DOE Exascale Plan Gets Support with Caveats

By John Russell

July 28, 2015

The DOE and the National Nuclear Security Administration (NNSA) plan to develop and deploy exascale technology by 2023 received strong backing yesterday from an Advanced Scientific Computing Advisory Committee (ASCAC) sub-committee but with caveats in the form of seven recommendations for strengthening management of the Exascale Computing Initiative (ECI).

Subcommittee chair, Dan Reed, vice president for research and economic development at the University of Iowa, presented the report and findings to an ASCAC meeting. “Like any ambitious undertaking, DOE’s proposed exascale computing initiative (ECI) involves some risks. Despite the risks, the benefits of the initiative to scientific discovery, national security and U.S. economic competitiveness are clear and compelling,” he said.

The subcommittee draft report was approved with a final full ASCAC version expected in August. Reed called the ECI well-crafted and noted DOE’s demonstrated ability to manage complicated, multi-stakeholder projects. Perhaps surprisingly, technology challenges were a subordinate part of the report. Instead, the report focused on project management.

Reed said, “We chose and we think appropriately to focus primarily on the organization and management issues because the technical issues and application issues have been reviewed so extensively for so many years (the by-now-familiar 10 technical challenges defined by DOE are listed further below).” Technology challenges clearly remain, he agreed.

The sub-committee’s detailed recommendations include:

  • Develop a detailed management and execution plan that defines clear responsibilities and decision-making authority to manage resources, risks, and dependencies appropriately across vendors, DOE laboratories, and other participants.
  • As part of the execution plan, clearly distinguish essential system attributes (e.g., sustained performance levels) from aspirational ones (e.g., specific energy consumption goals) and focus effort accordingly.
  • Given the scope, complexity, and potential impact of the ECI, conduct periodic external reviews by a carefully constituted advisory board.
  • Mitigate software risks by developing evolutionary alternatives to more innovative, but risky alternatives.
  • Unlike other elements of the hardware/software ecosystem, application performance and stability are mission critical, necessitating continued focus on hardware/software co-design to meet application needs.
  • Remain cognizant of the need for the ECI to support for data intensive and computation intensive workloads.
  • Where appropriate, work with other federal research agencies and international partners on workforce development and long-term research needs, while not creating dependences that could delay or imperil the execution plan.

Reed emphasized the need to be realistic in approaching the project and cautioned when setting expectations, particularly since the project is receiving wider attention in Congress.

“There’s a lot of uncertainty about the enabling technology still because this is a multi-year R&D plan. Innovation is still required. One of the things we want to ensure is that people don’t focus on the subsidiary metrics at the risk of those becoming part of the public perception of what success criteria should be. People latch onto figures of merit, sometimes rightly and sometimes wrongly. This is as much a political guidance as a technical one,” said Reed.

ASCAC Exascale Report Apps
Co-design, productive use of applications (legacy and new), and focusing on DOE and NNSA goals to advance science, enhance national competitiveness and assure nuclear stockpile stewardship are all emphasized in the report. Extending the benefits of extreme scale computing beyond these rather exclusive communities was also a theme.

“The whole point [of ECI] is to do a revolutionary leap forward. But it’s also important as part of that to the extent possible that we build broad ecosystems because the economic pull from a broad ecosystem will bring in more applications developers, it will lead to not just exascale laboratory systems, but also petascale research lab systems [used by] a much broader user base and shift the economics as well,” said Reed.

The sub-committee also recognized the growth of data-intensive computing to near equal footing with compute-intensive. Reed emphasized the DOE should, “Keep in mind in that data intensive and computationally intensive workflows both matter and in fact most of the time they are the same thing. They are intertwined pretty deeply [and] draw on the same ecosystems of hardware and software. Both matter. That drives as a corollary some focus on a new generation of analysis tools and libraries that will be needed to interpret that data.”

ASCAC had been charged by DOE and NNSA to review the “conceptual design for the Exascale Computing Initiative” and to deliver a report by September. Sub-committee members included: Reed; Martin Berzins, University of Utah; Bob Lucas, Livermore Software Technology Corporation; Satoshi Matsuoka, Tokyo Institute of Technology; Rob Pennington, University of Illinois, retired; Vivek Sarkar, Rice University; and Valerie Taylor, Texas A&M University.

The ECI’s goal is to deploy by 2023, capable exascale computing systems. This is defined as a hundred-fold increase in sustained performance over today’s computing capabilities, enabling applications to address next-generation science, engineering, and data problems to advance Department of Energy (DOE) Office of Science and National Nuclear Security Administration (NNSA) missions.

The plan includes three distinct components: Exascale Research, Development and Deployment (ExaRD); Exascale Application Development (ExaAD) to take full advantage of the emerging exascale hardware and software technologies from ExaRD; and Exascale Platform Deployment (ExaPD) to prepare for and acquire two or more exascale computers.

ASCAC Exascale Report Goals
Given the many technical issues remaining, ECI mission adjustments are inevitable said Reed. Establishing an external advisory board – coordinated by a single individual or a group – and leveraging other collaborations to help monitor and advise the project was strongly recommended. Reed also said, “On interagency and international collaboration, seek collaborations that don’t imperil the execution plan. This is not an open ended research project; it’s an outcome driven project.”

Included in the report was a restatement of the top ten exascale challenges as identified by DOE, shown here:

  • Energy efficiency: Creating more energy-efficient circuit, power, and cooling technologies.
  • Interconnect technology: Increasing the performance and energy efficiency of data movement.
  • Memory technology: Integrating advanced memory technologies to improve both capacity and bandwidth.
  • Scalable system software: Developing scalable system software that is power- and resilience-aware.
  • Programming systems: Inventing new programming environments that express massive parallelism, data locality, and resilience
  • Data management: Creating data management software that can handle the volume, velocity and diversity of data that is anticipated.
  • Exascale algorithms: Reformulating science problems and redesigning, or reinventing, their solution algorithms for exascale systems.
  • Algorithms for discovery, design, and decision: Facilitating mathematical optimization and uncertainty quantification for exascale discovery, design, and decision making.
  • Resilience and correctness: Ensuring correct scientific computation in face of faults, reproducibility, and algorithm verification challenges.
  • Scientific productivity: Increasing the productivity of computational scientists with new software engineering tools and environment

The full ASCAC report is expected to be completed in August. Here is a link to the slides presented by Reed: http://science.energy.gov/~/media/ascr/ascac/pdf/meetings/20150727/Exascale_Computing_Initiative_Review.pdf

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