NVIDIA Launches First Kepler GPUs at Gamers; HPC Version Waiting in the Wings

By Michael Feldman

March 22, 2012

NVIDIA debuted its much-talked-about Kepler GPU this week, promising much better performance and energy efficiency than its previous generation Fermi-based products. The first offerings are mid-range graphics cards targeted at the heart of the desktop and notebook market, but the more powerful second-generation Kepler GPU for high performance computing is already in the pipeline.

The two new products introduced this week, the GeForce GTX 680 for desktop systems and the GeForce 600M GPUs for notebooks, are twice as energy efficient as their Fermi-based counterparts, according to NVIDIA. And although they represent more powerful graphics processors than the previous generation, the overriding design theme of the new architecture is performance per watt, rather than performance per square millimeter. According to Sumit Gupta, NVIDIA’s senior director of the Tesla GPU Computing business unit, that’s a fundamental change in the company’s architectural strategy. “This is the first time that power is a higher order concern than area,” he says.

That’s because, like nearly every chipmaker on the planet, NVIDIA’s fastest growing market segment is the mobile and notebook/ultrabook space. This architectural emphasis on energy efficiency also dovetails rather nicely with the GPU computing market, where power consumption is also a huge factor. That’s especially true for the Tesla GPU parts that end up in energy-sucking HPC servers. “Every market we’re in has become power sensitive,” says Gupta.

Upping the power efficiency in Kepler relied heavily on a tried-and-true technique, namely increasing the core count while lowering the clock speed. But the architecture is somewhat different. Underneath the covers, the cores are collected into what NVIDIA calls their Streaming Multiprocessors (SMs). In the Fermi version there were only 32 cores per SM. In the Kepler implementation, they reduced the control logic disproportionally and were able to squeeze in 192.

Boosting the core numbers was a no-brainer, given they were moving from the 40nm process technology with Fermi, to the 28nm node for Kepler. In the case of the GeForce GTX 680, for example, there are 1536 cores — three times as many as in the high-end Fermi GPUs, which topped out at 512 cores. At the same time they reduced the clock frequency from 1.5 GHz on the Fermi chip to just a shade over 1 GHz. Although each core is now doing less work, because there are more of them, throughput increases and does so with lower energy consumption.

CPU chipmakers have employed this strategy as well. But because of the greater complexity of the individual CPU cores and their reliance on limited memory bandwidth, core count increases are starting to stagnate (no CPU make ever tripled core count in one generation). Also, since a lot of applications are dependent on single-threaded performance, CPU chip makers try to hold the line on clock speed as much as possible. Ratcheting down the clock speed by a third, as NVIDIA has done here, is unheard for a CPU product.

For Kepler, NVIDIA is claiming a doubling of performance per watt compared to the Fermi-generation GeForce GTX 580. For real gaming applications, the new Kepler products are getting between 1.1 to and 2 times better the performance per watt. In some cases though, it can do even better.

For example, NVIDIA used their Samaritan demo, which illustrates photorealistic gaming, to show a 3X performance boost. Up until this week, that demo required three GeForce GTX 580 cards, drawing a total of 732 watts. It can now be run with a single 195-watt GeForce GTX 680.

To support all the extra throughput, memory bandwidth has been kicked up significantly. The interface on the GTX 680 supports 6.0 Gbps, which is 50 percent more than the 4.0 Gbps available on the GTX 580. According to Gupta, that’s the highest memory bandwidth for any commodity-based chip, NVIDIA or otherwise.

All of these architectural changes — more cores, slower clocks, and more memory bandwidth — will carry over into the second version of the Kepler GPU, a higher-end design which will be aimed primarily at GPU computing applications. This is the one the next-generation Tesla products will be based upon, and the one that will initially end up in two of the most powerful supercomputers in the world: Blue Waters at NCSA and Titan at ORNL.

According to Gupta, the second Kepler implementation will include a lot of capability not present in these first gaming-oriented products. In particular, it will have a lot more double-precision capability (which is not required for most graphics applications) and include new compute-specific features. And of course the raw power of these chips will be quite a bit higher than the mid-range graphics version introduced this week.

Although the company is not yet giving any of the speeds and feeds on the second Kepler, one would expect the core count and peak double precision performance to be two to three times higher, and memory bandwidth to get at least a 50 percent bump. Clock speed will almost certainly be whittled down from the current 1.3 GHz on the Tesla M2090, but perhaps not so aggressively as in these first Kepler gaming parts.

Presumably, the NVIDIA will stick with its 225 watt power envelope for the Tesla lineup, so the engineers just have to balance the core count and clock to land on that thermal design point. Given that power ceiling and the core count increase, NVIDIA should be able to deliver a Tesla GPU with between 1.3 and 1.5 teraflops of double precision performance. On the other hand, there is probably a case to be made to also offer less performant parts that consume less power.

In any case we’ll know soon enough. NVIDIA will probably do their paper launch of the HPC Kepler at the company’s GPU Technology Conference in May. And according to Gupta, the company is on track to put this version into production in Q4. If that goes according to plan, the new Kepler GPUs will be up and running on supercomputers before the end of the year.

Related Articles

NVIDIA Revs Up Tesla GPU

GPUs Will Morph ORNL’s Jaguar Into 20-Petaflop Titan

NCSA Signs Up Cray for Blue Waters Redo

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!

Is Data Science the Fourth Pillar of the Scientific Method?

April 18, 2019

Nvidia CEO Jensen Huang revived a decade-old debate last month when he said that modern data science (AI plus HPC) has become the fourth pillar of the scientific method. While some disagree with the notion that statistic Read more…

By Alex Woodie

At ASF 2019: The Virtuous Circle of Big Data, AI and HPC

April 18, 2019

We've entered a new phase in IT -- in the world, really -- where the combination of big data, artificial intelligence, and high performance computing is pushing the bounds of what's possible in business and science, in w Read more…

By Alex Woodie with Doug Black and Tiffany Trader

Google Open Sources TensorFlow Version of MorphNet DL Tool

April 18, 2019

Designing optimum deep neural networks remains a non-trivial exercise. “Given the large search space of possible architectures, designing a network from scratch for your specific application can be prohibitively expens Read more…

By John Russell

HPE Extreme Performance Solutions

HPE and Intel® Omni-Path Architecture: How to Power a Cloud

Learn how HPE and Intel® Omni-Path Architecture provide critical infrastructure for leading Nordic HPC provider’s HPCFLOW cloud service.

powercloud_blog.jpgFor decades, HPE has been at the forefront of high-performance computing, and we’ve powered some of the fastest and most robust supercomputers in the world. Read more…

IBM Accelerated Insights

Bridging HPC and Cloud Native Development with Kubernetes

The HPC community has historically developed its own specialized software stack including schedulers, filesystems, developer tools, container technologies tuned for performance and large-scale on-premises deployments. Read more…

Interview with 2019 Person to Watch Michela Taufer

April 18, 2019

Today, as part of our ongoing HPCwire People to Watch focus series, we are highlighting our interview with 2019 Person to Watch Michela Taufer. Michela -- the General Chair of SC19 -- is an ACM Distinguished Scientist. Read more…

By HPCwire Editorial Team

At ASF 2019: The Virtuous Circle of Big Data, AI and HPC

April 18, 2019

We've entered a new phase in IT -- in the world, really -- where the combination of big data, artificial intelligence, and high performance computing is pushing Read more…

By Alex Woodie with Doug Black and Tiffany Trader

Interview with 2019 Person to Watch Michela Taufer

April 18, 2019

Today, as part of our ongoing HPCwire People to Watch focus series, we are highlighting our interview with 2019 Person to Watch Michela Taufer. Michela -- the Read more…

By HPCwire Editorial Team

Intel Gold U-Series SKUs Reveal Single Socket Intentions

April 18, 2019

Intel plans to jump into the single socket market with a portion of its just announced Cascade Lake microprocessor line according to one media report. This isn Read more…

By John Russell

BSC Researchers Shrink Floating Point Formats to Accelerate Deep Neural Network Training

April 15, 2019

Sometimes calculating solutions as precisely as a computer can wastes more CPU resources than is necessary. A case in point is with deep learning. In early stag Read more…

By Ken Strandberg

Intel Extends FPGA Ecosystem with 10nm Agilex

April 11, 2019

The insatiable appetite for higher throughput and lower latency – particularly where edge analytics and AI, network functions, or for a range of datacenter ac Read more…

By Doug Black

Nvidia Doubles Down on Medical AI

April 9, 2019

Nvidia is collaborating with medical groups to push GPU-powered AI tools into clinical settings, including radiology and drug discovery. The GPU leader said Monday it will collaborate with the American College of Radiology (ACR) to provide clinicians with its Clara AI tool kit. The partnership would allow radiologists to leverage AI techniques for diagnostic imaging using their own clinical data. Read more…

By George Leopold

Digging into MLPerf Benchmark Suite to Inform AI Infrastructure Decisions

April 9, 2019

With machine learning and deep learning storming into the datacenter, the new challenge is optimizing infrastructure choices to support diverse ML and DL workfl Read more…

By John Russell

AI and Enterprise Datacenters Boost HPC Server Revenues Past Expectations – Hyperion

April 9, 2019

Building on the big year of 2017 and spurred in part by the convergence of AI and HPC, global revenue for high performance servers jumped 15.6 percent last year Read more…

By Doug Black

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

Why Nvidia Bought Mellanox: ‘Future Datacenters Will Be…Like High Performance Computers’

March 14, 2019

“Future datacenters of all kinds will be built like high performance computers,” said Nvidia CEO Jensen Huang during a phone briefing on Monday after Nvidia revealed scooping up the high performance networking company Mellanox for $6.9 billion. Read more…

By Tiffany Trader

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

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

It’s Official: Aurora on Track to Be First US Exascale Computer in 2021

March 18, 2019

The U.S. Department of Energy along with Intel and Cray confirmed today that an Intel/Cray supercomputer, "Aurora," capable of sustained performance of one exaf 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

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

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

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

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

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

Arm Unveils Neoverse N1 Platform with up to 128-Cores

February 20, 2019

Following on its Neoverse roadmap announcement last October, Arm today revealed its next-gen Neoverse microarchitecture with compute and throughput-optimized si Read more…

By Tiffany Trader

France to Deploy AI-Focused Supercomputer: Jean Zay

January 22, 2019

HPE announced today that it won the contract to build a supercomputer that will drive France’s AI and HPC efforts. The computer will be part of GENCI, the Fre Read more…

By Tiffany Trader

Intel Launches Cascade Lake Xeons with Up to 56 Cores

April 2, 2019

At Intel's Data-Centric Innovation Day in San Francisco (April 2), the company unveiled its second-generation Xeon Scalable (Cascade Lake) family and debuted it Read more…

By Tiffany Trader

Oil and Gas Supercloud Clears Out Remaining Knights Landing Inventory: All 38,000 Wafers

March 13, 2019

The McCloud HPC service being built by Australia’s DownUnder GeoSolutions (DUG) outside Houston is set to become the largest oil and gas cloud in the world th Read more…

By Tiffany Trader

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

Air Force Research Laboratory Unveils First Shared, Classified DoD HPC Capability

February 28, 2019

In a ceremony on Tuesday, the Air Force Research Laboratory unveiled four new computing clusters, providing the capability for what it is calling the first-ever 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