Princeton’s New Supercomputer to Accelerate Scientific Discovery in Fusion Research

October 8, 2019

Oct. 8, 2019 — A ribbon-cutting ceremony in Princeton’s High-Performance Computing Research Center on Sept. 30 kicked off the University’s official launch of its newest supercomputer, called Traverse, which joins four other distinct computing clusters available to the university research community.

“We are delighted to unveil Traverse, our new Department of Energy (DOE) ‘Leadership Class’ compatible computing cluster,” said David McComas, vice president for the Princeton Plasma Physics Laboratory (PPPL) and professor of astrophysical sciences. “This is an important milestone in Princeton University’s increased collaboration with the DOE in support of basic plasma physics and the U.S. fusion energy mission.”

Shown at Princeton’s Sept. 30 ribbon-cutting for the Traverse supercomputer are, from left to right: Craig Ferguson, deputy director for operations and chief operating officer at the Princeton Plasma Physics Laboratory (PPPL); Steven Cowley, director of PPPL; David McComas, Princeton University’s vice president for PPPL; Chelle Reno, Princeton University’s assistant vice president for operations for PPPL; and Jay Dominick, Princeton University’s vice president for information technology and chief information officer. Image courtesy of Denise Applewhite, Office of Communications, Princeton University.

Traverse is a 1.4 petaflop High-Performance Computing (HPC) cluster that shares the same Graphics Processing Unit (GPU) and Central Processing Unit (CPU) architecture as the supercomputers at Oak Ridge National Laboratory (ORNL) and Lawrence Livermore National Laboratory. Traverse is currently one of the largest systems at Princeton and in the top 500 systems in the world.

Curt Hillegas, associate CIO, Research Computing, Office of Information Technology and the Princeton Institute for Computational Science and Engineering (PICSciE) and a member of the PPPL advisory board who led the project to purchase and install the cluster, said: “Traverse is a mini version of ORNL’s Summit, thereby providing a stepping stone for the research community to one of the world’s fastest supercomputers. Getting experience using Traverse will allow our research groups to adapt their codes, so they can use the current leadership-class machines and be best prepared for the new exascale systems — capable of at least one exaFLOPS, or a billion billion calculations per second — expected to come online in the upcoming two years.”

Exascale speeds are expected to help fusion researchers finally clear the remaining hurdles in the development of safe and sustainable fusion energy. “At that scale we will be able to simulate and optimize fusion reactors, speeding the deployment of fusion energy in the global battle against climate change,” explained Steven Cowley, PPPL director. “We are very grateful to the University for this marvelous facility.”

Plasma, the hot ionized gas that fuels fusion reactions, must be heated to very high temperatures for the particles to fuse and release their energy. The focus of much fusion research is preventing the swings in density and temperature that cause instabilities such as plasma disruptions, edge localized modes and energetic-particle driven modes. Machine learning (ML) techniques are helping researchers create better models for rapid control and containment of plasma.

C.S. Chang, who heads the Center for High-fidelity Boundary Plasma Simulation at PPPL, said: “Artificial intelligence (AI) and machine learning techniques could be a game-changer. Due to the complicated nonlinear physics involved in these problems, using a supercomputer became a necessity for theoretical understanding. PPPL scientists will use Traverse to attack many of these problems in experiments, to collaborate with domestic and international researchers, and to help predict plasma performance in ITER, the international plasma research project using the world’s largest magnetic fusion device, or tokamak.”

The AI advantages for scientific discovery are numerous, explained Chang. The hope is that equations will be solved much faster without going through traditional time-consuming numerical processes; experimental and theoretical data will be used to formulate simple equations that govern the physics processes; and the plasma will be controlled almost instantaneously, in millisecond time-frames too fast for human intervention.

“A GPU-dominated computer such as Traverse is ideal for such AI/ML studies,” said Chang. “Solving these, and other important, physics and AI/ML problems on Traverse will greatly enhance the capabilities of graduate students, postdoctoral scientists and researchers, and their ability to advance these highly impactful areas in the world fusion and computational science research.”

“Traverse is a major initiative in the University-DOE partnership,” McComas said. “Princeton and the U.S. Department of Energy have a long-standing commitment to the shared missions of fundamental research, world-leading education and fusion as a safe energy source. With the launch of Traverse, we look forward to even stronger connections between the University, PPPL and the DOE, and to accelerating leading-edge research needed to make fusion an abundant, safe and sustainable energy source for the U.S. and humanity.”


Subscribe to HPCwire's Weekly Update!

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

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire