Nvidia Sees Bright Future for AI Supercomputing

By Tiffany Trader

November 23, 2016

Graphics chipmaker Nvidia made a strong showing at SC16 in Salt Lake City last week. Most prominent wins were achieving the number one spot on the Green500 list with new in-house DGX-1 supercomputer, SaturnV, and partnering with the National Cancer Institute, the U.S. Department of Energy (DOE) and several national laboratories to accelerate cancer research as part of the Cancer Moonshot initiative.

The company kicked off its SC activities with a press briefing on Monday (Nov. 14), during which CEO Jen-Hsun Huang characterized 2016 as a tipping point for the GPU computing approach popularized by Nvidia for over a decade.

Not surprisingly, Huang’s main message was that the GPU computing era has arrived. Throughout the hour-long talk, Huang would revisit the theme of deep learning as both a supercomputing problem and a supercomputing opportunity.

“We believe that supercomputers ought to be designed as AI supercomputers – meaning it has to be good at both computational science as well as data science – that building a machine that’s only good at data science doesn’t make sense and building a supercomputer that’s only good at computational science doesn’t make sense,” he said.

“On the one hand, deep learning requires an enormous amount of data throughput processing – this way of developing software where the computers write software themselves inspired by a lot of data processing behind it is a very important approach to computing but it also has the wonderful opportunity to benefit supercomputing as well, solving problems for science that hasn’t been possible before today,” said Huang.

Huang’s view is that traditional numerical HPC is not going anywhere, but will exist side by side with machine learning methods.

“I’m a big fan of using math when you can; we should use AI when you can’t,” he said. “For example what’s the equation of a cat? It’s probably very similar to the equation for a dog – two ears, four legs, a tail. And so there are a lot of areas where equations don’t work and that’s where I see AI – search problems, recommendation problems, likelihood problems, where there’s either too much data, incomplete data, or no laws of physics that support it. So where do I feel like eating tonight – there’s no laws of physics for that. There’s a lot of these type of problems that we simply can’t solve – I think that they’re going to coexist.”

While Nvidia is enabling parallel computing via thousands of CUDA cores combined with the CUDA programing framework, the CEO emphasized the necessity of a performant central processing unit. “Almost everything we do we start with a strong CPU,” said Huang. “We still believe in Amdahl’s law; we believe that code has a lot of single threaded parts to it and this is an area that we want to continue to be good at.”

nvidia-nvlink-dgx-1-ibm-p8

The two servers currently shipping with the NVLink P100 GPU – Nvidia’s DGX-1 server and IBM’s Minsky platform – speak to this goal. The DGX-1 connects eight NVLink’d Pascal P100s to two 20-core Intel Xeon E5-2698 v4 chips. The IBM Minsky server leverages two Power8 CPUs and four P100 GPUs connected by NVlink up to the CPUs.

Nvidia’s 124-node supercomputer, SaturnV plays a crucial role in Nvidia’s plans to usher in AI supercomputing. The machine debuted on the 48th TOP500 list at number 28 with 3.3 petaflops Linpack (4.9 petaflops peak). Even more impressively, it nabbed the number one spot on the Green500 list achieving more than 8.17 gigaflops/watt. That’s a 42 percent improvement from the 6.67 gigaflops/watt delivered by the most efficient machine on the previous TOP500 list. Extrapolating to exascale gives us 105.7 MW. If we go with a semi-“relaxed” exascale power allowance of 30 MW (the original DARPA target was 20 MW), this is less than one-fourth the planned power consumption of US exascale systems. Three years ago, the extrapolated delta was over a 7X.

SaturnV – its name inspired by the original Moonshot – will be a critical part of the CANDLE (CANcer Distributed Learning Environment) project (covered here). Announced last month, CANDLE’s mission is to exploit high performance computing (HPC), machine learning and data analytics technologies to advance precision oncology. Huang said the partners will be working together to develop “the world’s first deep learning framework designed for exascale.”

“It’s going to be really hard,” he added. “That’s why we’re working with the four DOE labs and have all standardized on the same architecture – SaturnV is the biggest one of them but we’re all using exactly the same architecture and it’s all GPU accelerated and we’re going to develop a framework that allows us to scale to get to exascale.”

Huang noted that when you apply deep learning FLOPS math – aka 16-bit floating point operations as opposed to the HPC norm of 64-bit FLOPS, exascale is not far away at all.

The [IBM/Nvidia] CORAL machines are on track for 2018 with 300 petaflops peak FP64, which comes out to 1,200 peak FP16, Huang pointed out. “For AI, FP16 is fine, now in some areas we need FP32, we need variable precision, but that’s the point,” he said. “I think CORAL is going to be the world’s fastest AI supercomputer [and] I think that we didn’t know it then but I believe that we are building an exascale machine already.”

It’s a fair point that dialing down the bits increases data throughput (boosting FLOPS), but as one analyst at the event said, “calling it exascale is changing the rules.”

Lending more insight to Nvidia’s plans was Solutions Architect Louis Capps, who presented at the Green500 BoF on November 16.

“This is completely a research platform,” he said of SaturnV. “We’re going to have academics using it. We’re going to have partnerships, collaborations, and internally, we’re working on our deep learning research and our HPC research.”

Embedded, robotics, automotive, and hyperscale computing are all major focus areas, but Capps and Huang both were most effusive about the opportunities at the convergence of data science and HPC. “We’re just now starting to bridge where real HPC work is converging with deep learning,” said Capps.

nvidia_dgx_saturnv-800xSaturnV is organized into five 3U boxes per rack, with 15 kilowatt of power on each rack and some 25 racks total. While the press photo of SaturnV indicates 10 servers per rack, this is not reflective of what’s inside. “We could not put that many in ours,” said Capps. “We put this in a datacenter which is not HPC. It was an IT datacenter originally.”

SaturnV was one of two systems on the newly published TOP500 list to employ the Pascal-based P100 GPUs. The number two greenest super, Piz Daint is using the PCIe variants. Installed at the Swiss National Supercomputing Centre, Piz Daint delivers an energy-efficiency rating of 7.45 gigaflops/watt. Refreshed with the new P100 hardware, Piz Daint achieved 9.8 petaflops on the Linpack benchmark, securing it the eighth spot on the latest list.

Notably, every single one of the top ten systems on the Green500 list is using some flavor of acceleration or manycore. There is no pure-play traditional x86 in the bunch.

green500-nov-2016-top-10
Source: Top500/Green500

A compelling testament to this approach came from Thomas Schulthess, director of the Swiss National Supercomputing Centre, where Nvidia K80 GPUs have been used for operational weather forecasting for over a year now. “I know the HPC community has a problem with the heterogeneous approach,” he said. “We’ve done a lot of analysis on this issue. We asked, what would the goals we have at exascale look like if we build a homogeneous Xeon-based system, and there’s no way that you will run significant problems that are significantly bigger and faster than we do today in 5-6 years at exascale if you build it based on a Xeon system.

“The message to the application folks is, you’ve had time to think about it now, but now there is no more choice. If you want to run at exascale, it is going to be on Xeon Phi or GPU-accelerated or the lightweight core, almost Cell-like architectures that we see on TaihuLight.”

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!

Insights from Optimized Codes on Cineca’s Marconi

February 15, 2019

What can you do with 381,392 CPU cores? For Cineca, it means enabling computational scientists to expand a large part of the world’s body of knowledge from the nanoscale to the astronomic, from calculating quantum effe Read more…

By Ken Strandberg

What Will IBM’s AI Debater Learn from Its Loss?

February 14, 2019

The utility of IBM’s latest man-versus-machine gambit is debatable. At the very least its Project Debater got us thinking about the potential uses of artificial intelligence as a way of helping humans sift through al Read more…

By George Leopold

ClusterVision in Bankruptcy, Fate Uncertain

February 13, 2019

ClusterVision, European HPC specialists that have built and installed over 20 Top500-ranked systems in their nearly 17-year history, appear to be in the midst of bankruptcy proceedings. According to Dutch news site Drimb Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

HPE Systems With Intel Omni-Path: Architected for Value and Accessible High-Performance Computing

Today’s high-performance computing (HPC) and artificial intelligence (AI) users value high performing clusters. And the higher the performance that their system can deliver, the better. Read more…

IBM Accelerated Insights

Medical Research Powered by Data

“We’re all the same, but we’re unique as well. In that uniqueness lies all of the answers….”

  • Mark Tykocinski, MD, Provost, Executive Vice President for Academic Affairs, Thomas Jefferson University

Getting the answers to what causes some people to develop diseases and not others is driving the groundbreaking medical research being conducted by the Computational Medicine Center at Thomas Jefferson University in Philadelphia. Read more…

South African Weather Service Doubles Compute and Triples Storage Capacity of Cray System

February 13, 2019

South Africa has made headlines in recent years for its commitment to HPC leadership in Africa – and now, Cray has announced another major South African HPC expansion. Cray has been awarded contracts with Eclipse Holdings Ltd. to upgrade the supercomputing system operated by the South African Weather Service (SAWS). Read more…

By Oliver Peckham

Insights from Optimized Codes on Cineca’s Marconi

February 15, 2019

What can you do with 381,392 CPU cores? For Cineca, it means enabling computational scientists to expand a large part of the world’s body of knowledge from th Read more…

By Ken Strandberg

ClusterVision in Bankruptcy, Fate Uncertain

February 13, 2019

ClusterVision, European HPC specialists that have built and installed over 20 Top500-ranked systems in their nearly 17-year history, appear to be in the midst o Read more…

By Tiffany Trader

UC Berkeley Paper Heralds Rise of Serverless Computing in the Cloud – Do You Agree?

February 13, 2019

Almost exactly ten years to the day from publishing of their widely-read, seminal paper on cloud computing, UC Berkeley researchers have issued another ambitious examination of cloud computing - Cloud Programming Simplified: A Berkeley View on Serverless Computing. The new work heralds the rise of ‘serverless computing’ as the next dominant phase of cloud computing. Read more…

By John Russell

Iowa ‘Grows Its Own’ to Fill the HPC Workforce Pipeline

February 13, 2019

The global workforce that supports advanced computing, scientific software and high-speed research networks is relatively small when you stop to consider the magnitude of the transformative discoveries it empowers. Technical conferences provide a forum where specialists convene to learn about the latest innovations and schedule face-time with colleagues from other institutions. Read more…

By Elizabeth Leake, STEM-Trek

Trump Signs Executive Order Launching U.S. AI Initiative

February 11, 2019

U.S. President Donald Trump issued an Executive Order (EO) today launching a U.S Artificial Intelligence Initiative. The new initiative - Maintaining American L Read more…

By John Russell

Celebrating Women in Science: Meet Four Women Leading the Way in HPC

February 11, 2019

One only needs to look around at virtually any CS/tech conference to realize that women are underrepresented, and that holds true of HPC. SC hosts over 13,000 H Read more…

By AJ Lauer

IBM Bets $2B Seeking 1000X AI Hardware Performance Boost

February 7, 2019

For now, AI systems are mostly machine learning-based and “narrow” – powerful as they are by today's standards, they're limited to performing a few, narro Read more…

By Doug Black

Assessing Government Shutdown’s Impact on HPC

February 6, 2019

After a 35-day federal government shutdown, the longest in U.S. history, government agencies are taking stock of the damage -- and girding for a potential secon Read more…

By Tiffany Trader

Quantum Computing Will Never Work

November 27, 2018

Amid the gush of money and enthusiastic predictions being thrown at quantum computing comes a proposed cold shower in the form of an essay by physicist Mikhail Read more…

By John Russell

Cray Unveils Shasta, Lands NERSC-9 Contract

October 30, 2018

Cray revealed today the details of its next-gen supercomputing architecture, Shasta, selected to be the next flagship system at NERSC. We've known of the code-name "Shasta" since the Argonne slice of the CORAL project was announced in 2015 and although the details of that plan have changed considerably, Cray didn't slow down its timeline for Shasta. Read more…

By Tiffany Trader

The Case Against ‘The Case Against Quantum Computing’

January 9, 2019

It’s not easy to be a physicist. Richard Feynman (basically the Jimi Hendrix of physicists) once said: “The first principle is that you must not fool yourse Read more…

By Ben Criger

AMD Sets Up for Epyc Epoch

November 16, 2018

It’s been a good two weeks, AMD’s Gary Silcott and Andy Parma told me on the last day of SC18 in Dallas at the restaurant where we met to discuss their show news and recent successes. Heck, it’s been a good year. Read more…

By Tiffany Trader

Intel Reportedly in $6B Bid for Mellanox

January 30, 2019

The latest rumors and reports around an acquisition of Mellanox focus on Intel, which has reportedly offered a $6 billion bid for the high performance interconn Read more…

By Doug Black

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Ba Read more…

By Tiffany Trader

Looking for Light Reading? NSF-backed ‘Comic Books’ Tackle Quantum Computing

January 28, 2019

Still baffled by quantum computing? How about turning to comic books (graphic novels for the well-read among you) for some clarity and a little humor on QC. The Read more…

By John Russell

ClusterVision in Bankruptcy, Fate Uncertain

February 13, 2019

ClusterVision, European HPC specialists that have built and installed over 20 Top500-ranked systems in their nearly 17-year history, appear to be in the midst o Read more…

By Tiffany Trader

Leading Solution Providers

SC 18 Virtual Booth Video Tour

Advania @ SC18 AMD @ SC18
ASRock Rack @ SC18
DDN Storage @ SC18
HPE @ SC18
IBM @ SC18
Lenovo @ SC18 Mellanox Technologies @ SC18
NVIDIA @ SC18
One Stop Systems @ SC18
Oracle @ SC18 Panasas @ SC18
Supermicro @ SC18 SUSE @ SC18 TYAN @ SC18
Verne Global @ SC18

Contract Signed for New Finnish Supercomputer

December 13, 2018

After the official contract signing yesterday, configuration details were made public for the new BullSequana system that the Finnish IT Center for Science (CSC Read more…

By Tiffany Trader

Deep500: ETH Researchers Introduce New Deep Learning Benchmark for HPC

February 5, 2019

ETH researchers have developed a new deep learning benchmarking environment – Deep500 – they say is “the first distributed and reproducible benchmarking s Read more…

By John Russell

IBM Quantum Update: Q System One Launch, New Collaborators, and QC Center Plans

January 10, 2019

IBM made three significant quantum computing announcements at CES this week. One was introduction of IBM Q System One; it’s really the integration of IBM’s Read more…

By John Russell

HPC Reflections and (Mostly Hopeful) Predictions

December 19, 2018

So much ‘spaghetti’ gets tossed on walls by the technology community (vendors and researchers) to see what sticks that it is often difficult to peer through Read more…

By John Russell

IBM Bets $2B Seeking 1000X AI Hardware Performance Boost

February 7, 2019

For now, AI systems are mostly machine learning-based and “narrow” – powerful as they are by today's standards, they're limited to performing a few, narro Read more…

By Doug Black

Nvidia’s Jensen Huang Delivers Vision for the New HPC

November 14, 2018

For nearly two hours on Monday at SC18, Jensen Huang, CEO of Nvidia, presented his expansive view of the future of HPC (and computing in general) as only he can do. Animated. Backstopped by a stream of data charts, product photos, and even a beautiful image of supernovae... Read more…

By John Russell

The Deep500 – Researchers Tackle an HPC Benchmark for Deep Learning

January 7, 2019

How do you know if an HPC system, particularly a larger-scale system, is well-suited for deep learning workloads? Today, that’s not an easy question to answer Read more…

By John Russell

Intel Confirms 48-Core Cascade Lake-AP for 2019

November 4, 2018

As part of the run-up to SC18, taking place in Dallas next week (Nov. 11-16), Intel is doling out info on its next-gen Cascade Lake family of Xeon processors, specifically the “Advanced Processor” version (Cascade Lake-AP), architected for high-performance computing, artificial intelligence and infrastructure-as-a-service workloads. Read more…

By Tiffany Trader

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