First Annual Exascale Day Celebrates Next 1000x Horizon

By Tiffany Trader

October 21, 2019

October 18 (aka 10/18) marked the first annual exascale day, hosted by Cray, the Exascale Computing Project and the DOE labs — Argonne, Oak Ridge and Lawrence Livermore — that are getting ready to host the nation’s first exascale supercomputers. All three machines will be built by Cray utilizing their Shasta architecture, Slingshot interconnect and new software platform.

To mark the occasion, Cray (now an HPE company) and the DOE hosted a virtual panel discussion Friday morning. The participants came together to discuss how the exascale era will change the face of computational science and the advances it will foster. The panel was moderated by Earl Joseph, CEO of HPC analyst firm Hyperion Research.

Joining the panel were:

Doug Kothe, ECP Director
Steve Scott, Cray CTO
Rick Stevens, Associate Lab Director, ANL
Jeff Nichols, Associate Lab Director, ORNL
Michel McCoy, LLNL Program Director

Crossing the exascale threshold gives rise to a computer that can perform 1018 (18 quintillion) adds or multiplies per second. October 18 seemed a natural choice to acknowledge this important computational milestone and the community that is working to enable it. “[Exascale computing] really is the major driver for the future of our society and making the world a much better place as far as advancing science, building better products, improving health care for everyone and [reducing] the cost of health care, and also doing very unusual and fascinating things like testing the impossible in the world,” said Hyperion’s Joseph.

The trajectory from megaflops to exaflops brings a trillion-times growth in the ability to carry out adds or multiplies. “This allows us to do all kinds of science that we weren’t able to do 40 years ago,” said ORNL’s Nichols. “When we were doing calculations 40 years ago, we would be lucky to actually get something that would be close to experiment, but today, we can actually predict what experimentalists might go find in their laboratories.”

We heard again about the enormity of the computational challenge at Livermore, tasked with maintaining the nation’s nuclear stockpile without the use of nuclear testing. “The nasty truth is that up until now, we’ve basically had to run most of our routine calculations in 2D simply because running in 3D, the turnaround time was so long that the analyst would forget the question before getting the answer,” remarked LLNL’s McCoy. “Codes have had to become increasingly predictive,” he said, “because the nuclear weapons which were designed to last maybe a year and then they got replaced, now have to be kept going for decades. They age in place; things happen to them. The codes cannot rely on predictions from their antecedents.”

LLNL’s Sierra machine is already boosting the capabilities and enabling lab scientists to run 3D codes at 2D resolution. “That’s opening a door that was never opened before,” said McCoy. “With El Capitan, they will be able to run a series of calculations tests, and quantify their uncertainty in 3D. In other words, 3D can become the new 2D. The exacale systems are going to make a difference for us. And they’re coming just in time.”

Cray’s Steve Scott, designer of many Cray systems and the lead on the Slingshot network, underscored the scale of the coming generation of DOE machines. “Just looking at the Frontier system [expected at ORNL in late 2021], it’s the size of two basketball courts and has the weight of 35 school buses. It’s got 90 miles of cabling in it. If you just looked at the network bandwidth that ties everything together, there’s enough network bandwidth to upload 100,000 high definition movies in one second.”

The U.S. is on track to deploy one or possibly two exascale machines by the end of 2021. The pace of leadership computing battles a diminished Moore’s law and the loss of Dennard scaling. “We were expecting to get to an exaflop computer originally right around now, and it’s taking a little bit longer; it’s getting harder than in the past,” said Scott. Previously, supercomputing was hitting 1,000-fold performance increases roughly every 10 years. Roadrunner, the first petascale system, was deployed in 2008. ASCI Red broke the 1 teraflops barrier in 1997.

“For multiple decades, the power efficiency of that logic kept up with Moore’s law perfectly well. And over the past 10-15 years, that’s no longer been the case; it’s starting to drive up power. And we’re starting to get to where we can see the end of Moore’s law where the current silicon technology is not going to continue to exponentially improve over time, over the next decade, and so it’s getting increasingly harder to build these systems,” said Scott.

The power wall has propelled the transition to accelerators, which, said Scott, “give you more computing performance per watt than you can get with a traditional CPU.” All three planned U.S. exascale systems will be powered by accelerators: Aurora at Argonne with Intel GPUs, Frontier at Oak Ridge with AMD GPUs and El Capitan at Livermore with an as-yet-to-be-revealed GPU.

“As we look forward to the next decade, we’re going to have to do something even even more dramatic,” Scott said. “We will save that for zettaflops day.”

Argonne’s Rick Stevens pointed out that the Exascale Computing Project is developing software that will run on many machines, not just the three CORAL [Collaboration of Oak Ridge, Argonne and Livermore] machines. He noted the general trend of architectures moving toward accelerated systems. “GPU systems are the target for these application software packages and for the software stack (that ECP is developing). So think of this as not just feeding these three machines it’s feeding the whole ecosystem with open source technology that will raise everything, so I think that’s a really important point.”

Ensuring and enabling broader capability and wider utility is part of the ECP mission. “These technologies are going to be portable and transportable to everything from your laptop and your desktop to an engineering cluster to the biggest machines that we can put together, and the accelerated node technology is really critical for us to do this,” said ECP’s Doug Kothe. “These first three machines are important first movers to tackle the problems we’ve signed up to, but we expect these technology be used broadly across the ecosystem.”

Kothe reviewed the progress of the nation’s exascale program and reiterated the importance of a day-one ready software stack without which the (very expensive) exascale machines would not be productive. The ECP is supporting critical science workloads related to the nuclear stockpile program, energy production and transmission, additive manufacturing, cancer research and many other domains.

AI is a major focus area. AI capabilities are being brought into the ECP software stack and all three labs will be hosting both artificial intelligence machine learning applications in tandem with modeling and simulation. Stevens, who is also co-PI for the AI for science town hall meetings (as is Nichols, along with Kathy Yelick at Berkeley), shared his enthusiasm for the synergies between simulation and AI.

“I think this is going to be yet another sea change in how we do science,” he said. “In particular, we think that we can use that combination to design new materials, new materials for energy, whether it’s improved photovoltaics or energy storage materials, or materials that could make reactors safer. For example, we think we can apply the same thinking to building new classes of polymers, polymers that are environmentally friendly, that degrade on a regular schedule or don’t have harmful effects when we manufacture them. We think we can use it to design better drugs, particularly in cancer and other diseases. And finally, I think it will become possible in the exascale timeframe to use AI actually to design new types of organisms.”

While the AI silicon space is still nascent, GPUs have proved themselves suitable for traditional HPC codes as well as emerging AI codes, and their mixed-precision capabilities provide a speed-up for machine learning workloads. “Today, Summit can do 200 quadrillion double-precision adds or multiplies per second, but it can actually already do 3.3 quintillion half-precision adds or multiplies,” said Nichols. “This concept of using much lower precision to do training in order to do machine learning to build models based on the data is something that all of our systems will be able to exploit to a much greater degree. And so the machines that we have today with Summit and the machines that we have in the future are going to be quite capable of not only solving science problems from a first principles perspective, but also from a much reduced precision data based model.”

McCoy underscored the importance of AI and reduced precision approaches. “Moore’s law is slowing down; Dennard scaling is already in the rearview mirror, so computers aren’t going to get faster very quickly,” he said. “So we need to find some way to accelerate time to solution. Machine learning combined with partial differential equation simulation could act as a as a force multiplier, and continue the trajectory forward at an undiminished pace. So this is a huge world opening up for us.”

Scott concurred: “It’s very unlikely that we will ever get to a zettaflop computer, 10 to the 21 operations per second, using the technology that we know today, CMOS silicon technology. The next decade is going to be all about having significantly different approaches to how we do computing. And this convergence of analytics and simulation and with traditional modeling is likely to be at least a but likely the central trust for getting improved performance and capabilities, given the slowing in [CMOS] technology.”

The conversation continued to come back to power. DARPA initially set the opening exascale power envelope at 20 megawatts, but that has been relaxed to about 30 megawatts.

Power efficiency is a first-class concern, and it’s been a key driver for GPUs at the leading-edge of supercomputing. The world’s top 10 greenest supercomputers all employ accelerators, primarily GPUs, in a hybrid system design.

“When we did our upgrade from Jaguar to Titan, we got this 10x boost in performance, and our power consumption remained flat. Same thing going from Titan to Summit,” said Nichols.

That relatively flat power line won’t hold at exascale however. The transition from Summit to Frontier ups the power ante from 13 megawatts to 30 megawatts (up to 40 megawatts at the outside). At roughly $1 million per megawatt cost, 30 megawatts of power translates into a $30 million a year power bill. “How we get another factor 10 or 100, or 1,000 performance improvement without doubling, tripling or an order of magnitude of power is absolutely [a] huge, fundamental [question],” said Nichols. “We can’t go forward and continue to pay the kind of power bills that we’re paying after exascale without some significant innovation.”

The participants took this as an opening to give credit to the investments made by the DOE and the NNSA through the Exascale Computing Project and PathForward program. “These programs [and their forerunners] allowed us to fund the companies that do the deep dive node and system design to tackle exactly the problem of having more power-aware hardware and it’s really paid off,” said Kothe.

“It wasn’t easy to convince a lot of people in government, it took a while. But when they got behind it, they made it happen,” said Nichols.

“I can guarantee you that the machines that are going to be going onto your floors in a couple of years would not have been possible without all the early support and the Exascale Computing Project and the very targeted R&D that went into into several aspects of the machines,” said Scott.

Watch a replay of the webcast here: https://www.cray.com/resources/exascale-day-panel-discussion

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

With New Owner and New Roadmap, an Independent Omni-Path Is Staging a Comeback

July 23, 2021

Put on a shelf by Intel in 2019, Omni-Path faced a uncertain future, but under new custodian Cornelis Networks, OmniPath is looking to make a comeback as an independent high-performance interconnect solution. A "significant refresh" – called Omni-Path Express – is coming later this year according to the company. Cornelis Networks formed last September as a spinout of Intel's Omni-Path division. Read more…

PEARC21 Panel Reviews Eight New NSF-Funded HPC Systems Debuting in 2021

July 23, 2021

Over the past few years, the NSF has funded a number of HPC systems to further supply the open research community with computational resources to meet that community’s changing and expanding needs. A review of these systems at the PEARC21 conference (July 19-22) highlighted... Read more…

Chameleon’s HPC Testbed Sharpens Its Edge, Presses ‘Replay’

July 22, 2021

“One way of saying what I do for a living is to say that I develop scientific instruments,” said Kate Keahey, a senior fellow at the University of Chicago and a computer scientist at Argonne National Laboratory, as s Read more…

PEARC21 Plenary Session: AI for Innovative Social Work

July 21, 2021

AI analysis of social media poses a double-edged sword for social work and addressing the needs of at-risk youths, said Desmond Upton Patton, senior associate dean, Innovation and Academic Affairs, Columbia University. S Read more…

Summer Reading: “High-Performance Computing Is at an Inflection Point”

July 21, 2021

At last month’s 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies (HEART), a group of researchers led by Martin Schulz of the Leibniz Supercomputing Center (Munich) presented a “position paper” in which they argue HPC architectural landscape... Read more…

AWS Solution Channel

Accelerate innovation in healthcare and life sciences with AWS HPC

With Amazon Web Services, researchers can access purpose-built HPC tools and services along with scientific and technical expertise to accelerate the pace of discovery. Whether you are sequencing the human genome, using AI/ML for disease detection or running molecular dynamics simulations to develop lifesaving drugs, AWS has the infrastructure you need to run your HPC workloads. Read more…

PEARC21 Panel: Wafer-Scale-Engine Technology Accelerates Machine Learning, HPC

July 21, 2021

Early use of Cerebras’ CS-1 server and wafer-scale engine (WSE) has demonstrated promising acceleration of machine-learning algorithms, according to participants in the Scientific Research Enabled by CS-1 Systems panel Read more…

With New Owner and New Roadmap, an Independent Omni-Path Is Staging a Comeback

July 23, 2021

Put on a shelf by Intel in 2019, Omni-Path faced a uncertain future, but under new custodian Cornelis Networks, OmniPath is looking to make a comeback as an independent high-performance interconnect solution. A "significant refresh" – called Omni-Path Express – is coming later this year according to the company. Cornelis Networks formed last September as a spinout of Intel's Omni-Path division. Read more…

Chameleon’s HPC Testbed Sharpens Its Edge, Presses ‘Replay’

July 22, 2021

“One way of saying what I do for a living is to say that I develop scientific instruments,” said Kate Keahey, a senior fellow at the University of Chicago a Read more…

Summer Reading: “High-Performance Computing Is at an Inflection Point”

July 21, 2021

At last month’s 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies (HEART), a group of researchers led by Martin Schulz of the Leibniz Supercomputing Center (Munich) presented a “position paper” in which they argue HPC architectural landscape... Read more…

PEARC21 Panel: Wafer-Scale-Engine Technology Accelerates Machine Learning, HPC

July 21, 2021

Early use of Cerebras’ CS-1 server and wafer-scale engine (WSE) has demonstrated promising acceleration of machine-learning algorithms, according to participa Read more…

15 Years Later, the Green500 Continues Its Push for Energy Efficiency as a First-Order Concern in HPC

July 15, 2021

The Green500 list, which ranks the most energy-efficient supercomputers in the world, has virtually always faced an uphill battle. As Wu Feng – custodian of the Green500 list and an associate professor at Virginia Tech – tells it, “noone" cared about energy efficiency in the early 2000s, when the seeds... Read more…

Frontier to Meet 20MW Exascale Power Target Set by DARPA in 2008

July 14, 2021

After more than a decade of planning, the United States’ first exascale computer, Frontier, is set to arrive at Oak Ridge National Laboratory (ORNL) later this year. Crossing this “1,000x” horizon required overcoming four major challenges: power demand, reliability, extreme parallelism and data movement. Read more…

Quantum Roundup: IBM, Rigetti, Phasecraft, Oxford QC, China, and More

July 13, 2021

IBM yesterday announced a proof for a quantum ML algorithm. A week ago, it unveiled a new topology for its quantum processors. Last Friday, the Technical Univer Read more…

ExaWind Prepares for New Architectures, Bigger Simulations

July 10, 2021

The ExaWind project describes itself in terms of terms like wake formation, turbine-turbine interaction and blade-boundary-layer dynamics, but the pitch to the Read more…

AMD Chipmaker TSMC to Use AMD Chips for Chipmaking

May 8, 2021

TSMC has tapped AMD to support its major manufacturing and R&D workloads. AMD will provide its Epyc Rome 7702P CPUs – with 64 cores operating at a base cl Read more…

Intel Launches 10nm ‘Ice Lake’ Datacenter CPU with Up to 40 Cores

April 6, 2021

The wait is over. Today Intel officially launched its 10nm datacenter CPU, the third-generation Intel Xeon Scalable processor, codenamed Ice Lake. With up to 40 Read more…

Berkeley Lab Debuts Perlmutter, World’s Fastest AI Supercomputer

May 27, 2021

A ribbon-cutting ceremony held virtually at Berkeley Lab's National Energy Research Scientific Computing Center (NERSC) today marked the official launch of Perlmutter – aka NERSC-9 – the GPU-accelerated supercomputer built by HPE in partnership with Nvidia and AMD. Read more…

Ahead of ‘Dojo,’ Tesla Reveals Its Massive Precursor Supercomputer

June 22, 2021

In spring 2019, Tesla made cryptic reference to a project called Dojo, a “super-powerful training computer” for video data processing. Then, in summer 2020, Tesla CEO Elon Musk tweeted: “Tesla is developing a [neural network] training computer called Dojo to process truly vast amounts of video data. It’s a beast! … A truly useful exaflop at de facto FP32.” Read more…

Google Launches TPU v4 AI Chips

May 20, 2021

Google CEO Sundar Pichai spoke for only one minute and 42 seconds about the company’s latest TPU v4 Tensor Processing Units during his keynote at the Google I Read more…

CentOS Replacement Rocky Linux Is Now in GA and Under Independent Control

June 21, 2021

The Rocky Enterprise Software Foundation (RESF) is announcing the general availability of Rocky Linux, release 8.4, designed as a drop-in replacement for the soon-to-be discontinued CentOS. The GA release is launching six-and-a-half months after Red Hat deprecated its support for the widely popular, free CentOS server operating system. The Rocky Linux development effort... Read more…

CERN Is Betting Big on Exascale

April 1, 2021

The European Organization for Nuclear Research (CERN) involves 23 countries, 15,000 researchers, billions of dollars a year, and the biggest machine in the worl Read more…

Iran Gains HPC Capabilities with Launch of ‘Simorgh’ Supercomputer

May 18, 2021

Iran is said to be developing domestic supercomputing technology to advance the processing of scientific, economic, political and military data, and to strengthen the nation’s position in the age of AI and big data. On Sunday, Iran unveiled the Simorgh supercomputer, which will deliver.... Read more…

Leading Solution Providers

Contributors

HPE Launches Storage Line Loaded with IBM’s Spectrum Scale File System

April 6, 2021

HPE today launched a new family of storage solutions bundled with IBM’s Spectrum Scale Erasure Code Edition parallel file system (description below) and featu Read more…

Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?

January 13, 2021

The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…

10nm, 7nm, 5nm…. Should the Chip Nanometer Metric Be Replaced?

June 1, 2020

The biggest cool factor in server chips is the nanometer. AMD beating Intel to a CPU built on a 7nm process node* – with 5nm and 3nm on the way – has been i Read more…

GTC21: Nvidia Launches cuQuantum; Dips a Toe in Quantum Computing

April 13, 2021

Yesterday Nvidia officially dipped a toe into quantum computing with the launch of cuQuantum SDK, a development platform for simulating quantum circuits on GPU-accelerated systems. As Nvidia CEO Jensen Huang emphasized in his keynote, Nvidia doesn’t plan to build... Read more…

Microsoft to Provide World’s Most Powerful Weather & Climate Supercomputer for UK’s Met Office

April 22, 2021

More than 14 months ago, the UK government announced plans to invest £1.2 billion ($1.56 billion) into weather and climate supercomputing, including procuremen Read more…

Q&A with Jim Keller, CTO of Tenstorrent, and an HPCwire Person to Watch in 2021

April 22, 2021

As part of our HPCwire Person to Watch series, we are happy to present our interview with Jim Keller, president and chief technology officer of Tenstorrent. One of the top chip architects of our time, Keller has had an impactful career. Read more…

Quantum Roundup: IBM, Rigetti, Phasecraft, Oxford QC, China, and More

July 13, 2021

IBM yesterday announced a proof for a quantum ML algorithm. A week ago, it unveiled a new topology for its quantum processors. Last Friday, the Technical Univer Read more…

Senate Debate on Bill to Remake NSF – the Endless Frontier Act – Begins

May 18, 2021

The U.S. Senate today opened floor debate on the Endless Frontier Act which seeks to remake and expand the National Science Foundation by creating a technology Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire