Ten Great Reasons to Build the 1.5 Exaflops Frontier

By John Russell

May 7, 2019

It’s perhaps obvious that the fundamental reason for building expensive exascale computers is to drive science and industry forward, realizing the resulting benefits will ripple through society. Helping to ensure that happens is the non-trivial task of the U.S. Exscale Computing Project (ECP) whose mission is to foster development of the exascale-ready software ecosystem including science applications required. At today’s announcement of plans to build the $600 million, 1.5 exaflops Frontier supercomputer at Oak Ridge National Laboratory, organizers also presented a glimpse into some of the science Frontier may tackle.

Amitava-Bhattacharjee, Princeton Plasma Lab

Project organizers asked ten ECP project leaders to describe what they hoped to accomplish with Frontier’s exascale power. One of them is Amitava Bhattacharjee of the Princeton Plasma Physics Laboratory and PI for ECP’s WDMApp (Whole Device Modeling of Magnetically Confined Fusion Plasma).

He noted, “A whole-device computer model can offer insights about the plasma processes that go on in the fusion device and predictions regarding the performance and optimization of next-step experimental facilities. Using Frontier, we will be able to add new capabilities to the whole-device model, including the effects of the plasma boundary, the effects of fusion products, the influence of sources of heating, and the superimposed engineering structure that would make a fusion reactor operate as a unit.”

The goal of delivering safe, abundant, cheap energy from fusion is just one of many challenges in which exascale computing’s power may prove decisive. That’s the hope and expectation.

Presented below are quotes from nine more ECP PIs on their expectations for putting Frontier to use. (For details of the machine itself, whose construction is being led by partners Cray and AMD, see HPCwire’s article today, Cray, AMD to Extend DOE’s Exascale Frontier, written by Tiffany Trader.)

Additive Manufacturing. John Turner, ORNL and PI for ExaAM (Transformative Additive Manufacturing), ECP: “The thing that’s really attractive about Frontier is the powerful nodes. Having fewer powerful nodes with a very tightly integrated set of CPUs and GPUs at the node-level gives us the ability to distribute hundreds or thousands of microstructure and property calculations on one or a few nodes across the machine. With Frontier, we’re going to be able to predict the microstructure and properties of an additively manufactured part at much higher fidelity and in many more locations within a part than we are able to even with the world’s current fastest supercomputers.”

Materials Science. Danny Perez, Los Alamos National Laboratory and PI for EXAALT (Molecular Dynamics at Exascale for Materials Science), ECP: “Studying materials at exascale could have a significant impact on our world, because materials show up everywhere in the economy. Using a combination of advanced methods and scalable codes on Frontier, we’ll be able to perform simulations with potential millionfold increases in our time scales. We’ll also be able to do one-to-one comparisons with experiments and make better predictions about the evolution of these systems.”

Jacqueline Chen, Sandia National Laboratory

Combustion Efficiency. Jacqueline Chen, Sandia National Laboratories and PI for Combustion-Pele, ECP: “Combustion systems are projected to dominate the energy marketplace for decades to come. One engine concept—a low-temperature, reactivity-controlled, compression ignition engine— has the potential to deliver groundbreaking efficiencies of up to 60 percent while reducing emissions. On Frontier, we anticipate using high-fidelity simulations with machine learning and A.I. to model the underlying processes of this promising engine.”

Cosmology. Salman Habib, Argonne National Laboratory and PI for ExaSky (Computing the Sky at Extreme Scales), ECP: “Exascale will enable cosmology simulations large enough to model the distribution of billions of galaxies but also fine-grained enough to compare to a range of ground- and satellite-based observations, such as cosmic microwave background measurements and radio, optical, and xray data sets. At the same time, Frontier’s AI-oriented technology will enable us to analyze data from simulations in ways we simply can’t today.”

Software Technology. Mike Heroux, Sandia National Laboratories and Director, Software Technology, ECP: “ECP Software Technology is excited to be a part of preparing the software stack for Frontier. We are already on our way, using Summit and Sierra as launching pads. Working with OLCF, Cray, and AMD, we look forward to providing the programming environments and tools, and math, data and visualization libraries that will unlock the potential of Frontier for producing the countless scientific achievements we expect from such a powerful system. We are privileged to be part of the effort.”

Andreas Kronfield, Fermilab

Quantum Physics. Andreas Kronfeld, Fermilab and PI for Lattice QCD, ECP: “Exascale computing will be essential to precisely illuminating phenomena that emerge from neutrino physics experiments and maintaining the superb cross talk that has existed between the quantitative and the qualitative sides of discoveries in particle and nuclear physics. We anticipate that Frontier will provide the compute power and, just as important, the architecture for computation we must have to do our complicated, difficult calculations.”

Energy Application. Tom Evans, ORNL and Technical Lead for the Energy Applications Focus Area, ECP: “We are approaching a revolution in how we can design and analyze materials. We can look and carefully characterize the electronic structure of fairly simple atoms and very simple molecules right now. But with exascale computing on Frontier, we’re trying to stretch that to molecules that consist of thousands of atoms. The more we understand about the electronic structure, the more we’re able to actually manufacture and use exotic materials for things like very small, high tensile strength materials and buildings to make them more energy efficient. At the end of the day, everything in some sense comes down to materials.”

Grand Challenges. Andrew Siegel, Argonne National Laboratory and Director of Application Development Director, ECP: “At the inception of the ECP project we asked researchers to imagine new frontiers in science and engineering enabled by exascale computing. With Frontier, we have the opportunity now to fully realize our original vision, solving grand challenge problems that lead to breakthroughs in areas of energy generation, materials design, earth and space sciences, and related fields of physics and engineering.”

Laser Research. Amedeo Perazzo, SLAC National Accelerator Laboratory and PI for ExaFEL, ECP: “Free-electron X-ray laser facilities, such as the Linac Coherent Light Source (LCLS) at the SLAC National Accelerator Laboratory, produce ultrafast pulses from which scientists take stop- action pictures of moving atoms and molecules for research in physics, chemistry, and biology. For example, LCLS will be able to reconstruct biological structures in unprecedented atomic detail under physiological conditions. We foresee that access to Frontier will enable the LCLS users to achieve not only higher resolution and significantly deeper scientific insight than are possible today but also a dramatically increased image reconstruction rate for the delivery of information in minutes rather than weeks.”

Visit the Frontier website to read Q&As with these and other scientists conducting high impact research and preparing next-generation DOE applications for exascale.

There will of course be many more projects seeking and obtaining time on Frontier. Through its Center for Accelerated Application Readiness (CAAR), the OLCF will partner with simulation, data-intensive,and machine learning application teams consisting of application core developers and OLCF staff members. “CAAR partnership project proposals, accepted now through June 8, will be evaluated by a computational and scientific review conducted by the OLCF. In addition to gauging the scientific merit and acceleration plan of each proposal, the committee will strive to select a mix of computational algorithms and programming approaches representing a broad range of scientific disciplines,” reports ECP.

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