Interview with 2019 Person to Watch Steve Oberlin

By HPCwire Editorial Team

May 9, 2019

This week, as part of our ongoing HPCwire People to Watch focus series, we are highlighting our interview with 2019 Person to Watch Steve Oberlin, chief technology officer for accelerated computing at Nvidia.

Steve’s large-scale computing technology career has spanned over 30 years, beginning in 1980 at Cray Research, where he worked on the CRAY-1 supercomputer systems. He later became the chief architect of the CRAY T3D MPP and the CRAY T3E and now holds 15 architecture and design patents related to those systems.

Steve founded Unlimited Scale, Inc. in 2000, where he spent 13 years creating new cloud computing infrastructure management and intelligent resource optimization tools. He returned to the HPC world when he joined Nvidia in 2013.

HPCwire: Steve, congratulations on being named to our People to Watch list. In November, you commemorated five years as CTO of the Tesla business unit at Nvidia, responsible for the company’s flagship architecture and roadmap. It’s been a pinnacle period of success, where Nvidia has seen its datacenter business swell. What were some of the key milestones for the Tesla unit in 2018?

Steve Oberlin: Thank you, it’s an honor!

No kidding about this being a pinnacle period for us. It’s so great to see so much work by so many talented people paying off in mind-blowing achievements. There are too many milestones to list, but I’ll give you my top three:

First, there’s Oak Ridge’s Summit and Lawrence Livermore’s Sierra GPU-accelerated supercomputers topping the Top500 list. That, combined with so many other powerful GPU-accelerated systems around the world at their back, and dominating the top of the Green500 list, is a powerful validation of the scalability of our accelerated computing platform.

DGX-2, with NVSwitch and our Volta Tensor Cores, is the second. Nobody has built iron like this — such a crazy amount of performance and memory bandwidth in a shared memory server — since the days of giant vector supercomputers. Half a terabyte of HBM at over 15 TB/s, 125 TFLOPS double precision peak. It’s an awesome beast for HPC as well as AI, and a clue into how we’ll continue to scale application performance at Moore’s Law rate (or faster!), despite Moore’s Law’s decline.

The third has to be unprecedented application success, like both Gordon Bell Award winners achieving exascale and multi-exascale performance levels using Volta Tensor Cores on Summit, and seeing important workhorse applications like WRF being added to the 580+ accelerated applications already in our catalog, which now includes 15 of the top 15 HPC applications. This progress comes thanks in large part to PGI’s OpenACC being embraced by developers for its productivity, efficiency, and great performance. There’s a wave of OpenACC success stories emerging from hackathons around the world. It’s so fun to watch.

HPCwire: How would you describe the evolution of the Tesla GPU family under your leadership?

I’d say it’s hardly “leadership”, more like “cheerleading”. I’ve been privileged to work with some of the smartest and creative engineers in the world over my career and Nvidia is extending that experience. They do all the rowing. I get to sit in the bow of the boat and pretend I’m steering.

There are two areas of optimization that are arguably the most important things we’ve done since CUDA made GPUs programmable. The first is NVLink/NVSwitch, which let’s us seamlessly scale the area of silicon a programmer sees as “one big GPU”. The second is the suite of optimizations in support of AI, including Tensor Cores and multi-precision arithmetic, which are now of course also being applied with such great results to HPC applications.

Together, these architecture features will continue to drive HPC application performance at the dizzy rate we’ve been growing for the past 5 years.

HPCwire: What is your perspective on the relationship and synergy between HPC and AI? What is the role of GPUs in this regard?

This is by far my favorite topic. There’s no doubt the current AI revolution — all of it, the self-driving cars, our smart phones actually acting smart, talking and listening to us, all the image and video recognition, classification, captioning, recommenders, AIs beating humans at games and serious tasks alike – happened largely because Nvidia GPUs and CUDA were at a critical point of usefulness and wild price performance to enable deep learning algorithms to ingest and learn enormous new data sets. Almost every AI advancement in the past five years that required any significant compute horsepower was powered by Nvidia GPUs. HPC + algorithms + big data = society-changing technology revolution.

Now, the AI revolution is coming back home to fundamentally alter how we do computational science.

Computational science is all about creating a mathematical model of the physics, chemistry, biology, or whatever phenomena you are investigating in software, and then programmatically executing it at sufficiently-interesting scale to make predictions that hopefully agree with and are relevant to the real world. But models are just models, and often – almost always – models necessarily take shortcuts to approximate various factors of computations that might be too computationally intensive or otherwise make the simulation too expensive and prevent simulating at meaningful scale or resolution.

Generically, deep neural networks are universal function approximators. They can learn a model from a well-designed and complete enough data set, which can be a high-fidelity, first-principles HPC algorithm. Once a model is trained, it can run in prediction mode, “inferencing”, at very high efficiency. It’s astounding. People are training AI models from simulations and real world data and producing models that are not only more accurate than traditional models, but can be several orders of magnitude faster.

This is going to redefine how supercomputing is done, and the architecture of supercomputers. AI supercomputing wants a universal architecture like ours, where the platform is simultaneously great at double-precision HPC, training AI, and inferencing at enormous scale. Summit and Sierra, and Japan’s new ABCI system are recent examples of this new kind of architecture.

HPCwire: What is Nvidia doing to further the democratization of AI?

What aren’t we doing? Even before my time, Nvidia had a “CUDA everywhere” philosophy that propagated the same parallel architecture, programmable by the same languages and tools, on everything from 5-15 Watt mobile devices, to laptops, desktops and workstations, to the world’s largest and fastest supercomputer for the last 12 years. There are millions of GeForce game cards that can run all the frameworks. This whole AI revolution started with researchers training neural networks on their desktop GPUs.

Don’t have one or need more than you have? Volta with Tensor Cores, and a variety of other powerful Nvidia GPUs, are in every cloud. I read the cost to train AlexNet is now down to just a few bucks. We’ve made a free repository of Docker containers with pre-installed configurations of every framework, optimized, accelerated, and maintained by Nvidia’s performance experts that run on in-house or cloud resources.

If you’re an individual or small lab or business and don’t think you can get affordable access to Nvidia GPUs to pursue AI, then you’re just not looking. It couldn’t be easier.

Philosophically, a platform and the community that stands on it is a democratizing force in itself. Nvidia has invested a lot in the platform technologies and tools. Users benefit from those, but also from a network effect from being able to share and leverage work that is built upon that platform. A major benefit that’s definitely in the “democratization” vein is knowing that the great majority of models and codes in the thousands of GitHub AI repositories you may wish to leverage in your work were originally built on frameworks optimized for Nvidia GPUs like your’s, and that as AI continues to explode, your platform is the vehicle for you to stay connected and leverage the advances being made by others at that leading edge, too.

In addition to the platform, we give a lot away to help people bootstrap to the next level, regardless where they are at. We’ve donated hundreds of the latest GPUs to researchers. We have Inception, a program that engages with AI startups (by the thousands, now), and DLI, our “Deep Learning Institute”, that offers a host of training and tutorial resources and classes. We have leading AI researchers in at Nvidia and we collaborate around the world. We publish our results. We develop and maintain key technology like the CuDNN and NCCL libraries, which every DL framework leverages for optimal compute and communications. We’ve even released open source hardware, the design of our super-efficient inference accelerator, for anyone to include in their ASICs. Today, it’s “AI Everywhere” at Nvidia.

HPCwire: Your tenure of innovation in HPC includes leading design work at Cray Research and SGI and now you’ve been driving Nvidia’s high-end architecture since 2013 – what excites you (most) about working in high-performance computing?

Well, I love hardware. I’ve always been a HW geek. When I joined Nvidia, I was coming back from a decade away from HPC, and hadn’t really paid close attention to it. I had dinner with Bill Dally, Nvidia’s Chief Scientist and a friend from the ‘90s when he helped us with the interconnect network architecture for Cray Research’s first MPPs, the T3D and T3E. When I worried my HPC knowledge might be stale, Bill told me, “Don’t worry, nothing’s really changed.”

That wasn’t quite true. GPU accelerated computing was new, and it was incredibly powerful. I had new perspective on the meaning of “future shock” the first time someone handed me a Pascal GPU. The Cray T3E was the first supercomputer in the world to sustain 1 TFLOPS on a real application. When I stepped away, there were still T3Es in production in the world, and, only a little over a decade later, I was holding its equivalent in my hand. That gave me goosebumps. (And, made me want to network a bunch of them together!)

The only thing that’s better than that, is the kick I get from seeing people take that amazing technology and do even more amazing things with it. I love nothing more than watching that never-before-revealed insight presented by excited researchers, the predictions confirmed or upended, the visualizations and interactions that are just impossible in the real world, and the fundamental impact on everyone on earth. HPC is important in ways that business or enterprise computing are not. Yes, our economy and the engines powering society are critical, but all of civilization is built on technology, and technology is built on science. It sounds corny, but it’s a thrill to know that the tools you’ve had a hand in creating are advancing civilization. There’s something deeply satisfying in that.

HPCwire: Outside of the professional sphere, what can you tell us about yourself – personal life, family, background, hobbies, etc.? Is there anything about you your colleagues might be surprised to learn?

Probably several things, but I’m only going to talk about one.

Back in the ‘80s, when computers had only alphanumeric displays and keyboards, my artist wife, Gwen, and I built a bunch of computer graphics hardware (frame buffers, floating point accelerators, and film recorders) of our own design and wrote various ray tracer, z-buffer, and scanline rendering programs, particle systems, paint programs, compositors, etc., trying to bootstrap a CGI business before there were such things outside Hollywood and Madison Ave. We did everything ourselves from scratch, wire-wrapping thousands of ICs, mining Siggraph proceedings and other papers for algorithms. It was completely fascinating. Even the failures were often visually spectacular. Of course, the desktops we were using were so feeble (even after I souped them up) it could take a day or more to ray trace a single 640×480 image, pixel by excruciating pixel, but it was unbelievably cool to get up in the morning and look at the newest image to emerge from this wild new viewport into a completely synthetic world.

It was nuts. We were terrible businesspeople who only liked to do the fun technical stuff, and it probably would have failed even if we’d done everything right, but it was about the most technical fun I’ve ever had (and I’ve had a lot of great technical fun). I was simultaneously working for Cray Research on the Cray-2 and Cray-3 during that glorious time, then effectively abandoned Gwen and doomed the graphics endeavor as I started to travel heavily in the early days of Cray’s MPP project. But, I still have a soft spot in my heart for computer graphics, the technology and the art, and still wonder what might have been if I’d taken the RGB pill instead of the blue one…

And the world moves on: 2018 brought even more future shock as Nvidia demonstrates real time raytracing at ~10x higher resolution in professional and even gaming desktop GPUs. How cool is that?!

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!

Penguin Computing Brings Cascade Lake-AP to OCP Form Factor

July 7, 2020

Penguin Computing, a subsidiary of SMART Global Holdings, Inc., is announcing a new Tundra server, Tundra AP, that is the first to implement the Intel Xeon Scalable 9200 series processors (codenamed Cascade Lake-AP) in t Read more…

By Tiffany Trader

Google Cloud Debuts 16-GPU Ampere A100 Instances

July 7, 2020

On the heels of the Nvidia's Ampere A100 GPU launch in May, Google Cloud is announcing alpha availability of the A100 "Accelerator Optimized" VM A2 instance family on Google Compute Engine. The instances are powered by t Read more…

By Tiffany Trader

Q&A: HLRS’s Bastian Koller Tackles HPC and Industry in Germany and Europe

July 6, 2020

HPCwire: Let's start with HLRS and work our way up to the European scale. HLRS has stood out in the HPC world for its support of both scientific and industrial research. Can you discuss key developments in recent years? Read more…

By Steve Conway, Hyperion

The Barcelona Supercomputing Center Offers a Virtual Tour of Its MareNostrum Supercomputer

July 6, 2020

With the COVID-19 pandemic continuing to threaten the world and disrupt normal operations, facility tours remain a little difficult to operate, with many supercomputing centers having shuttered facility tours for visitor Read more…

By Oliver Peckham

What’s New in Computing vs. COVID-19: Fugaku, Congress, De Novo Design & More

July 2, 2020

Supercomputing, big data and artificial intelligence are crucial tools in the fight against the coronavirus pandemic. Around the world, researchers, corporations and governments are urgently devoting their computing reso Read more…

By Oliver Peckham

AWS Solution Channel

Maxar Builds HPC on AWS to Deliver Forecasts 58% Faster Than Weather Supercomputer

When weather threatens drilling rigs, refineries, and other energy facilities, oil and gas companies want to move fast to protect personnel and equipment. And for firms that trade commodity shares in oil, precious metals, crops, and livestock, the weather can significantly impact their buy-sell decisions. Read more…

Intel® HPC + AI Pavilion

Supercomputing the Pandemic: Scientific Community Tackles COVID-19 from Multiple Perspectives

Since their inception, supercomputers have taken on the biggest, most complex, and most data-intensive computing challenges—from confirming Einstein’s theories about gravitational waves to predicting the impacts of climate change. Read more…

OpenPOWER Reboot – New Director, New Silicon Partners, Leveraging Linux Foundation Connections

July 2, 2020

Earlier this week the OpenPOWER Foundation announced the contribution of IBM’s A21 Power processor core design to the open source community. Roughly this time last year, IBM announced open sourcing its Power instructio Read more…

By John Russell

Google Cloud Debuts 16-GPU Ampere A100 Instances

July 7, 2020

On the heels of the Nvidia's Ampere A100 GPU launch in May, Google Cloud is announcing alpha availability of the A100 "Accelerator Optimized" VM A2 instance fam Read more…

By Tiffany Trader

Q&A: HLRS’s Bastian Koller Tackles HPC and Industry in Germany and Europe

July 6, 2020

HPCwire: Let's start with HLRS and work our way up to the European scale. HLRS has stood out in the HPC world for its support of both scientific and industrial Read more…

By Steve Conway, Hyperion

OpenPOWER Reboot – New Director, New Silicon Partners, Leveraging Linux Foundation Connections

July 2, 2020

Earlier this week the OpenPOWER Foundation announced the contribution of IBM’s A21 Power processor core design to the open source community. Roughly this time Read more…

By John Russell

Hyperion Forecast – Headwinds in 2020 Won’t Stifle Cloud HPC Adoption or Arm’s Rise

June 30, 2020

The semiannual taking of HPC’s pulse by Hyperion Research – late fall at SC and early summer at ISC – is a much-watched indicator of things come. This yea Read more…

By John Russell

Racism and HPC: a Special Podcast

June 29, 2020

Promoting greater diversity in HPC is a much-discussed goal and ostensibly a long-sought goal in HPC. Yet it seems clear HPC is far from achieving this goal. Re Read more…

Top500 Trends: Movement on Top, but Record Low Turnover

June 25, 2020

The 55th installment of the Top500 list saw strong activity in the leadership segment with four new systems in the top ten and a crowning achievement from the f Read more…

By Tiffany Trader

ISC 2020 Keynote: Hope for the Future, Praise for Fugaku and HPC’s Pandemic Response

June 24, 2020

In stark contrast to past years Thomas Sterling’s ISC20 keynote today struck a more somber note with the COVID-19 pandemic as the central character in Sterling’s annual review of worldwide trends in HPC. Better known for his engaging manner and occasional willingness to poke prickly egos, Sterling instead strode through the numbing statistics associated... Read more…

By John Russell

ISC 2020’s Student Cluster Competition Winners Announced

June 24, 2020

Normally, the Student Cluster Competition involves teams of students building real computing clusters on the show floors of major supercomputer conferences and Read more…

By Oliver Peckham

Supercomputer Modeling Tests How COVID-19 Spreads in Grocery Stores

April 8, 2020

In the COVID-19 era, many people are treating simple activities like getting gas or groceries with caution as they try to heed social distancing mandates and protect their own health. Still, significant uncertainty surrounds the relative risk of different activities, and conflicting information is prevalent. A team of Finnish researchers set out to address some of these uncertainties by... Read more…

By Oliver Peckham

[email protected] Turns Its Massive Crowdsourced Computer Network Against COVID-19

March 16, 2020

For gamers, fighting against a global crisis is usually pure fantasy – but now, it’s looking more like a reality. As supercomputers around the world spin up Read more…

By Oliver Peckham

[email protected] Rallies a Legion of Computers Against the Coronavirus

March 24, 2020

Last week, we highlighted [email protected], a massive, crowdsourced computer network that has turned its resources against the coronavirus pandemic sweeping the globe – but [email protected] isn’t the only game in town. The internet is buzzing with crowdsourced computing... Read more…

By Oliver Peckham

Global Supercomputing Is Mobilizing Against COVID-19

March 12, 2020

Tech has been taking some heavy losses from the coronavirus pandemic. Global supply chains have been disrupted, virtually every major tech conference taking place over the next few months has been canceled... Read more…

By Oliver Peckham

Supercomputer Simulations Reveal the Fate of the Neanderthals

May 25, 2020

For hundreds of thousands of years, neanderthals roamed the planet, eventually (almost 50,000 years ago) giving way to homo sapiens, which quickly became the do Read more…

By Oliver Peckham

DoE Expands on Role of COVID-19 Supercomputing Consortium

March 25, 2020

After announcing the launch of the COVID-19 High Performance Computing Consortium on Sunday, the Department of Energy yesterday provided more details on its sco Read more…

By John Russell

Steve Scott Lays Out HPE-Cray Blended Product Roadmap

March 11, 2020

Last week, the day before the El Capitan processor disclosures were made at HPE's new headquarters in San Jose, Steve Scott (CTO for HPC & AI at HPE, and former Cray CTO) was on-hand at the Rice Oil & Gas HPC conference in Houston. He was there to discuss the HPE-Cray transition and blended roadmap, as well as his favorite topic, Cray's eighth-gen networking technology, Slingshot. Read more…

By Tiffany Trader

Honeywell’s Big Bet on Trapped Ion Quantum Computing

April 7, 2020

Honeywell doesn’t spring to mind when thinking of quantum computing pioneers, but a decade ago the high-tech conglomerate better known for its control systems waded deliberately into the then calmer quantum computing (QC) waters. Fast forward to March when Honeywell announced plans to introduce an ion trap-based quantum computer whose ‘performance’ would... Read more…

By John Russell

Leading Solution Providers

Contributors

Neocortex Will Be First-of-Its-Kind 800,000-Core AI Supercomputer

June 9, 2020

Pittsburgh Supercomputing Center (PSC - a joint research organization of Carnegie Mellon University and the University of Pittsburgh) has won a $5 million award Read more…

By Tiffany Trader

‘Billion Molecules Against COVID-19’ Challenge to Launch with Massive Supercomputing Support

April 22, 2020

Around the world, supercomputing centers have spun up and opened their doors for COVID-19 research in what may be the most unified supercomputing effort in hist Read more…

By Oliver Peckham

Nvidia’s Ampere A100 GPU: Up to 2.5X the HPC, 20X the AI

May 14, 2020

Nvidia's first Ampere-based graphics card, the A100 GPU, packs a whopping 54 billion transistors on 826mm2 of silicon, making it the world's largest seven-nanom Read more…

By Tiffany Trader

Australian Researchers Break All-Time Internet Speed Record

May 26, 2020

If you’ve been stuck at home for the last few months, you’ve probably become more attuned to the quality (or lack thereof) of your internet connection. Even Read more…

By Oliver Peckham

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…

By Doug Black

15 Slides on Programming Aurora and Exascale Systems

May 7, 2020

Sometime in 2021, Aurora, the first planned U.S. exascale system, is scheduled to be fired up at Argonne National Laboratory. Cray (now HPE) and Intel are the k Read more…

By John Russell

Summit Supercomputer is Already Making its Mark on Science

September 20, 2018

Summit, now the fastest supercomputer in the world, is quickly making its mark in science – five of the six finalists just announced for the prestigious 2018 Read more…

By John Russell

TACC Supercomputers Run Simulations Illuminating COVID-19, DNA Replication

March 19, 2020

As supercomputers around the world spin up to combat the coronavirus, the Texas Advanced Computing Center (TACC) is announcing results that may help to illumina Read more…

By Staff report

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This