Utah, Indiana University, UIUC, Stony Brook, College of William & Mary
  • Molecular Dynamics at the Exascale: Spanning the Accuracy, Length and Time Scales for Critical Problems in Materials Science, Arthur Voter (LANL) with SNL, University of Tennessee
  • Exascale Modeling of Advanced Particle Accelerators, Jean-Luc Vay (LBNL) with LLNL, SLAC
  • An Exascale Subsurface Simulator of Coupled Flow, Transport, Reactions and Mechanics, Carl Steefel (LBNL) with LLNL, NETL
  • Exascale Predictive Wind Plant Flow Physics Modeling, Steve Hammond (NREL) with SNL, ORNL, University of Texas Austin
  • QMCPACK: A Framework for Predictive and Systematically Improvable QuantumMechanics Based Simulations of Materials, Paul Kent (ORNL) with ANL, LLNL, SNL, Stone Ridge Technology, Intel, Nvidia
  • Coupled Monte Carlo Neutronics and Fluid Flow Simulation of Small Modular Reactors, Thomas Evans (ORNL, PI) with ANL, INL, MIT
  • Transforming Additive Manufacturing through Exascale Simulation (TrAMEx), John Turner (ORNL) with LLNL, LANL, NIST
  • NWChemEx: Tackling Chemical, Materials and Biomolecular Challenges in the Exascale Era, T. H. Dunning, Jr. (PNNL), with Ames, ANL, BNL, LBNL, ORNL, PNNL, Virginia Tech
  • High-Fidelity Whole Device Modeling of Magnetically Confined Fusion Plasma, Amitava Bhattacharjee (PPPL) with ANL, ORNL, LLNL, Rutgers, UCLA, University of Colorado
  • Data Analytics at the Exascale for Free Electron Lasers, Amedeo Perazzo (SLAC) with LANL, LBNL, Stanford
  • Transforming Combustion Science and Technology with Exascale Simulations, Jackie Chen (SNL) with LBNL, NREL, ORNL, University of Connecticut
  • Cloud-Resolving Climate Modeling of the Earth’s Water Cycle, Mark Taylor (SNL) with ANL, LANL, LLNL, ORNL, PNNL, UCI, CSU

Seed funding:

  • Enabling GAMESS for Exascale Computing in Chemistry & Materials, Mark Gordon (Ames) with ANL, ORNL, Iowa State University, Georgia Tech, Old Dominion University, Australian National University, EP Analytics, NVIDIA
  • Multiscale Coupled Urban Systems, Charlie Catlett (ANL) with LBNL, NREL, ORNL, PNNL
  • Exascale Models of Stellar Explosions: Quintessential Multi-Physics Simulation, Daniel Kasen (LBNL), with ANL, ORNL, Stony Brook, University of Chicago
  • Exascale Solutions for Microbiome Analysis, Kathy Yelick (LBNL) with LANL, Joint Genome Institute
  • High Performance, Multidisciplinary Simulations for Regional Scale Seismic Hazard and Risk Assessments, David McCallen (LBNL) with LLNL, UC Davis, UC Berkeley
  • Performance Prediction of Multiphase Energy Conversion Devices with Discrete Element, Particle-in-Cell, and Two-Fluid Models (MFIX-Exa), Madhava Syamlal (NETL) with LBNL, University of Colorado
  • Optimizing Stochastic Grid Dynamics at Exascale, Henry Huang (PNNL) with ANL, NREL

Sandia National Laboratories is a multi-mission laboratory operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corp., for the U.S. Department of Energy’s National Nuclear Security Administration. With main facilities in Albuquerque, N.M., and Livermore, Calif., Sandia has major R&D responsibilities in national security, energy and environmental technologies and economic competitiveness.

Sandia news media contact: Neal Singer,  (505) 845-7078