Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

By Tiffany Trader

May 10, 2017

At Nvidia’s GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company’s much-anticipated Volta architecture and flagship high-end GPU, the Tesla V100, noting that it took several thousand engineers several years to create, at an approximate development cost of $3 billion.

One thing is undeniable about the Volta V100: it is a giant chip, 33 percent larger than the Pascal P100 and once again “the biggest GPU ever made.” Fabricated by TSMC on a custom 12-nm FFN high performance manufacturing process, the V100 GPU squeezes 21.1 billion transistors and almost 100 billion via connectors on an 815 mm2 die, about the size of the Apple watch, said Huang.

“It is at the limits of photolithography,” Huang told the crowd. “You can’t make a chip any bigger than this because transistors would fall on the ground. Every single transistor that is possible to make by today’s physics was crammed into this processor.”

“To make one chip work per 12-inch wafer, I would characterize as unlikely,” added the CEO. “And so the fact that this was manufactured was a great feat.”

This is a domain specific chip, said Jonah Alben, senior vice president of GPU engineering at Nvidia. “This chip can run games very well if we want it to, but the focus [of the V100] is to be a great chip for AI and for HPC, so we dedicated all the resources we could until it was illegal to do more.”

“The first thing to know about Volta is it a giant leap for machine learning,” Luke Durant, principal engineer, CUDA Software, Nvidia followed. “[However,] we still are completely focused on high-performance computing. Across the board we’re seeing about a 1.5x speedup as compared to Pascal, just one year ago.”

Volta is a major launch for Nvidia, but not exactly a surprise. Back in 2014, the architecture was tapped to power the next-generation CORAL supercomputers, Summit and Sierra, in partnership with IBM, Mellanox and the Department of Energy. Those computers, expected to reach at least 200 petaflops of performance, are now due to be installed later this year into early 2018.

The new V100 touts spec’d performance of 7.5 teraflops double-precision, 15 teraflops single-precision, and 30 teraflops half-precision. This is nearly a 42 percent increase in peak flops over one year.

The Volta architecture introduces a brand new type of processor, Tensor Core, designed to accelerate AI workloads. With 640 Tensor Cores (8 per SM), V100 delivers 120 teraflops of deep learning performance, providing 6-12 times higher peak teraflops for Tensor operations compared with previous-generation silicon.

Volta is also slated to provide up to 60 tera-ops of INT8 performance. Nvidia kept the INT8 instructions to maintain compatibility with existing code bases and also reported that having a dedicated integer unit on Volta would help write machine learning kernels.

Tesla comparison over the last five years. Source: Nvidia. Click to Expand.

“With the V100, the most important statement isn’t the raw performance, although Nvidia managed to raise eyebrows with that,” commented Intersect360 Research CEO Addison Snell. “It’s that they are designing chips for double-precision 64-bit performance, single-precision 32-bit performance, or tensor performance, in the same package, so a single processor targets a range of applications in AI and HPC.”

Volta comes with 6MB of L2 cache and 16GB of HBM2 memory, providing 900 GB/s of bandwidth. The SMX2 form factor V100 features NVLink2 connectivity with nearly twice the throughput of the prior generation NVLink, going from 160 GB/s to 300 GB/s. Designers accomplished this by adding 50 percent more links and running them 28 percent faster.

Similar to the Pascal GP100, the Volta GV100 SM incorporates 64 FP32 cores and 32 FP64 cores per SM, however the new GPU has 80 SMs compared with 56 on the GP100. It thus has many more registers and supports more threads, warps, and thread blocks compared with previous Tesla generation GPUs, according to Nvidia.

Major features of the Volta SM include:

+ New mixed-precision FP16/FP32 Tensor Cores purpose-built for deep learning matrix arithmetic.

+ Enhanced L1 data cache for higher performance and lower latency.

+ Streamlined instruction set for simpler decoding and reduced instruction latencies.

+ Higher clocks and higher power efficiency.

“It has a completely different instruction set than Pascal,” remarked Bryan Catanzaro, vice president, Applied Deep Learning Research at Nvidia. “It’s fundamentally extremely different. Volta is not Pascal with Tensor Core thrown onto it – it’s a completely different processor.”

Catanzaro, who returned to Nvidia from Baidu six months ago, emphasized how the architectural changes wrought greater flexibility and power efficiency.

“It’s worth noting that Volta has the biggest change to the GPU threading model basically since I can remember and I’ve been programming GPUs for a while,” he said. “With Volta we can actually have forward progress guarantees for threads inside the same warp even if they need to synchronize, which we have never been able to do before. This is going to enable a lot more interesting algorithms to be written using the GPU, so a lot of code that you just couldn’t write before because it potentially would hang the GPU based on that thread scheduling model is now possible. I’m pretty excited about that, especially for some sparser kinds of data analytics workloads there’s a lot of use cases where we want to be collaborating between threads in more complicated ways and Volta has a thread scheduler can accommodate that.

“It’s actually pretty remarkable to me that we were able to get more flexibility and better performance-per-watt. Because I was really concerned when I heard that they were going to change the Volta thread scheduler that it was going to give up performance-per-watt, because the reason that the old one wasn’t as flexible is you get a lot of energy efficiency by ganging up threads together and having the capability to let the threads be more independent then makes me worried that performance-per-watt is going to be worse, but actually it got better, so that’s pretty exciting.”

Added Alben: “This was done through a combination of process and architectural changes but primarily architecture. This was a very significant rewrite of the processor architecture. The Tensor Core part is obviously very [significant] but even if you look at FP32 and FP64, we’re talking about 50 percent more performance in the same power budget as where we’re at with Pascal. Every few years, we say, hey we discovered something really cool. We basically discovered a new architectural approach we could pursue that unlocks even more power efficiency than we had previously. The Volta SM is a really ambitious design; there’s a lot of different elements in there, obviously Tensor Core is one part, but the architectural power efficiency is a big part of this design.”

 

Nvidia showed off three different V100 form factors at GTC: the 300 watt SXM2 (mezzanine) module; an inferencing accelerator for hyperscale that is a 150 watt full height, half length (FHHL) PCIe card about the size of a CD case; and the standard PCIe two-slot, full-length card.

DGX-1 with eight V100s

V100 GPUs will be available starting next quarter, according to Nvidia. Customers can pre-order the Volta-series DGX-1 box now for $149,000, $20,000 more than the list price for the Pascal-equipped version.

In addition to the coming DGX-1 Volta refresh, Nvidia also released the new DGX Station. Billed as a “personal supercomputer for AI development,” DGX Station provides four NVLink-connected Tesla V100s to deliver 480 (peak) Tensor teraflops in a 1,500 watt water-cooled chassis for $69,000.

Riding the wave of AI and HPC announcements made this week and on the heels of a stronger-than-expected first quarter (recording revenue of $1.94 billion with record datacenter sales of $409 million), Nvidia shares were up 18 percent as of close of market Wednesday, reaching $121.29, an all-time high.

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!

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 existing 20-quibit platform into a more robust, self-contain Read more…

By John Russell

Intel at CES: Nervana; 10nm Server CPU; Cascade Lake

January 9, 2019

On the eve of the Consumer Electronics Show in Las Vegas this week, Intel staged a launch event that covered a new version of its Nervana AI processor and a demonstration of the next-generation Xeon 10nm chip. The Read more…

By Staff

IBM’s New Global Weather Forecasting System Runs on GPUs

January 9, 2019

Anyone who has checked a forecast to decide whether or not to pack an umbrella knows that weather prediction can be a mercurial endeavor. It is a Herculean task: the constant modeling of incredibly complex systems to a high degree of accuracy at a local level within very short spans of time. Read more…

By Oliver Peckham

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

Data: The Key To Unlocking Modern Research

Research tackles the big questions, delving into uncharted territory in pursuit of knowledge that could change the world. Today’s research simulations are generating more data than ever before, a trend that shows no signs of slowing. Read more…

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 yourself – and you are the easiest person to fool.” This maxim Read more…

By Ben Criger

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

IBM’s New Global Weather Forecasting System Runs on GPUs

January 9, 2019

Anyone who has checked a forecast to decide whether or not to pack an umbrella knows that weather prediction can be a mercurial endeavor. It is a Herculean task: the constant modeling of incredibly complex systems to a high degree of accuracy at a local level within very short spans of time. Read more…

By Oliver Peckham

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

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

HPCwire Awards Highlight Supercomputing Achievements in the Sciences

January 3, 2019

In November at SC18 in Dallas, HPCwire Readers’ and Editors’ Choice awards program commemorated its 15th year of honoring achievement in HPC, with categories ranging from Best Use of AI to the Workforce Diversity Leadership Award and recipients across a wide variety of industrial and research sectors. Read more…

By the Editorial Team

White House Top Science Post Filled After Two-Year Vacancy

January 3, 2019

Half-way into Trump's term, the Senate has confirmed a director for the Office of Science and Technology Policy (OSTP), the agency that coordinates science poli Read more…

By Tiffany Trader

Batswana Gems

December 20, 2018

Most who work in the high-performance computing (HPC) industry agree; people problems are far more complicated than technical challenges. As I wrote in a 2015 HPCwire feature titled, “Women in HPC: Revelations and Reckoning,” diversity, or the lack thereof, is the HPC industry’s current grand challenge. Read more…

By Elizabeth Leake

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

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

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

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

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

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and developm Read more…

By John Russell

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

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

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

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

HPE No. 1, IBM Surges, in ‘Bucking Bronco’ High Performance Server Market

September 27, 2018

Riding healthy U.S. and global economies, strong demand for AI-capable hardware and other tailwind trends, the high performance computing server market jumped 28 percent in the second quarter 2018 to $3.7 billion, up from $2.9 billion for the same period last year, according to industry analyst firm Hyperion Research. Read more…

By Doug Black

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

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

Germany Celebrates Launch of Two Fastest Supercomputers

September 26, 2018

The new high-performance computer SuperMUC-NG at the Leibniz Supercomputing Center (LRZ) in Garching is the fastest computer in Germany and one of the fastest i Read more…

By Tiffany Trader

Houston to Field Massive, ‘Geophysically Configured’ Cloud Supercomputer

October 11, 2018

Based on some news stories out today, one might get the impression that the next system to crack number one on the Top500 would be an industrial oil and gas mon Read more…

By Tiffany Trader

Microsoft to Buy Mellanox?

December 20, 2018

Networking equipment powerhouse Mellanox could be an acquisition target by Microsoft, according to a published report in an Israeli financial publication. Microsoft has reportedly gone so far as to engage Goldman Sachs to handle negotiations with Mellanox. Read more…

By Doug Black

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

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