Exascale Computing to Help Accelerate Drive for Clean Fusion Energy

By Jon Bashor, Lawrence Berkeley National Laboratory Computing Sciences

October 2, 2017

Editor’s note: One of the U.S. Exascale Computing Project’s mandates is to explain how exascale computing power will enhance scientific discovery and society broadly. This article from ECP not only examines the need for exascale computing power to advance research on fusion reactor design but it also highlights the potential for collaboration with industry partners who will require this kind of power.

For decades, scientists have struggled to create a clean, unlimited energy source here on Earth by recreating the conditions that drive our sun. Called a fusion reactor, the mechanism would use powerful magnetic fields to confine and compress gases four times as hot as our sun. By using the magnetic fields to squeeze the gases, the atoms would fuse and release more energy than was used to power the reactor. But to date, that has only worked in theory.

Achieving fusion energy production would benefit society by providing a power source that is non-polluting, renewable and using fuels such as the hydrogen isotopes found in seawater and boron isotopes found in minerals.

Early fusion research projects in the 1950s and ‘60s relied on building expensive magnetic devices, testing them and then building new ones and repeating the cycle. In the mid-1970s, fusion scientists began using powerful computers to simulate how the hot gases, called plasmas, would be heated, squeezed and fused to produce energy. It’s an extremely complex and difficult problem, one that some fusion researchers have likened to holding gelatin together with rubber bands.

Using supercomputers to model and simulate plasma behavior, scientists have made great strides toward building a working reactor. The next generation of supercomputers on the horizon, known as exascale systems, will bring the promise of fusion energy closer.

The best-known fusion reactor design is called a tokamak, in which a donut-shaped chamber is used to contain the hot gases, inside. Because the reactors are so expensive, only small-scale ones have been built. ITER, an international effort to build the largest-ever tokamak-in the south of France. The project, conceived in 1985, is now scheduled to have its first plasma experiments in 2025 and begin fusion experiments in 2035. The estimated cost is 14 billion euros, with the European Union and six other nations footing the bill.

Historically, fusion research around the world has been funded by governments due to the high cost and long-range nature of the work.

But in the Orange County foothills of Southern California, a private company is also pursuing fusion energy, but taking a far different path than that of ITER and other tokamaks. Tri Alpha Energy’s cylindrical reactor design is completely different in its design philosophy, geometry, fuels and method of heating the plasma, all built with a different funding model. Chief Science Officer Toshiki Tajima says their approach makes them mavericks in the fusion community.

But the one thing both ITER and similar projects and Tri Alpha Energy have consistently relied on is using high-performance computers to simulate conditions inside the reactor as they seek to overcome the challenges inherent in designing, building and operating a machine that will replicate the processes of the sun here on Earth.

As each generation of supercomputers has come online, fusion scientists have been able to study plasma conditions in greater detail, helping them understand how the plasma will behave, how it may lose energy and disrupt the reactions, and what can be done to create and maintain fusion. With exascale supercomputers that are 50 times more powerful than today’s top systems looming on the horizon, Tri Alpha Energy sees great possibilities in accelerating the development of their reactor design. Tajima is one of 18 members of the industry advisory council for the U.S. Department of Energy’s (DOE) Exascale Computing Project (ECP).

“We’re very excited by the promise of exascale computing – we are currently fund-raising for our next-generation machine, but we can build a simulated reactor using a very powerful computer, and for this we would certainly need exascale,” Tajima said. “This would help us accurately predict if our idea would work, and if it works as predicted, our investors would be encouraged to support construction of the real thing.”

The Tri Alpha Energy fusion model builds on the experience and expertise of Tajima and his longtime mentor, the late Norman Rostoker, a professor of physics at the University of California, Irvine (UCI). Tajima first met Rostoker as a graduate student, leaving Japan to study at Irvine in 1973. In addition to his work with TAE, Tajima holds the Norman Rostoker Chair in Applied Physics at UCI. In 1998, Rostoker co-founded TAE, which Tajima joined in 2011.

In it for the long run

It was also in the mid-1970s, that the U.S. Atomic Energy Commission, the forerunner of DOE, created a computing center to support magnetic fusion energy research, first with a cast-off computer from classified defense programs, but then with a series of ever-more capable supercomputers. From the outset, Tajima was an active user, and still remembers he was User No. 1100 at the Magnetic Fusion Energy Computer Center. The Control Data Corp. and Cray supercomputers were a big leap ahead of the IBM 360 he had been using.

“The behavior of plasma could not easily be predicted with computation back then and it was very hard to make any progress,” Tajima said. “I was one of the very early birds to foul up the machines. When the Cray-1 arrived, it was marvelous and I fell in love with it.”

At the time, the tokamak was seen as the hot design and most people in the field gravitated in this direction, Tajima said, and he followed. But after learning about plasma-driven accelerators under Professor Rostoker, in 1976 he went to UCLA to work with Prof. John Dawson. “He and I shared a vision of new accelerators and we began using large-scale computation in 1975, an area in which I wanted to learn more from him,” Tajima said.

As a result, the two men wrote a paper entitled “Laser Electron Accelerator,” which appeared in Physical Review Letters in 1979. The seminal paper explained how firing an intense electromagnetic pulse (or beam of particles) into a plasma can create a wake in the plasma and that electrons, and perhaps ions, trapped in this wake can be accelerated to very high energies.

TAE’s philosophy, built on Rostoker’s ideas, is to combine both accelerator and fusion plasma research. In a tokamak, the deuterium-tritium fuel needs to be heated and confined at an energy level of 10,000 eV (electron volts) for fusion to occur. The TAE reactor, however, needs to be 30 times hotter. In a tokamak, the same magnetic fields that confine the plasma also heat it to 3 billion degrees C. In the TAE machine, the energy will be injected using a particle accelerator. “A 100,000 eV beam is nothing for an accelerator,” Tajima said, pointing to the 1G eV BELLA device at DOE’s Lawrence Berkeley National Laboratory. “Using a beam-driven plasma is relatively easy but it may be counterintuitive that you can get higher energy with more stability — the more energetic the wake is, the more stable it becomes.”

But this approach is not without risk. With the tokamak, the magnetic fields protect the plasma, much like the exoskeleton of a beetle protects the insect’s innards, Tajima said. But the accelerator beam creates a kind of spine, which creates the plasma by its weak magnetic fields, a condition known as Reverse Field Configuration. One of Rostoker’s concerns was that the plasma would be too vulnerable to other forces in the early stages of its formation. However, in the 40-centimeter diameter cylindrical reactor, the beam forms a ring like a bicycle tire, and like a bicycle, the stability increases the faster the wheels spin.

“The stronger the beam is, the more stable the plasma becomes,” Tajima said. “This was the riskiest problem for us to solve, but in early 2000 we showed the plasma could survive and this reassured our investors. We call this approach of tackling the hardest problem first ‘fail fast’.”

Another advantage of TAE’s approach is that the main fuel, Boron-11, does not produce neutrons as a by-product; instead it produces three alpha particles, which is the basis of the company’s name. A tokamak, using hydrogen-isotope fuels, generates neutrons, which can penetrate and damage materials, including the superconducting magnets that confine the tokamak plasma. To prevent this, the tokamak reactor requires one-meter-thick shielding. Without the need to contain neutrons, the TAE reactor does not need heavy shielding. This also helps reduce construction costs.

Computation Critical to Future Progress

With his 40 years of experience using HPC to advance fusion energy, Tajima offers a long-term perspective, from the past decades to exascale systems in the early 2020s. As a principal investigator on the Numerical Tokamak project in the early 1990s, he has helped build much of the HPC ecosystem for fusion research.

At the early stage of modeling fusion behavior, the codes focus on the global plasma at very fast time scales. These codes, known as MHD codes (magnetohydrodynamics), are not as computationally “expensive,” meaning they do not require as many computing resources, and at TAE were run on in-house clusters.

The next step is to model the more minute part of the plasma instability, known as kinetic instability, which requires more sophisticated codes that can simulate the plasma in greater detail over longer time scales. Achieving this requires more sophisticated systems. Around 2008-09, TAE stabilized this stage of the problem using its own computing system and by working with university collaborators who have access to federally funded supercomputing centers, such as those supported by DOE. “Our computing became more demanding during this time,” Tajima said.

The third step, which TAE is now tackling, is to make a plasma that can “live” longer, which is known as the transport issue in the fusion community. “This is a very, very difficult problem and consumes large amounts of computing resources as it encompasses a different element of the plasma,” Tajima said, “and the plasma becomes much more complex.”

The problem involves three distinct functions:

  • The core of the field reverse configuration, which is where the plasma is at the highest temperature
  • The “scrape-off layer,” which is the protective outer layer of ash on the core and which Tajima likens to an onion’s skin
  • The “ash cans,” or diverters, that are at each end of the reactor. They remove the ash, or impurities, from the scrape-off layer, which can make the plasma muddy and cause it to behave improperly.

“The problem is that the three elements behave very, very differently in both the plasma physics as well as in other properties,” Tajima said. “For example, the diverters are facing the metallic walls so you have to understand the interaction of the cold plate metals and the out-rushing impurities. And those dynamics are totally different than the core which is very high temperature and very high energy and spinning around like a bicycle tire, and the scrape-off layer.”

These factors are all coupled to each other using very complex geometries and in order to see if the TAE approach is feasible, researchers need to simulate the entirety of the reactor in order to understand and eventually control the reactions.

“We will run a three-layered simulation of our fusion reactor on the computer, with the huge particle code, the transport code and the neural net on the simulation – that’s our vision and we will certainly need an exascale machine to do this,” Tajima said. “This will allow us to predict if our concept works or not in advance of building machine so that our investors’ funds are not wasted.”

The overall code will have three components. At the basic level will be a representative simulation of particles in each part of the plasma. The second layer will be the more abstract transport code, which tracks heat moving in and out of the plasma. But even on exascale systems, the transport code will not be able to run fast enough to keep up with real-time changes in the plasma. Instabilities which affect the heat transport in the plasma come and go in milliseconds.

“So, we need a third layer that will be an artificial neural net, which will be able to react in microseconds, which is a bit similar to a driverless auto, and will ‘learn’ how to control the bicycle tire-shaped plasma, Tajima said. This application will be run on top of transport code and it will observe experimental data and react appropriately to keep the simulation running.

“Doing this will certainly require exascale computing,” Tajima said. “Without it we will take up to 30 years to finish – and our investors cannot wait that long. This project has been independent of the government funding, so that our investors’ fund provided an independent, totally different path toward fusion. This could amount to a means of national security to provide an alternative solution to a problem as large as fusion energy. Society will also benefit from a clean source of energy and our exascale-driven reactor march will be a very good thing for the nation and the world.”

Advanced Accelerators are Pivotal

Both particle accelerators and fusion energy are technologies important to the nation’s scientific leadership, with research funded over many decades by the Department of Energy and its predecessor agencies.

Not only are particle accelerators a vital part of the DOE-supported infrastructure of discovery science and university research, they also have private-sector applications and a broad range of benefits to industry, security, energy, the environment and medicine.

Since Toshiki Tajima and John Dawson published their paper “Laser Electron Accelerator” in 1979, the idea of building smaller accelerators, with the length measure in meters instead of kilometers, has gained traction. In these new accelerators, particles “surf” in the plasma wake of injected particles, reaching very high energy levels in very short distances.

According to Jean-Luc Vay, a researcher at DOE’s Lawrence Berkeley National Laboratory, taking full advantage of accelerators’ societal benefits, game-changing improvements in the size and cost of accelerators are needed. Plasma-based particle accelerators stand apart in their potential for these improvements, according to Vay, and turning this from a promising technology into a mainstream scientific tool depends critically on high-performance, high-fidelity modeling of complex processes that develop over a wide range of space and time scales.

To help achieve this goal, Vay is leading a project called Exascale Modeling of Advanced Particle Accelerators as part of DOE’s Exascale Computing Project. This project supports the practical economic design of smaller, less-expensive plasma-based accelerators.

As Tri Alpha Energy pursues its goal of using a particle accelerator (though this accelerator is not related to wakefield accelerators) to achieve fusion energy, the company is also planning to apply its experience and expertise in accelerator research for medical applications. Not only will this effort produce returns for the company’s investors, but it should also help advance TAE’s understanding of accelerators and using them to create a fusion reactor.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Better Scientific Software: Turn Your Passion into Cash

September 13, 2019

Do you know your way around scientific software and programming? You think you can contribute to the community by making scientific software better? If so, then the Better Scientific Software (BSSW) organization wants yo Read more…

By Dan Olds

Google’s ML Compiler Initiative Advances

September 12, 2019

Machine learning models running on everything from cloud platforms to mobile phones are posing new challenges for developers faced with growing tool complexity. Google’s TensorFlow team unveiled an open-source machine Read more…

By George Leopold

HPC Perspectives with Dr. Seid Koric

September 12, 2019

Brendan McGinty, director of Industry for the National Center for Supercomputing Applications (NCSA), University of Illinois at Urbana-Champaign, kicks off the first in a series of pieces profiling leaders in high performance computing (HPC), writing for the... Read more…

By Brendan McGinty

AWS Solution Channel

A Guide to Discovering the Best AWS Instances and Configurations for Your HPC Workload

The flexibility and heterogeneity of HPC cloud services provide a welcome contrast to the constraints of on-premises HPC. Every HPC configuration is potentially accessible to any given workload in a well-resourced cloud HPC deployment, with vast scalability to spin up as much compute as that workload demands in any given moment. Read more…

HPE Extreme Performance Solutions

Intel FPGAs: More Than Just an Accelerator Card

FPGA (Field Programmable Gate Array) acceleration cards are not new, as they’ve been commercially available since 1984. Typically, the emphasis around FPGAs has centered on the fact that they’re programmable accelerators, and that they can truly offer workload specific hardware acceleration solutions without requiring custom silicon. Read more…

IBM Accelerated Insights

Building a Solid IA for Your AI

The journey to high performance precision medicine starts with designing and deploying a solid Information Architecture that addresses the spectrum of challenges from data and applications that need to be managed and orchestrated together to empower workloads from analytics to AI. Read more…

IDAS: ‘Automagic’ HPC With Training Wheels

September 12, 2019

High-performance computing (HPC) for research is notorious for having steep barriers to entry. For this reason, high-tech disciplines were early adopters, have used the most cycles and typically drove hardware and softwa Read more…

By Elizabeth Leake

IDAS: ‘Automagic’ HPC With Training Wheels

September 12, 2019

High-performance computing (HPC) for research is notorious for having steep barriers to entry. For this reason, high-tech disciplines were early adopters, have Read more…

By Elizabeth Leake

Univa Brings Cloud Automation to Slurm Users with Navops Launch 2.0

September 11, 2019

Univa, the company behind Grid Engine, announced today its HPC cloud-automation platform NavOps Launch will support the popular open-source workload scheduler Slurm. With the release of NavOps Launch 2.0, “Slurm users will have access to the same cloud automation capabilities... Read more…

By Tiffany Trader

When Dense Matrix Representations Beat Sparse

September 9, 2019

In our world filled with unintended consequences, it turns out that saving memory space to help deal with GPU limitations, knowing it introduces performance pen Read more…

By James Reinders

Eyes on the Prize: TACC’s Frontera Quickly Ramps up Science Agenda

September 9, 2019

Announced a year ago and officially launched a week ago, the Texas Advanced Computing Center’s Frontera – now the fastest academic supercomputer (~25 petefl Read more…

By John Russell

Quantum Roundup: IBM Goes to School, Delft Tackles Networking, Rigetti Updates

September 5, 2019

IBM today announced a new open source quantum ‘textbook’, a series of quantum education videos, and plans to expand its nascent quantum hackathon program. L Read more…

By John Russell

DARPA Looks to Propel Parallelism

September 4, 2019

As Moore’s law runs out of steam, new programming approaches are being pursued with the goal of greater hardware performance with less coding. The Defense Advanced Projects Research Agency is launching a new programming effort aimed at leveraging the benefits of massive distributed parallelism with less sweat. Read more…

By George Leopold

Fastest Academic Supercomputer Enters Full Production at TACC, Just in Time for Hurricane Season

September 3, 2019

Frontera, the NSF supercomputer installed at the Texas Advanced Computing Center (TACC) in June, passed its formal acceptance last week and is now officially la Read more…

By Tiffany Trader

MIT Prepares for Satori…and a New 2 Petaflops Computer Too

August 27, 2019

Sometime this fall, MIT will fire up Satori – an $11.6 million compute cluster donated by IBM and coinciding with the opening of the MIT Stephen A. Schwarzma Read more…

By John Russell

High Performance (Potato) Chips

May 5, 2006

In this article, we focus on how Procter & Gamble is using high performance computing to create some common, everyday supermarket products. Tom Lange, a 27-year veteran of the company, tells us how P&G models products, processes and production systems for the betterment of consumer package goods. Read more…

By Michael Feldman

Supercomputer-Powered AI Tackles a Key Fusion Energy Challenge

August 7, 2019

Fusion energy is the Holy Grail of the energy world: low-radioactivity, low-waste, zero-carbon, high-output nuclear power that can run on hydrogen or lithium. T Read more…

By Oliver Peckham

AMD Verifies Its Largest 7nm Chip Design in Ten Hours

June 5, 2019

AMD announced last week that its engineers had successfully executed the first physical verification of its largest 7nm chip design – in just ten hours. The AMD Radeon Instinct Vega20 – which boasts 13.2 billion transistors – was tested using a TSMC-certified Calibre nmDRC software platform from Mentor. Read more…

By Oliver Peckham

TSMC and Samsung Moving to 5nm; Whither Moore’s Law?

June 12, 2019

With reports that Taiwan Semiconductor Manufacturing Co. (TMSC) and Samsung are moving quickly to 5nm manufacturing, it’s a good time to again ponder whither goes the venerable Moore’s law. Shrinking feature size has of course been the primary hallmark of achieving Moore’s law... Read more…

By John Russell

DARPA Looks to Propel Parallelism

September 4, 2019

As Moore’s law runs out of steam, new programming approaches are being pursued with the goal of greater hardware performance with less coding. The Defense Advanced Projects Research Agency is launching a new programming effort aimed at leveraging the benefits of massive distributed parallelism with less sweat. Read more…

By George Leopold

Cray Wins NNSA-Livermore ‘El Capitan’ Exascale Contract

August 13, 2019

Cray has won the bid to build the first exascale supercomputer for the National Nuclear Security Administration (NNSA) and Lawrence Livermore National Laborator Read more…

By Tiffany Trader

AMD Launches Epyc Rome, First 7nm CPU

August 8, 2019

From a gala event at the Palace of Fine Arts in San Francisco yesterday (Aug. 7), AMD launched its second-generation Epyc Rome x86 chips, based on its 7nm proce Read more…

By Tiffany Trader

Nvidia Embraces Arm, Declares Intent to Accelerate All CPU Architectures

June 17, 2019

As the Top500 list was being announced at ISC in Frankfurt today with an upgraded petascale Arm supercomputer in the top third of the list, Nvidia announced its Read more…

By Tiffany Trader

Leading Solution Providers

ISC 2019 Virtual Booth Video Tour

CRAY
CRAY
DDN
DDN
DELL EMC
DELL EMC
GOOGLE
GOOGLE
ONE STOP SYSTEMS
ONE STOP SYSTEMS
PANASAS
PANASAS
VERNE GLOBAL
VERNE GLOBAL

Ayar Labs to Demo Photonics Chiplet in FPGA Package at Hot Chips

August 19, 2019

Silicon startup Ayar Labs continues to gain momentum with its DARPA-backed optical chiplet technology that puts advanced electronics and optics on the same chip Read more…

By Tiffany Trader

Top500 Purely Petaflops; US Maintains Performance Lead

June 17, 2019

With the kick-off of the International Supercomputing Conference (ISC) in Frankfurt this morning, the 53rd Top500 list made its debut, and this one's for petafl Read more…

By Tiffany Trader

A Behind-the-Scenes Look at the Hardware That Powered the Black Hole Image

June 24, 2019

Two months ago, the first-ever image of a black hole took the internet by storm. A team of scientists took years to produce and verify the striking image – an Read more…

By Oliver Peckham

Cray – and the Cray Brand – to Be Positioned at Tip of HPE’s HPC Spear

May 22, 2019

More so than with most acquisitions of this kind, HPE’s purchase of Cray for $1.3 billion, announced last week, seems to have elements of that overused, often Read more…

By Doug Black and Tiffany Trader

Chinese Company Sugon Placed on US ‘Entity List’ After Strong Showing at International Supercomputing Conference

June 26, 2019

After more than a decade of advancing its supercomputing prowess, operating the world’s most powerful supercomputer from June 2013 to June 2018, China is keep Read more…

By Tiffany Trader

Qualcomm Invests in RISC-V Startup SiFive

June 7, 2019

Investors are zeroing in on the open standard RISC-V instruction set architecture and the processor intellectual property being developed by a batch of high-flying chip startups. Last fall, Esperanto Technologies announced a $58 million funding round. Read more…

By George Leopold

Intel Confirms Retreat on Omni-Path

August 1, 2019

Intel Corp.’s plans to make a big splash in the network fabric market for linking HPC and other workloads has apparently belly-flopped. The chipmaker confirmed to us the outlines of an earlier report by the website CRN that it has jettisoned plans for a second-generation version of its Omni-Path interconnect... Read more…

By Staff report

Intel Debuts Pohoiki Beach, Its 8M Neuron Neuromorphic Development System

July 17, 2019

Neuromorphic computing has received less fanfare of late than quantum computing whose mystery has captured public attention and which seems to have generated mo Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This