Exascale Advocates Stand on Nuclear Stockpiles

By Nicole Hemsoth

May 23, 2013

When it comes to investment in scientific research, the U.S. government tends to have an open ear for new ideas. However, in this time of tight budgets and heightened national security, federal coffers tend to have looser locks when there is a threat situation—whether that is global competitiveness or the safety and security of the nation.

According to a group of leading voices in high performance computing who gathered before yesterday’s U.S. Subcommittee on Energy, all of these national commodities are at stake without sustained investment in exascale systems.

While exascale funding hearings are nothing new, yesterday’s appeal struck a different chord, harmonizing with the urgency of ensuring U.S. nuclear capabilities—a note that has been resonating in headlines lately.

Instead of pitching the “big science” projects that lack a direct call to action, the threat of enroaching dominance from China and others, internal security, continued economic viability, and even the ability to predict tornado paths (a top news item during yesterday’s hearings following a devastating F5 in Oklahoma) took center stage, pushing exascale into the light of a requirement versus another expensive scientific endeavor.

Dr. Roscoe Giles, Chairman of the Advanced Scientific Computing Advisory Committee; Dr. Rick Stevens, Associate Director for Computing, Environment and Life Sciences at Argonne; Dona Crawford, Associate Director for Computation at Lawrence Livermore; and Dr. Dan Reed, VP of Research and Economic Development at the University of Iowa, all weighed in on various, expected components of exascale’s future (architecture, power/cooling, memory, etc.) before ringing the urgency alarm.

The hearing’s purpose was to examine draft legislation as it relates to the Department of Energy’s goals to build an exascale system. While the scientific payload of exascale was an important topic, the real meat, particularly when the floor was opened for questions, was how exascale will fit into larger national security goals, including nuclear stockpile stewardship—a rather familiar subject in the context of historical HPC funding.

The government has a $465.59 million proposal for FY 2014 in their hands to fund the DOE’s Office of Science Advanced Scientific Computing Research program, which will help spearhead U.S exascale efforts. Additionally, the National Nuclear Security Administration (NNSA) is requesting a tick over $400 million for its Advanced Simulation and Computing programs, which will help the U.S. maintain the safety and viability of its nuclear weapons stockpile without active underground or small on-ground tests.

If the Advanced Simulation and Computing Program rings a bell, it’s because it was an original part of the initial DOE Stockpile Stewardship and Management plan, which took the dirt and grit out of the physical testing process of nukes and plugged the possibilities into supercomputers and new instruments instead. Since even the youngest nuclear devices in the U.S. shed are 20 years old, a lot of testing needs to be done to see how they will react under the stresses of aging in terms of stability and viability should the unfortunate need arise.

From the beginning, this Stewardship and associated Simulation and Computing program pulled in funding—breathing new life into research endeavors at a number of national labs, most notably Sandia, Lawrence Livermore and Los Alamos. It also kicked funds into the private technology sector by default. To avoid a tangent, take this redirect to an analysis of some of the program’s strengths and weaknesses in terms of the computational horsepower.

Using the arsenal of current tools, the NNSA continuously assesses each nuclear weapon to certify its reliability and to detect or anticipate any potential problems that may come about as a result of aging.  All weapon types in the U.S. nuclear stockpile require routine maintenance, periodic repair, replacement of limited life components, surveillance (a thorough examination of a weapon)—all tasks that Crawford and colleagues say require exaflop-capable resources.

In short, this convincing approach worked in the 1990s when modeling and simulation capabilities were increasing rapidly—but the question is whether or not even that call to action for exascale’s value will be enough to add the required $400 million-level of urgency. Combined, however, with the dramatic and timely issues of nuclear threats pointed at allies—not to mention our competitive stew has cooled on multiple industrial and economic fronts—this appeal might carry more weight than it would have even this time last year.

As Dona Crawford explained, it is now the use of exascale systems that represents the only way to truly understand how to make sure the U.S. nuclear stockpile is safe, secure and in top condition. The same argument that propelled a great deal of investment into tech companies back in the 1990s when the NNSA looked to simulations and supercomputing to carry the stewardship load.

“Computing is the integrating element of maintaining the safety, security and reliability of our nuclear weapons stockpile without returning to underground tests,” said Crawford. “By integrating element, I mean that right now we have old test data, above-ground small test data, a lot of theory and some new models,” but that these cannot be used effectively unless scientists have access to far higher-fidelity simulations.

Even without using exascale to ensure nuclear stockpile safety and security, the side effect of lagging investment is a dwindling of our competitive prowess.

When asked why the U.S. doesn’t look to more international collaboration to reach its exascale ambitions, Dr. Stevens said that this makes sense on the software level, especially since so many large-scale systems use the same open source packages that are then pushed out to the community. However, he argued that it would not be suitable for us to share resources on the hardware front, pointing to what might happen if we were to trust our secure operations to run on hardware built in China.

The competitive threat wasn’t difficult for the speakers to tease apart for the committee—they pointed to investments in China and Japan toward exascale, making it clear that these were not insignificant funding efforts.  

Dan Reed made the argument that we are facing an uncertain future in HPC as other nations are making critical investments in supercomputing, noting, “Global leadership isn’t a birthright.” Even if the nuclear stockpile can make do with its current level of petascale capabilities, winning a silver, bronze—or even no medal in the exascale race itself presents a bevy of potential problems.

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