Berkeley Lab to Lead Two DOE Exascale Computing Proposals, Support Four Others

September 7, 2016

BERKELEY, Calif., Sept. 7 — Scientists at the Department of Energy’s (DOE) Lawrence Berkeley National Laboratory (Berkeley Lab) will lead or play key roles in developing 11 critical research applications for next-generation supercomputers as part of DOE’s Exascale Computing Project (ECP).

The ECP announced Sept. 7 that it has selected 15 application development proposals for full funding—of which Berkeley Lab will lead two and support four others—and seven proposals for “seed” funding, three of which will be led by Berkeley Lab, which will also support two others.

Exascale refers to high-performance computing systems capable of at least a billion billion calculations per second, or 50 to 100 times faster than the nation’s most powerful supercomputers in use today. The projects target advanced modeling and simulation solutions to specific challenges supporting key DOE missions in science, clean energy and national security. Since designing an exascale computer will require a significant change from current supercomputer architectures, scientific applications that run on today’s systems will also need to be reconfigured to take advantage of exascale systems.

The ECP’s multi-year mission is to maximize the benefits of high performance computing (HPC) for U.S. economic competitiveness, national security and scientific discovery. In addition to applications, the DOE project addresses hardware, software, platforms and workforce development needs critical to the effective development and deployment of future exascale systems. The ECP is sponsored by the DOE Office of Science and the National Nuclear Security Administration.

Berkeley Lab has provided high performance computing resources to scientists since the 1960s and is home to DOE’s National Energy Research Scientific Computing Center (NERSC), a user facility funded by DOE’s Office of Science and supporting 6,000 researchers at national labs, universities and industry. The Lab’s Computational Research Division also has extensive experience in developing scientific applications and mathematical tools for advancing research using supercomputers.

“These awards reflect our extensive experience and expertise in computational science across a wide range of disciplines, including accelerator design, subsurface flows, cosmology, combustion, chemistry,” said Kathy Yelick, Associate Laboratory Director for Computing Sciences. “Our applied mathematics and computer science expertise will be needed to develop applications tailored to exascale systems, and has also opened up a new set of high end simulation and data analytics applications in bioinformatics, seismology, carbon capture and urban systems modeling.”

Berkeley Lab is already paving the way for critical science applications to be ready for exascale computing. In 2104 NERSC launched the NERSC Exascale Science Applications Program (NESAP), a collaborative effort in which NERSC works closely with code teams and library and tools developers to prepare for the NERSC’s newest supercomputer, Cori, based on Intel’s newest Xeon Phi processor with 68 cores per processor. Additionally, applied mathematicians have developed Adaptive Mesh Refinement (AMR) libraries that are being used in many exascale applications.

The fully funded four-year ECP projects led by Berkeley Lab scientists are:

“An Exascale Subsurface Simulator of Coupled Flow, Transport, Reactions and Mechanics” will be led by Carl Steefel of the Earth and Environmental Sciences Area and David Trebotich of the Computational

David Trebotich (left) and Carl Steefel, leaders of the exascale subsurface modeling project, pose with Cori, NERSC's newest supercomputer. Photo by Marilyn Chung.
David Trebotich (left) and Carl Steefel, leaders of the exascale subsurface modeling project, pose with Cori, NERSC’s newest supercomputer. Photo by Marilyn Chung.

Research Division. The project will support application code development for a sound understanding of and predictive capability for the interacting hydrological, chemical, thermal, and mechanical processes in subsurface formations for improved energy extraction and safely storing CO2 and other wastes. Lawrence Livermore National Laboratory and the National Energy Technology Laboratory will participate in the project. Chombo-Crunch, the underlying application code, is one of the codes targeted by the NESAP program and incorporates AMR.

“The two awards in the geosciences area will deliver breakthrough HPC modeling and simulation solutions that tackle critical challenges in safely utilizing subsurface energy resources as well as predicting regional-scale earthquake hazards,” said Energy Geosciences Division Director Jens Birkholzer.

“Exascale Modeling of Advanced Particle Accelerators” will be led by Jean-Luc Vay of the Accelerator Technology and Applied Physics Division. Particle accelerators are a vital part of the DOE-supported infrastructure of discovery science and university research, as well as private-sector applications, and have a broad range of benefits to industry, security, energy, the environment and medicine. This project supports the practical economic design of smaller, less-expensive plasma-based accelerators. 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. Lawrence Livermore National Laboratory and the SLAC National Accelerator Laboratory will participate in the project. Vay also leads the NESAP project on Advanced Modeling of Particle Accelerators. This project also incorporates AMR.

“This accelerator modeling project embodies the new paradigm of combining experimental and computational methods to advance a critical technology,” said James Symons, Associate Laboratory Director for Physical Sciences. “Realizing the potential of plasma-driven accelerators will impact fields ranging from health care to manufacturing to basic research.”

Berkeley Lab is also participating in these four-year projects:

“Computing the Sky at Extreme Scales,” led by Argonne National Laboratory will support cosmological research in the Standard Model of Particle Physics, including dark matter, dark energy and inflation of the universe. This is another project incorporating AMR.

“NWChemEx: Tackling Chemical, Materials and Biomolecular Challenges in the Exascale Era,” led by Pacific Northwest National Laboratory, will advance the NWChem computational chemistry application, which is used in areas ranging from designing catalysts for biofuels to developing stress-resistant crops. NWChem is one of the applications targeted by NESAP.

“Transforming Combustion Science and Technology with Exascale Simulations,” led by Sandia National Laboratories, will use computer simulations to design high-efficiency, low-emission combustion engines and gas turbines to reduce emissions and improve fuel efficiency. This project also incorporates AMR.

“Data Analytics at the Exascale for Free Electron Lasers,” led by the SLAC National Accelerator Laboratory, will support research in protein structures and dynamics and 3D molecular structure design of engineering functional properties. This project will work closely with Berkeley Lab’s Center for Advanced Mathematics for Energy Research Applications (CAMERA).

Of the seven “seed” projects slated to receive start-up funding over three years, Berkeley Lab will lead three:

“Exascale Solutions for Microbiome Analysis” will be led by Associate Lab Director Yelick, with support from Los Alamos National Laboratory and DOE’s Joint Genome Institute. The project will use machine learning algorithms and a high performance metagenome assembler based on the Meraculous application to study microbial diversity with the goal of developing new products and identifying new life forms. Meraculous is a NESAP application.

“Exascale Models of Stellar Explosions: Quintessential Multi-Physics Simulation” will be led by Dan Kasen of the Nuclear Science Division, with support from Argonne and Oak Ridge national labs, Stony Brook University and the University of Chicago. The project aims to explore the origin of chemical elements (which result from exploding stars, as well as other phenomena. HACC (Hardware/Hybrid Accelerated Cosmology Code) for Extreme Scale Cosmology is a NESAP project and also incorporates AMR.

“High Performance, Multidisciplinary Simulations for Regional Scale Seismic Hazard and Risk Assessments” will be led by David McCallen of Earth and Environmental Sciences, with participation from Lawrence Livermore National Laboratory, the University of California at Davis and UC Berkeley. This project also incorporates AMR.

Berkeley Lab is also contributing to two other seed projects:

“Multiscale Coupled Urban Systems,” led by Argonne National Lab, will retrofit and improve urban districts with new technologies, knowledge and tools.

“Performance Prediction of Multiphase Energy Conversion Devices with Discrete Element, Particle-in-Cell, and Two-Fluid Models,” led by the National Energy Technology Laboratory, will investigate the design of specialized facilities to capture and store CO2. This project also incorporates AMR.

About Computing Sciences and Berkeley Lab

The Lawrence Berkeley National Laboratory Computing Sciences organization provides the computing and networking resources and expertise critical to advancing the Department of Energy’s research missions: developing new energy sources, improving energy efficiency, developing new materials and increasing our understanding of ourselves, our world and our universe.

Lawrence Berkeley National Laboratory addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the DOE’s Office of Science.

About the DOE Office of Science

The 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, please visit science.energy.gov.


Source: LBNL

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!

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

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from its predecessors, including the red-hot H100 and A100 GPUs. 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. While Nvidia may not spring to mind when thinking of the quant Read more…

2024 Winter Classic: Meet the HPE Mentors

March 18, 2024

The latest installment of the 2024 Winter Classic Studio Update Show features our interview with the HPE mentor team who introduced our student teams to the joys (and potential sorrows) of the HPL (LINPACK) and accompany Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the field was normalized for boys in 1969 when the Apollo 11 missi Read more…

Apple Buys DarwinAI Deepening its AI Push According to Report

March 14, 2024

Apple has purchased Canadian AI startup DarwinAI according to a Bloomberg report today. Apparently the deal was done early this year but still hasn’t been publicly announced according to the report. Apple is preparing Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimization algorithms to iteratively refine their parameters until Read more…

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

March 18, 2024

Nvidia's latest and fastest GPU, code-named 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…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimizat Read more…

PASQAL Issues Roadmap to 10,000 Qubits in 2026 and Fault Tolerance in 2028

March 13, 2024

Paris-based PASQAL, a developer of neutral atom-based quantum computers, yesterday issued a roadmap for delivering systems with 10,000 physical qubits in 2026 a Read more…

India Is an AI Powerhouse Waiting to Happen, but Challenges Await

March 12, 2024

The Indian government is pushing full speed ahead to make the country an attractive technology base, especially in the hot fields of AI and semiconductors, but Read more…

Charles Tahan Exits National Quantum Coordination Office

March 12, 2024

(March 1, 2024) My first official day at the White House Office of Science and Technology Policy (OSTP) was June 15, 2020, during the depths of the COVID-19 loc Read more…

AI Bias In the Spotlight On International Women’s Day

March 11, 2024

What impact does AI bias have on women and girls? What can people do to increase female participation in the AI field? These are some of the questions the tech 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…

Analyst Panel Says Take the Quantum Computing Plunge Now…

November 27, 2023

Should you start exploring quantum computing? Yes, said a panel of analysts convened at Tabor Communications HPC and AI on Wall Street conference earlier this y 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…

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

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…

Training of 1-Trillion Parameter Scientific AI Begins

November 13, 2023

A US national lab has started training a massive AI brain that could ultimately become the must-have computing resource for scientific researchers. Argonne N 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…

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…

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…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire