ORNL Unveils Summit Supercomputer

June 8, 2018

OAK RIDGE, Tenn., June 8, 2018 — The U.S. Department of Energy’s Oak Ridge National Laboratory today unveiled Summit as the world’s most powerful and smartest scientific supercomputer.

With a peak performance of 200,000 trillion calculations per second—or 200 petaflops, Summit will be eight times more powerful than ORNL’s previous top-ranked system, Titan. For certain scientific applications, Summit will also be capable of more than three billion billion mixed precision calculations per second, or 3.3 exaops. Summit will provide unprecedented computing power for research in energy, advanced materials and artificial intelligence (AI), among other domains, enabling scientific discoveries that were previously impractical or impossible.

“Today’s launch of the Summit supercomputer demonstrates the strength of American leadership in scientific innovation and technology development. It’s going to have a profound impact in energy research, scientific discovery, economic competitiveness and national security,” said Secretary of Energy Rick Perry. “I am truly excited by the potential of Summit, as it moves the nation one step closer to the goal of delivering an exascale supercomputing system by 2021. Summit will empower scientists to address a wide range of new challenges, accelerate discovery, spur innovation and above all, benefit the American people.”

The IBM AC922 system consists of 4,608 compute servers, each containing two 22-core IBM Power9 processors and six NVIDIA Tesla V100 graphics processing unit accelerators, interconnected with dual-rail Mellanox EDR 100Gb/s InfiniBand. Summit also possesses more than 10 petabytes of memory paired with fast, high-bandwidth pathways for efficient data movement. The combination of cutting-edge hardware and robust data subsystems marks an evolution of the hybrid CPU–GPU architecture successfully pioneered by the 27-petaflops Titan in 2012.

ORNL researchers have figured out how to harness the power and intelligence of Summit’s state-of-art architecture to successfully run the world’s first exascale scientific calculation. A team of scientists led by ORNL’s Dan Jacobson and Wayne Joubert has leveraged the intelligence of the machine to run a 1.88 exaops comparative genomics calculation relevant to research in bioenergy and human health. The mixed precision exaops calculation produced identical results to more time-consuming 64-bit calculations previously run on Titan.

“From its genesis 75 years ago, ORNL has a history and culture of solving large and difficult problems with national scope and impact,” ORNL Director Thomas Zacharia said. “ORNL scientists were among the scientific teams that achieved the first gigaflops calculations in 1988, the first teraflops calculations in 1998, the first petaflops calculations in 2008 and now the first exaops calculations in 2018. The pioneering research of ORNL scientists and engineers has played a pivotal role in our nation’s history and continues to shape our future. We look forward to welcoming the scientific user community to Summit as we pursue another 75 years of leadership in science.”

In addition to scientific modeling and simulation, Summit offers unparalleled opportunities for the integration of AI and scientific discovery, enabling researchers to apply techniques like machine learning and deep learning to problems in human health, high-energy physics, materials discovery and other areas. Summit allows DOE and ORNL to respond to the White House Artificial Intelligence for America initiative.

“Summit takes accelerated computing to the next level, with more computing power, more memory, an enormous high-performance file system and fast data paths to tie it all together. That means researchers will be able to get more accurate results faster,” said Jeff Nichols, ORNL associate laboratory director for computing and computational sciences. “Summit’s AI-optimized hardware also gives researchers an incredible platform for analyzing massive datasets and creating intelligent software to accelerate the pace of discovery.”

Summit moves the nation one step closer to the goal of developing and delivering a fully capable exascale computing ecosystem for broad scientific use by 2021.

Summit will be open to select projects this year while ORNL and IBM work through the acceptance process for the machine. In 2019, the bulk of access to the IBM system will go to research teams selected through DOE’s Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program.

In anticipation of Summit’s launch, researchers have been preparing applications for its next-generation architecture, with many ready to make effective use of the system on day one. Among the early science projects slated to run on Summit:

Astrophysics

Exploding stars, known as supernovas, supply researchers with clues related to how heavy elements—including the gold in jewelry and iron in blood—seeded the universe.

The highly scalable FLASH code models this process at multiple scales—from the nuclear level to the large-scale hydrodynamics of a star’s final moments. On Summit, FLASH will go much further than previously possible, simulating supernova scenarios several thousand times longer and tracking about 12 times more elements than past projects.

“It’s at least a hundred times more computation than we’ve been able to do on earlier machines,” said ORNL computational astrophysicist Bronson Messer. “The sheer size of Summit will allow us to make very high-resolution models.”

Materials

Developing the next generation of materials, including compounds for energy storage, conversion and production, depends on subatomic understanding of material behavior. QMCPACK, a quantum Monte Carlo application, simulates these interactions using first-principles calculations.

Up to now, researchers have only been able to simulate tens of atoms because of QMCPACK’s high computational cost. Summit, however, can support materials composed of hundreds of atoms, a jump that aids the search for a more practical superconductor—a material that can transmit electricity with no energy loss.

“Summit’s large, on-node memory is very important for increasing the range of complexity in materials and physical phenomena,” said ORNL staff scientist Paul Kent. “Additionally, the much more powerful nodes are really going to help us extend the range of our simulations.”

Cancer Surveillance

One of the keys to combating cancer is developing tools that can automatically extract, analyze and sort existing health data to reveal previously hidden relationships between disease factors such as genes, biological markers and environment. Paired with unstructured data such as text-based reports and medical images, machine learning algorithms scaled on Summit will help supply medical researchers with a comprehensive view of the U.S. cancer population at a level of detail typically obtained only for clinical trial patients.

This cancer surveillance project is part of the CANcer Distributed Learning Environment, or CANDLE, a joint initiative between DOE and the National Cancer Institute.

“Essentially, we are training computers to read documents and abstract information using large volumes of data,” ORNL researcher Gina Tourassi said. “Summit enables us to explore much more complex models in a time efficient way so we can identify the ones that are most effective.”

Systems Biology

Applying machine learning and AI to genetic and biomedical datasets offers the potential to accelerate understanding of human health and disease outcomes.

Using a mix of AI techniques on Summit, researchers will be able to identify patterns in the function, cooperation and evolution of human proteins and cellular systems. These patterns can collectively give rise to clinical phenotypes, observable traits of diseases such as Alzheimer’s, heart disease or addiction, and inform the drug discovery process.

Through a strategic partnership project between ORNL and the U.S. Department of Veterans Affairs, researchers are combining clinical and genomic data with machine learning and Summit’s advanced architecture to understand the genetic factors that contribute to conditions such as opioid addiction.

“The complexity of humans as a biological system is incredible,” said ORNL computational biologist Dan Jacobson. “Summit is enabling a whole new range of science that was simply not possible before it arrived.”

Summit is part of the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility located at ORNL. UT-Battelle manages ORNL for the Department of Energy’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. DOE’s Office of Science is working to address some of the most pressing challenges of our time. For more information, please visit http://science.energy.gov.


Source: ORNL

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!

Under The Wire: Nearly HPC News (June 13, 2024)

June 13, 2024

As managing editor of the major global HPC news source, the term "news fire hose" is often mentioned. The analogy is quite correct. In any given week, there are many interesting stories, and only a few ever become headli Read more…

Quantum Tech Sector Hiring Stays Soft

June 13, 2024

New job announcements in the quantum tech sector declined again last month, according to an Quantum Economic Development Consortium (QED-C) report issued last week. “Globally, the number of new, public postings for Qu Read more…

Labs Keep Supercomputers Alive for Ten Years as Vendors Pull Support Early

June 12, 2024

Laboratories are running supercomputers for much longer, beyond the typical lifespan, as vendors prematurely deprecate the hardware and stop providing support. A typical supercomputer lifecycle is about five to six years Read more…

MLPerf Training 4.0 – Nvidia Still King; Power and LLM Fine Tuning Added

June 12, 2024

There are really two stories packaged in the most recent MLPerf  Training 4.0 results, released today. The first, of course, is the results. Nvidia (currently king of accelerated computing) wins again, sweeping all nine Read more…

Highlights from GlobusWorld 2024: The Conference for Reimagining Research IT

June 11, 2024

The Globus user conference, now in its 22nd year, brought together over 180 researchers, system administrators, developers, and IT leaders from 55 top research computing centers, national labs, federal agencies, and univ Read more…

Nvidia Shipped 3.76 Million Data-center GPUs in 2023, According to Study

June 10, 2024

Nvidia had an explosive 2023 in data-center GPU shipments, which totaled roughly 3.76 million units, according to a study conducted by semiconductor analyst firm TechInsights. Nvidia's GPU shipments in 2023 grew by more Read more…

Under The Wire: Nearly HPC News (June 13, 2024)

June 13, 2024

As managing editor of the major global HPC news source, the term "news fire hose" is often mentioned. The analogy is quite correct. In any given week, there are Read more…

Labs Keep Supercomputers Alive for Ten Years as Vendors Pull Support Early

June 12, 2024

Laboratories are running supercomputers for much longer, beyond the typical lifespan, as vendors prematurely deprecate the hardware and stop providing support. Read more…

MLPerf Training 4.0 – Nvidia Still King; Power and LLM Fine Tuning Added

June 12, 2024

There are really two stories packaged in the most recent MLPerf  Training 4.0 results, released today. The first, of course, is the results. Nvidia (currently Read more…

Highlights from GlobusWorld 2024: The Conference for Reimagining Research IT

June 11, 2024

The Globus user conference, now in its 22nd year, brought together over 180 researchers, system administrators, developers, and IT leaders from 55 top research Read more…

Nvidia Shipped 3.76 Million Data-center GPUs in 2023, According to Study

June 10, 2024

Nvidia had an explosive 2023 in data-center GPU shipments, which totaled roughly 3.76 million units, according to a study conducted by semiconductor analyst fir Read more…

ASC24 Expert Perspective: Dongarra, Hoefler, Yong Lin

June 7, 2024

One of the great things about being at an ASC (Asia Supercomputer Community) cluster competition is getting the chance to interview various industry experts and Read more…

HPC and Climate: Coastal Hurricanes Around the World Are Intensifying Faster

June 6, 2024

Hurricanes are among the world's most destructive natural hazards. Their environment shapes their ability to deliver damage; conditions like warm ocean waters, Read more…

ASC24: The Battle, The Apps, and The Competitors

June 5, 2024

The ASC24 (Asia Supercomputer Community) Student Cluster Competition was one for the ages. More than 350 university teams worked for months in the preliminary competition to earn one of the 25 final competition slots. The winning teams... Read more…

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators and Atos' financial turmoil have the HPC market worried. If Atos goes under, HPE will be the only major option for building large-scale systems. Read more…

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…

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…

Everyone Except Nvidia Forms Ultra Accelerator Link (UALink) Consortium

May 30, 2024

Consider the GPU. An island of SIMD greatness that makes light work of matrix math. Originally designed to rapidly paint dots on a computer monitor, it was then 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…

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…

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…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top Read more…

Leading Solution Providers

Contributors

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…

The NASA Black Hole Plunge

May 7, 2024

We have all thought about it. No one has done it, but now, thanks to HPC, we see what it looks like. Hold on to your feet because NASA has released videos of wh Read more…

Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's l Read more…

Intel’s Next-gen Falcon Shores Coming Out in Late 2025 

April 30, 2024

It's a long wait for customers hanging on for Intel's next-generation GPU, Falcon Shores, which will be released in late 2025.  "Then we have a rich, a very Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to 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…

Intel Plans Falcon Shores 2 GPU Supercomputing Chip for 2026  

August 8, 2023

Intel is planning to onboard a new version of the Falcon Shores chip in 2026, which is code-named Falcon Shores 2. The new product was announced by CEO Pat Gel Read more…

How the Chip Industry is Helping a Battery Company

May 8, 2024

Chip companies, once seen as engineering pure plays, are now at the center of geopolitical intrigue. Chip manufacturing firms, especially TSMC and Intel, have b Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire