Exascale for the Rest of Us: Exaflops Systems Capable for Industry

By Doug Black

June 6, 2018

Enterprise advanced scale computing – or HPC in the enterprise – is an entity unto itself, situated between (and with characteristics of) conventional enterprise IT, on one side, and traditional HPC at supercomputing centers, on the other.

When these three groups rub against each other, conflict is natural – conflict in outlook, requirements, aspirations and methods. Such is the challenge for the U.S. Department of Energy’s Exascale Computing Project (ECP) as it guides the country’s development of exascale (a billion billion calculations per second) computing. The next frontier in supercomputing, exascale also is being pursued in China, Japan, Russia and the EU, it’s generally regarded as critical to national security, scientific discovery and industrial, economic competitiveness.

The American effort emphasizes “capable exascale,” which the ECP defines as more than a system that can attain an exascale benchmark: “ECP’s work encompasses the development of an entire exascale ecosystem: applications, system software, hardware technologies and architectures, along with critical workforce development.” In short: usability and broad applicability, including adoptability by industrial companies.

That’s where the ECP’s Industry Council (IC) comes in. An external advisory group comprised of managers from 17 major corporations (Lily, Westinghouse, Dreamworks, Exxon Mobil, etc.), it serves as a voice on supercomputing issues that industrial companies care about.

We recently talked with IC Chair Dave Kepczynski, CIO, GE Global Research, General Electric, who discussed the IC’s mission within the ECP’s overall development work.  Kepczynski freely states that GE – and many other industrial organizations with insatiable compute-intensive requirements – can’t wait to get their hands on an exascale system, as long as it’s a system designed with compassion for their technical skills, existing applications and workload environments.

Following are excerpted remarks from Kepczynski in which he talks about the exascale technology he and his IC colleagues envision. As does the ECP, he emphasized that the U.S. exascale effort has a broader, more inclusive development perspective than previous government-funded supercomputing projects.


Some of the big projects of the past have been more focused around the hardware technology and programming instruments. What’s evident now is there is an entire key element around product management, around software and integrations and testing…

David Kepczynski of GE

Two things are at an intersection with the Industry Council, and they’re hardware- and software-related. We want to have a reasonable level of standardized hardware that really drives reusability of the technology architecture. That, I think, is an important piece. It’s already being demonstrated by the ECP because of the number of labs that will then re-use the blueprinted hardware and technology architecture; and not in all cases is it coming from the same hardware vendors or the same hardware make-up. So that’s a good way to demonstrate it.

The other key piece, for us, is industry-friendly software. We’re looking for reusable integration applications and microservices. We spent our last face-to-face Council meeting just on that side of the equation…. It’s more than just the hardware technology, we all recognize that now, we really need to get the entire integrated technology stack ecosystem right… We had a panel of our ISVs (Ansys, Cascade Technology, Altair) that are part of the Council to talk specifically about what everyone is doing next, so we can concentrate effort around reusable integrations, applications and microservices.

So it’s not hardware-led, it’s both hardware and software. Part of the discussion we had is that in the past the hardware kind of led and software lagged. The go-forward plan (hardware alongside software) is more than just an attempt, it’s part of the ECP. That’s why there are ISVs as part of the IC… That’s why these discussions are important for all of us. The sooner we create industry-friendly software the sooner we can shorten…speed to implementation and integration of exascale.

Refactoring Applications for Exascale

We have software and applications internal to the national labs, we have our ISVs, and we have our own internal software and applications. At GE, we have our own internal proprietary (software) that we use on aviation, for purposes of combustion and aero development, and in fact we have even used one or several of them in conjunction with U.S. government DoE national labs’ compute environments.

So all three of those are important here for us to deliver capable exascale. We need to recognize the amount of software development (and code refactoring) that will need to go into taking advantage of this next generation of parallel processing capability – taking advantage of the new technology architecture with interwoven CPUs with GPUs.

We’ve begun work on prioritized software and applications…, there is some early development that is becoming available on pre-exascale technology, and those are opportunities for ISVs and industry partners to begin testing of refactored (code). There are some early templates of the technology architecture, and so you don’t need to be a large company to begin to understand if or when or how you can take advantage of exascale.

Exascale in GE’s Future?

I would say yes, (exascale is in GE’s future). What we have internal to our company, which isn’t much different from many industrial companies, is you have a mix of supercomputing environments… Exascale is definitely on our future roadmap. We don’t want to have this big lag that we’ve had in the past (between HPC technology used in supercomputing centers and HPC used in industry)…. We want the same in order to differentiate and continue our U.S. competitiveness. We want the next levels of technical velocity, improved cycles, higher (compute) performance, higher fidelity at lower cost.

It almost gets you to ask yourself: Over time, with compute capabilities continuing to grow, most companies have already begun…their transition between less physical tests and more computational, experimental methods, heightened leveraging of advanced technologies and HPC.

There used to be many physical tests at very high cost. That doesn’t mean we’re eliminating physical tests. It means we can significantly reduce the number and significantly improve the expected results of our physical tests….

Most industrials today, whether U.S. or global, using computationally advanced applications on the supercomputing side of the equation, are really working on components and subsystems. The question is what’s the limitation? The limitation is the level of computing (available). The crux of the matter is we want more capable compute to leverage.

Today we do a lot of performance analysis and optimization at these part/subsystem levels. But really, we want to do system and environmental computational and virtual validation work at a multi-disciplinary, multi-system level. And that’s where the next level of computational capabilities is going to be able to take us as an industry.


A version of this article first appeared on our sister site EnterpriseTech.

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!

Empowering High-Performance Computing for Artificial Intelligence

April 19, 2024

Artificial intelligence (AI) presents some of the most challenging demands in information technology, especially concerning computing power and data movement. As a result of these challenges, high-performance computing Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that have occurred about once a decade. With this in mind, the ISC Read more…

2024 Winter Classic: Texas Two Step

April 18, 2024

Texas Tech University. Their middle name is ‘tech’, so it’s no surprise that they’ve been fielding not one, but two teams in the last three Winter Classic cluster competitions. Their teams, dubbed Matador and Red Read more…

2024 Winter Classic: The Return of Team Fayetteville

April 18, 2024

Hailing from Fayetteville, NC, Fayetteville State University stayed under the radar in their first Winter Classic competition in 2022. Solid students for sure, but not a lot of HPC experience. All good. They didn’t Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use of Rigetti’s Novera 9-qubit QPU. The approach by a quantum Read more…

2024 Winter Classic: Meet Team Morehouse

April 17, 2024

Morehouse College? The university is well-known for their long list of illustrious graduates, the rigor of their academics, and the quality of the instruction. They were one of the first schools to sign up for the Winter Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that ha Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use o Read more…

MLCommons Launches New AI Safety Benchmark Initiative

April 16, 2024

MLCommons, organizer of the popular MLPerf benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, one of the most pre Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announce Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. I Read more…

Google Announces Homegrown ARM-based CPUs 

April 9, 2024

Google sprang a surprise at the ongoing Google Next Cloud conference by introducing its own ARM-based CPU called Axion, which will be offered to customers in it 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…

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…

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…

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…

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…

Leading Solution Providers

Contributors

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…

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…

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…

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…

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…

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana 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…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire