Three Years On, GPU Computing Is Coming of Age

By Michael Feldman

October 7, 2010

If you’ve been reading this publication for any length of time, I’m sure you’ve noticed how much ink has been spilled on NVIDIA’s GPU computing business. The reason for that is simple: general-purpose GPU (GPGPU) computing has become a technology disrupter in HPC, and NVIDIA is the company driving it. And if you followed our recent coverage of the GPU Technology Conference (GTC) in September, you’ll get a pretty good idea of why and how this is happening.

But the technology, and especially the business, is still in its early stages. It was only in June of 2007 that NVIDIA announced its first Tesla GPU products for technical computing. Although AMD pushed its GPU FireStream products into market that same year, it is NVIDIA that has set the pace in this market. At GTC, I got a chance to talk with Andy Keane, who has headed NVIDIA’s Tesla unit since its inception. During our conversation, he offered his perspective on how the company’s GPU computing business unfolded over the past three years.

The first question I asked him was if the Tesla business was where he thought it would be when they began three years ago. Although he’s been at the center of the storm, so to speak, Keane said that even he is a bit surprised at how far the technology has come in such a short amount of time. “I felt we pushed the GPU faster than I had expected,” he admitted.

He credits a lot of this to the enthusiasm of the developer and user community.The high-end features coalesced in the current Fermi generation, like support for ECC memory and serious double-precision performance, were always on the roadmap, he said. They were just put in ahead of schedule because the community was asking for them.

The first-ever Tesla GPU-equipped cluster was shipped to the Max Planck Institute in 2008 to support Professor Holger Stark’s work in understanding the 3D structure of “macromolecules.” Stark had been using GeForce GPUs for awhile, but he wanted to scale his work to a cluster to speed up the image processing. Later that year, the first deployment of the next-generation Teslas (the 10-series GPUs), was undertaken at Tokyo Tech. Those GPUs, in this case, 170 S1070 Tesla servers, were folded into the TSUBAME 1.2 system. That machine became the first GPU-equipped supercomputer on the TOP500 list.

More Tesla cluster deployments followed. According to Keane, these larger deployments suggested the world needed ECC support and a lot more double precision — features required by large-scale scientific computing. Customers also needed more sophisticated CUDA driver software to optimize the CPU-GPU interface. “So the people you’re selling to influence the type of features you put in the GPU and the software,” Keane said.

In that sense, NVIDIA sees itself more as a catalyst for the community, rather than a market leader, per se. It’s certainly conceivable that some company is going to make more money from products based on NVIDIA’s GPGPUs than NVIDIA itself. Beyond straight HPC, GPU computing is now being employed in everything from computer vision to business intelligence. Like the CPU, the GPU is now in that territory where developers are adapting to the chip, rather than the other way around.

“We could not have written the list of applications that are here at GTC,” Keane told me. “Some are obvious, like pattern recognition and graphics. But things like neuron research? We wouldn’t have come up with that. So there are areas we’re going into because of the creativity of the developer.”

NVIDIA is counting on its next two generations of GPUs — Kepler and Maxwell — to keep the momentum going. Although new GPU computing features are in the offing for these architectures, there is going to be a concerted focus on energy efficiency. Although GPUs already have an enviable FLOPS/watt ratio, system vendors can’t accommodate devices that are more power-hungry than the current crop of chips. Fermi Teslas are rated at 225 watts today, which is frankly more than most server makers are comfortable with. So like its CPU competition, NVIDIA will be compelled to bring out more powerful devices in the same (or lower) thermal envelop.

For supercomputing, this is going to be a critical feature, especially for those counting on GPGPUs as a path to exascale. According to Keane (but not only him), delivering a 1,000-fold performance improvement over today’s computers cannot be achieved with the old techniques — certainly not with transistor and voltage scaling, and probably not with x86 manycore. The route to faster computers will be accomplished indirectly through lower power, which will translate into more parallelism, said Keane.

But achieving that level of parallelism on a conventional CPU is a lot trickier than doing it on a GPU. NVIDIA Chief Scientist Bill Dally is convinced the GPU architecture is inherently superior in delivering more FLOPS/watt than general-purpose CPUs and has even sketched a path to exascale based on extrapolations of GPU technology.

Technology aside, there’s still the question of how NVIDIA is going to make the business model work for HPC. Keane admitted that his Tesla business wouldn’t be viable as a stand-alone company. Given the cost of semiconductor design and the rest of the infrastructure need to support processor development, you need a broad product base, he said. A $2,000 Tesla device would probably cost $10,000 if you factored in all the overhead costs. You just have to look to now-defunct ClearSpeed to see the folly of such a business model.

The way NVIDIA makes this work is to amortize the R&D costs over a much larger product set, in this case the GeForce and Quadro offerings. (The Tegra products use a somewhat different set of technologies.) Tesla is designed as a higher end product, with more cores, more floating point performance, and ECC support. The consumer side needs those things. But since all three units are able to share design and development, Keane can extract his HPC goodies. “AMD has that model, Intel has that model, now NVIDIA has that model,” he said.

But that doesn’t mean the company is content to see the Teslas remain a niche business. Far from it. Keane envisions a volume market for his high-end GPUs beyond strict high performance computing. For example, computers running air traffic control, Internet traffic, and billing systems for a telecom can all benefit from the data parallel muscle of a GPU. Although mostly invisible, these “infrastructure” computers form the backbone of many IT businesses, not to mention the government. “The real volume market for a product like Tesla is in the computers you don’t see,” said Keane.

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!

CMU’s Latest “Card Shark” – Libratus – is Beating the Poker Pros (Again)

January 20, 2017

It’s starting to look like Carnegie Mellon University has a gambling problem – can’t stay away from the poker table. Read more…

By John Russell

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

Weekly Twitter Roundup (Jan. 19, 2017)

January 19, 2017

Here at HPCwire, we aim to keep the HPC community apprised of the most relevant and interesting news items that get tweeted throughout the week. Read more…

By Thomas Ayres

France’s CEA and Japan’s RIKEN to Partner on ARM and Exascale

January 19, 2017

France’s CEA and Japan’s RIKEN institute announced a multi-faceted five-year collaboration to advance HPC generally and prepare for exascale computing. Among the particulars are efforts to: build out the ARM ecosystem; work on code development and code sharing on the existing and future platforms; share expertise in specific application areas (material and seismic sciences for example); improve techniques for using numerical simulation with big data; and expand HPC workforce training. It seems to be a very full agenda. Read more…

By Nishi Katsuya and John Russell

HPE Extreme Performance Solutions

Remote Visualization: An Integral Technology for Upstream Oil & Gas

As the exploration and production (E&P) of natural resources evolves into an even more complex and vital task, visualization technology has become integral for the upstream oil and gas industry. Read more…

ARM Waving: Attention, Deployments, and Development

January 18, 2017

It’s been a heady two weeks for the ARM HPC advocacy camp. At this week’s Mont-Blanc Project meeting held at the Barcelona Supercomputer Center, Cray announced plans to build an ARM-based supercomputer in the U.K. while Mont-Blanc selected Cavium’s ThunderX2 ARM chip for its third phase of development. Last week, France’s CEA and Japan’s Riken announced a deep collaboration aimed largely at fostering the ARM ecosystem. This activity follows a busy 2016 when SoftBank acquired ARM, OpenHPC announced ARM support, ARM released its SVE spec, Fujistu chose ARM for the post K machine, and ARM acquired HPC tool provider Allinea in December. Read more…

By John Russell

Women Coders from Russia, Italy, and Poland Top Study

January 17, 2017

According to a study posted on HackerRank today the best women coders as judged by performance on HackerRank challenges come from Russia, Italy, and Poland. Read more…

By John Russell

Spurred by Global Ambitions, Inspur in Joint HPC Deal with DDN

January 17, 2017

Inspur, the fast-growth cloud computing and server vendor from China that has several systems on the current Top500 list, and DDN, a leader in high-end storage, have announced a joint sales and marketing agreement to produce solutions based on DDN storage platforms integrated with servers, networking, software and services from Inspur. Read more…

By Doug Black

Weekly Twitter Roundup (Jan. 12, 2017)

January 12, 2017

Here at HPCwire, we aim to keep the HPC community apprised of the most relevant and interesting news items that get tweeted throughout the week. Read more…

By Thomas Ayres

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

France’s CEA and Japan’s RIKEN to Partner on ARM and Exascale

January 19, 2017

France’s CEA and Japan’s RIKEN institute announced a multi-faceted five-year collaboration to advance HPC generally and prepare for exascale computing. Among the particulars are efforts to: build out the ARM ecosystem; work on code development and code sharing on the existing and future platforms; share expertise in specific application areas (material and seismic sciences for example); improve techniques for using numerical simulation with big data; and expand HPC workforce training. It seems to be a very full agenda. Read more…

By Nishi Katsuya and John Russell

ARM Waving: Attention, Deployments, and Development

January 18, 2017

It’s been a heady two weeks for the ARM HPC advocacy camp. At this week’s Mont-Blanc Project meeting held at the Barcelona Supercomputer Center, Cray announced plans to build an ARM-based supercomputer in the U.K. while Mont-Blanc selected Cavium’s ThunderX2 ARM chip for its third phase of development. Last week, France’s CEA and Japan’s Riken announced a deep collaboration aimed largely at fostering the ARM ecosystem. This activity follows a busy 2016 when SoftBank acquired ARM, OpenHPC announced ARM support, ARM released its SVE spec, Fujistu chose ARM for the post K machine, and ARM acquired HPC tool provider Allinea in December. Read more…

By John Russell

Spurred by Global Ambitions, Inspur in Joint HPC Deal with DDN

January 17, 2017

Inspur, the fast-growth cloud computing and server vendor from China that has several systems on the current Top500 list, and DDN, a leader in high-end storage, have announced a joint sales and marketing agreement to produce solutions based on DDN storage platforms integrated with servers, networking, software and services from Inspur. Read more…

By Doug Black

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

UberCloud Cites Progress in HPC Cloud Computing

January 10, 2017

200 HPC cloud experiments, 80 case studies, and a ton of hands-on experience gained, that’s the harvest of four years of UberCloud HPC Experiments. Read more…

By Wolfgang Gentzsch and Burak Yenier

A Conversation with Women in HPC Director Toni Collis

January 6, 2017

In this SC16 video interview, HPCwire Managing Editor Tiffany Trader sits down with Toni Collis, the director and founder of the Women in HPC (WHPC) network, to discuss the strides made since the organization’s debut in 2014. Read more…

By Tiffany Trader

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

AWS Beats Azure to K80 General Availability

September 30, 2016

Amazon Web Services has seeded its cloud with Nvidia Tesla K80 GPUs to meet the growing demand for accelerated computing across an increasingly-diverse range of workloads. The P2 instance family is a welcome addition for compute- and data-focused users who were growing frustrated with the performance limitations of Amazon's G2 instances, which are backed by three-year-old Nvidia GRID K520 graphics cards. Read more…

By Tiffany Trader

US, China Vie for Supercomputing Supremacy

November 14, 2016

The 48th edition of the TOP500 list is fresh off the presses and while there is no new number one system, as previously teased by China, there are a number of notable entrants from the US and around the world and significant trends to report on. Read more…

By Tiffany Trader

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

Vectors: How the Old Became New Again in Supercomputing

September 26, 2016

Vector instructions, once a powerful performance innovation of supercomputing in the 1970s and 1980s became an obsolete technology in the 1990s. But like the mythical phoenix bird, vector instructions have arisen from the ashes. Here is the history of a technology that went from new to old then back to new. Read more…

By Lynd Stringer

Container App ‘Singularity’ Eases Scientific Computing

October 20, 2016

HPC container platform Singularity is just six months out from its 1.0 release but already is making inroads across the HPC research landscape. It's in use at Lawrence Berkeley National Laboratory (LBNL), where Singularity founder Gregory Kurtzer has worked in the High Performance Computing Services (HPCS) group for 16 years. Read more…

By Tiffany Trader

Dell EMC Engineers Strategy to Democratize HPC

September 29, 2016

The freshly minted Dell EMC division of Dell Technologies is on a mission to take HPC mainstream with a strategy that hinges on engineered solutions, beginning with a focus on three industry verticals: manufacturing, research and life sciences. "Unlike traditional HPC where everybody bought parts, assembled parts and ran the workloads and did iterative engineering, we want folks to focus on time to innovation and let us worry about the infrastructure," said Jim Ganthier, senior vice president, validated solutions organization at Dell EMC Converged Platforms Solution Division. Read more…

By Tiffany Trader

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Leading Solution Providers

D-Wave SC16 Update: What’s Bo Ewald Saying These Days

November 18, 2016

Tucked in a back section of the SC16 exhibit hall, quantum computing pioneer D-Wave has been talking up its new 2000-qubit processor announced in September. Forget for a moment the criticism sometimes aimed at D-Wave. This small Canadian company has sold several machines including, for example, ones to Lockheed and NASA, and has worked with Google on mapping machine learning problems to quantum computing. In July Los Alamos National Laboratory took possession of a 1000-quibit D-Wave 2X system that LANL ordered a year ago around the time of SC15. Read more…

By John Russell

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

Nvidia Sees Bright Future for AI Supercomputing

November 23, 2016

Graphics chipmaker Nvidia made a strong showing at SC16 in Salt Lake City last week. Read more…

By Tiffany Trader

Beyond von Neumann, Neuromorphic Computing Steadily Advances

March 21, 2016

Neuromorphic computing – brain inspired computing – has long been a tantalizing goal. The human brain does with around 20 watts what supercomputers do with megawatts. And power consumption isn’t the only difference. Fundamentally, brains ‘think differently’ than the von Neumann architecture-based computers. While neuromorphic computing progress has been intriguing, it has still not proven very practical. Read more…

By John Russell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

The Exascale Computing Project Awards $39.8M to 22 Projects

September 7, 2016

The Department of Energy’s Exascale Computing Project (ECP) hit an important milestone today with the announcement of its first round of funding, moving the nation closer to its goal of reaching capable exascale computing by 2023. Read more…

By Tiffany Trader

Dell Knights Landing Machine Sets New STAC Records

November 2, 2016

The Securities Technology Analysis Center, commonly known as STAC, has released a new report characterizing the performance of the Knight Landing-based Dell PowerEdge C6320p server on the STAC-A2 benchmarking suite, widely used by the financial services industry to test and evaluate computing platforms. The Dell machine has set new records for both the baseline Greeks benchmark and the large Greeks benchmark. Read more…

By Tiffany Trader

What Knights Landing Is Not

June 18, 2016

As we get ready to launch the newest member of the Intel Xeon Phi family, code named Knights Landing, it is natural that there be some questions and potentially some confusion. Read more…

By James Reinders, Intel

  • arrow
  • Click Here for More Headlines
  • arrow
Share This