ALCF, NCSA Supercomputers Generate Movies of the Universe

August 28, 2017

ARGONNE, Ill., Aug. 28, 2017 — If you have ever had to wait those agonizing minutes in front of a computer for a movie or large file to load, you’ll likely sympathize with the plight of cosmologists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory. But instead of watching TV dramas, they are trying to transfer, as fast and as accurately as possible, the huge amounts of data that make up movies of the universe – computationally demanding and highly intricate simulations of how our cosmos evolved after the Big Bang.

In a new approach to enable scientific breakthroughs, researchers linked together supercomputers at the Argonne Leadership Computing Facility (ALCF) and at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign (UI). This link enabled scientists to transfer massive amounts of data and to run two different types of demanding computations in a coordinated fashion – referred to technically as a workflow.

What distinguishes the new work from typical workflows is the scale of the computation, the associated data generation and transfer and the scale and complexity of the final analysis. Researchers also tapped the unique capabilities of each supercomputer: They performed cosmological simulations on the ALCF’s Mira supercomputer, and then sent huge quantities of data to UI’s Blue Waters, which is better suited to perform the required data analysis tasks because of its processing power and memory balance.

For cosmology, observations of the sky and computational simulations go hand in hand, as each informs the other. Cosmological surveys are becoming ever more complex as telescopes reach deeper into space and time, mapping out the distributions of galaxies at farther and farther distances, at earlier epochs of the evolution of the universe.

The very nature of cosmology precludes carrying out controlled lab experiments, so scientists rely instead on simulations to provide a unique way to create a virtual cosmological laboratory. “The simulations that we run are a backbone for the different kinds of science that can be done experimentally, such as the large-scale experiments at different telescope facilities around the world,” said Argonne cosmologist Katrin Heitmann. “We talk about building the ‘universe in the lab,’ and simulations are a huge component of that.”

Not just any computer is up to the immense challenge of generating and dealing with datasets that can exceed many petabytes a day, according to Heitmann. “You really need high-performance supercomputers that are capable of not only capturing the dynamics of trillions of different particles, but also doing exhaustive analysis on the simulated data,” she said. “And sometimes, it’s advantageous to run the simulation and do the analysis on different machines.”

Typically, cosmological simulations can only output a fraction of the frames of the computational movie as it is running because of data storage restrictions. In this case, Argonne sent every data frame to NCSA as soon it was generated, allowing Heitmann and her team to greatly reduce the storage demands on the ALCF file system. “You want to keep as much data around as possible,” Heitmann said. “In order to do that, you need a whole computational ecosystem to come together: the fast data transfer, having a good place to ultimately store that data and being able to automate the whole process.”

In particular, Argonne transferred the data produced immediately to Blue Waters for analysis. The first challenge was to set up the transfer to sustain the bandwidth of one petabyte per day.

Once Blue Waters performed the first pass of data analysis, it reduced the raw data – with high fidelity – into a manageable size. At that point, researchers sent the data to a distributed repository at Argonne, the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory and the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory. Cosmologists can access and further analyze the data through a system built by researchers in Argonne’s Mathematics and Computer Science Division in collaboration with Argonne’s High Energy Physics Division.

Argonne and University of Illinois built one such central repository on the Supercomputing ’16 conference exhibition floor in November 2016, with memory units supplied by DDN Storage. The data moved over 1,400 miles to the conference’s SciNet network. The link between the computers used high-speed networking through the Department of Energy’s Energy Science Network (ESnet). Researchers sought, in part, to take full advantage of the fast SciNET infrastructure to do real science; typically it is used for demonstrations of technology rather than solving real scientific problems.

“External data movement at high speeds significantly impacts a supercomputer’s performance,” said Brandon George, systems engineer at DDN Storage. “Our solution addresses that issue by building a self-contained data transfer node with its own high-performance storage that takes in a supercomputer’s results and the responsibility for subsequent data transfers of said results, leaving supercomputer resources free to do their work more efficiently.”

The full experiment ran successfully for 24 hours without interruption and led to a valuable new cosmological data set that Heitmann and other researchers started to analyze on the SC16 show floor.

Argonne senior computer scientist Franck Cappello, who led the effort, likened the software workflow that the team developed to accomplish these goals to an orchestra. In this “orchestra,” Cappello said, the software connects individual sections, or computational resources, to make a richer, more complex sound.

He added that his collaborators hope to improve the performance of the software to make the production and analysis of extreme-scale scientific data more accessible. “The SWIFT workflow environment and the Globus file transfer service were critical technologies to provide the effective and reliable orchestration and the communication performance that were required by the experiment,” Cappello said.

“The idea is to have data centers like we have for the commercial cloud. They will hold scientific data and will allow many more people to access and analyze this data, and develop a better understanding of what they’re investigating,” said Cappello, who also holds an affiliate position at NCSA and serves as director of the international Joint Laboratory on Extreme Scale Computing, based in Illinois. “In this case, the focus was cosmology and the universe. But this approach can aid scientists in other fields in reaching their data just as well.”

Argonne computer scientist Rajkumar Kettimuthu and David Wheeler, lead network engineer at NCSA, were instrumental in establishing the configuration that actually reached this performance. Maxine Brown from University of Illinois provided the Sage environment to display the analysis result at extreme resolution. Justin Wozniak from Argonne developed the whole workflow environment using SWIFT to orchestrate and perform all operations.

The Argonne Leadership Computing Facility, the Oak Ridge Leadership Computing Facility, the Energy Science Network and the National Energy Research Scientific Computing Center are DOE Office of Science User Facilities. Blue Waters is the largest leadership-class supercomputer funded by the National Science Foundation. Part of this work was funded by DOE’s Office of Science.

The National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign provides supercomputing and advanced digital resources for the nation’s science enterprise. At NCSA, University of Illinois faculty, staff, students, and collaborators from around the globe use advanced digital resources to address research grand challenges for the benefit of science and society. NCSA has been advancing one third of the Fortune 50 for more than 30 years by bringing industry, researchers, and students together to solve grand challenges at rapid speed and scale.

The National Science Foundation (NSF) is an independent federal agency that supports fundamental research and education across all fields of science and engineering. In fiscal year (FY) 2016, its budget is $7.5 billion. NSF funds reach all 50 states through grants to nearly 2,000 colleges, universities and other institutions. Each year, NSF receives more than 48,000 competitive proposals for funding and makes about 12,000 new funding awards. NSF also awards about $626 million in professional and service contracts yearly.

Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science.

The U.S. Department of Energy’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit the Office of Science website.


Source: Jared Sagoff and Austin Keating, Argonne National Laboratory

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