Cray Unveils Its First GPU Supercomputer

By Michael Feldman

May 24, 2011

Cray has released the details of its GPU-equipped supercomputer: the XK6. The machine is a derivative of the XE6, an AMD Opteron-based machine that the company announced a year ago. Although Cray is calling this week’s announcement the XK6 launch, systems will not be available until the second half of the year.

Cray’s pitch for the XK6 is that it enables applications to be productive with GPUs at scale. According to Barry Bolding, vice president of Cray’s products division, they are unique in the GPU computing space because of their long-term commitment to heterogeneous computing and their track record for building productive petascale systems. In addition, he points out that Cray has a legacy of experience with vector-based supercomputing and their associated compilers, most recently with their X2 super, aka “Black Widow.”

Hardware-wise, though, the XK6 is not that different from its CPU-based brethren. The blade is basically a variant of the XE6, replacing four of the eight AMD Opteron sockets with NVIDIA Tesla GPU modules. Each four-node blade consists of two Gemini interconnect chips, four Opteron CPUs, and four NVIDIA Tesla 20-series GPUs. The Tesla in this case is the X2090, a compact form factor of the M2090 module that was introduced last week. Like the M2090, the X2090 sports a 665 gigaflop (double precision) GPU, 6 GB of GDDR5, and 178 GB/second of memory bandwidth. A XK6 cabinet can house up to 24 blades (96 nodes), which will deliver something in the neighborhood of 70 teraflops.

Each XK6 node in the blade pairs a single X2090 GPU with an AMD Interlagos CPU (Opteron 6200), along with 16 or 32 GB of 1600 MHz DDR3 memory. That’s a rather CPU-rich configuration for a GPU-based server, given that many commodity clusters use two, four, or even eight graphics devices per x86 processor. And in many cases those processors are not top-of-the-line Xeons or Opterons.

According to Bolding, their thinking here is that not all supercomputing workloads are able to take maximum advantage of the GPU’s capability, so they’ve opted for a fairly conservative processor mix. “We really envision some applications spending a considerable amount of time running on just the x86 portion of the system,” he told HPCwire. “So we really want to have a balance between scalar and accelerator.”

On the other hand, some customers are likely to have applications that are already highly tuned for GPUs, and in this case would want a system with a higher GPU:CPU ratio. Bolding says, for those users they are willing to build custom machines with a richer GPU configuration, but it would not be the standard XK6 and would entail more than just a tweak to those blades.

Besides the hardware, the XK6 will inherit software stack and programming environment from the XE6, including the Cray Linux Environment (CLE). Added on top will be GPU-specific libraries and tools like NVIDIA’s CUDA SDK for programming the Tesla components. GPU support will also be provided by some of the third-party software that Cray currently resells, like the PGI compilers. The PGI compiler suite has already been extended to generate code for GPUs, and is being integrated and tested with the XK6 . The CAPS enterprise HMPP product for GPUs is also available, but unlike PGI is not currently part of XK6 test suite, and is not being resold by Cray.

Cray also will be developing additional GPU compilers, runtime libraries, and tools, as well as bringing in third-party software, such as EM Photonics’ CULA library, to make the environment richer and more productive. The idea here is to bring GPU acceleration in line with its Adaptive Supercomputing approach. The ultimate goal is to be able to write source code that could automatically be transformed to run on either CPUs, GPUs or some mix of the two. The goal is not just to deliver performance, says Bolding, but to “get your codes to better performance faster.”

To propel that vision, Cray is developing its own OpenMP-based compiler that will be targeted for GPU acceleration. This is a higher-level programming model than CUDA, using special directives within the application source to generate GPU code, much like what is available from PGI today. Unlike that offering however, the OpenMP version from Cray is based on standardized OpenMP directives designed to address hardware accelerators. A pre-production version will be available to selected customers, says Bolding, and will support both Fortran and C.

The directives-based programming tools for GPUs is a key part of Cray’s strategy to turn the XK6 into a productive GPU machine, and an attempt to differentiate it from the current crop of GPU-equipped clusters. Bolding says they expect to get the majority of performance available from lower level programming environments like CUDA, but in a much more productive and portable environment. And even though Cray is developing an OpenMP compiler, their overarching goal is to provide a standard, high-level programming environment that is portable across accelerators. “We really believe that a good programming model has to be hardware independent,” said Bolding.

The whole idea of GPUs in supercomputers, of course, is to accelerate codes amenable to data parallelism. One application set Cray envisions for these supers is weather and climate modeling, an area the company has been particularly successful in. For weather prediction, code acceleration can be especially critical, given the requirement is to deliver accurate results in real time. And for this application, model accuracy is directly related to floating point horsepower.

For example, it is estimated that for a weather forecasting model with a horizontal grid granularity of 40 km, one would need 0.4 petaflops. But to refine that granularity to 10 km, one would need a 20 petaflop system. The floating point requirements are similar for providing greater levels of granularity in climate simulations, but without the need to deliver results in real-time. Although these codes scale well enough on CPUs, the prospect of buying a system with 50 times as many processors to deliver more accurate results is daunting from both an upfront cost basis and the ongoing expense of powering such a system.

Today, the most feasible way to accomplish this level of performance boost is with accelerators. Not that GPUs are particularly cheap. An X2090 is likely to be four to five times as expensive as a top-of-the-line Opteron. But since a 20-series Tesla delivers about 10 times the raw floating point performance at only about twice the power consumption, a GPU solution makes sense as long as the codes can extract those extra FLOPS.

Once you’ve made the initial outlay, though, the XK6 is relatively easy to upgrade. According to Bolding, the next-generation GPUs, such as the future Kepler parts, will be able to be inserted into existing machines with just a module swap on the blade. Once those next-gen GPUs are available, Cray estimates these supercomputers will be able to scale up to 50 peak petaflops.

Also, one doesn’t have to build a pure XK6 machine. The GPU blades can be mixed into existing XE6 configurations, which themselves can be constructed from the older XT6 systems via the insertion of the Gemini interconnect.

Cray’s first XK6 order represents such an upgrade. The Swiss National Supercomputing Centre (CSCS) will use their existing XE6m system as the foundation for a multi-cabinet Cray XK6. The system is to be used to support scientific research in weather forecasting, climatology, chemistry, physics, material sciences, geology, biology, genetics, experimental medicine, astronomy, mathematics and computer sciences.

For the Swiss or anyone else to experience all this GPU goodness, they will have to wait for at least a few months. While the availability of the X2090 coincides with that of the M2090 announced last week, AMD’s Opteron 6200 isn’t expected to hit the streets until Q3. Whether Cray has other dependencies associated with availability, Bolding wouldn’t say.

Cray, of course, could have constructed a GPU machine last year based on the Magny-Cours CPU (Opteron 6100) and X2070 GPU.  HP, IBM, SGI, and practically every other HPC cluster vendor came up with a GPU offering in 2010. But according to Bolding, the XK6 is a more thought-out approach and will be the more productive machine.

“We could have come out with something earlier that wasn’t a complete Cray product, in other words, just a bunch of hardware and a mish-mash of open source software, but we chose not to,” he said. ”Our best mapping of a complete HPC product to the market aligned with the current Cray XK6 timeframe.”

“We’re not first to the party here, but we’re hoping we’re the best dancer,” he added.

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 Launches Commercial Quantum Network with Samsung, ORNL

December 14, 2017

In the race to commercialize quantum computing, IBM is one of several companies leading the pack. Today, IBM announced it had signed JPMorgan Chase, Daimler AG, Samsung and a number of other corporations to its IBM Q Net Read more…

By Tiffany Trader

TACC Researchers Test AI Traffic Monitoring Tool in Austin

December 13, 2017

Traffic jams and mishaps are often painful and sometimes dangerous facts of life. At this week’s IEEE International Conference on Big Data being held in Boston, researchers from TACC and colleagues will present a new Read more…

By HPCwire Staff

AMD Wins Another: Baidu to Deploy EPYC on Single Socket Servers

December 13, 2017

When AMD introduced its EPYC chip line in June, the company said a portion of the line was specifically designed to re-invigorate a single socket segment in what has become an overwhelmingly two-socket landscape in the d Read more…

By John Russell

HPE Extreme Performance Solutions

Explore the Origins of Space with COSMOS and Memory-Driven Computing

From the formation of black holes to the origins of space, data is the key to unlocking the secrets of the early universe. Read more…

Microsoft Wants to Speed Quantum Development

December 12, 2017

Quantum computing continues to make headlines in what remains of 2017 as several tech giants jockey to establish a pole position in the race toward commercialization of quantum. This week, Microsoft took the next step in Read more…

By Tiffany Trader

IBM Launches Commercial Quantum Network with Samsung, ORNL

December 14, 2017

In the race to commercialize quantum computing, IBM is one of several companies leading the pack. Today, IBM announced it had signed JPMorgan Chase, Daimler AG, Read more…

By Tiffany Trader

AMD Wins Another: Baidu to Deploy EPYC on Single Socket Servers

December 13, 2017

When AMD introduced its EPYC chip line in June, the company said a portion of the line was specifically designed to re-invigorate a single socket segment in wha Read more…

By John Russell

Microsoft Wants to Speed Quantum Development

December 12, 2017

Quantum computing continues to make headlines in what remains of 2017 as several tech giants jockey to establish a pole position in the race toward commercializ Read more…

By Tiffany Trader

HPC Iron, Soft, Data, People – It Takes an Ecosystem!

December 11, 2017

Cutting edge advanced computing hardware (aka big iron) does not stand by itself. These computers are the pinnacle of a myriad of technologies that must be care Read more…

By Alex R. Larzelere

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Microsoft Spins Cycle Computing into Core Azure Product

December 5, 2017

Last August, cloud giant Microsoft acquired HPC cloud orchestration pioneer Cycle Computing. Since then the focus has been on integrating Cycle’s organization Read more…

By John Russell

GlobalFoundries, Ayar Labs Team Up to Commercialize Optical I/O

December 4, 2017

GlobalFoundries (GF) and Ayar Labs, a startup focused on using light, instead of electricity, to transfer data between chips, today announced they've entered in Read more…

By Tiffany Trader

HPE In-Memory Platform Comes to COSMOS

November 30, 2017

Hewlett Packard Enterprise is on a mission to accelerate space research. In August, it sent the first commercial-off-the-shelf HPC system into space for testing Read more…

By Tiffany Trader

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute Read more…

By Tiffany Trader

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

AMD Showcases Growing Portfolio of EPYC and Radeon-based Systems at SC17

November 13, 2017

AMD’s charge back into HPC and the datacenter is on full display at SC17. Having launched the EPYC processor line in June along with its MI25 GPU the focus he Read more…

By John Russell

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Japan Unveils Quantum Neural Network

November 22, 2017

The U.S. and China are leading the race toward productive quantum computing, but it's early enough that ultimate leadership is still something of an open questi Read more…

By Tiffany Trader

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

Leading Solution Providers

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Tensors Come of Age: Why the AI Revolution Will Help HPC

November 13, 2017

Thirty years ago, parallel computing was coming of age. A bitter battle began between stalwart vector computing supporters and advocates of various approaches to parallel computing. IBM skeptic Alan Karp, reacting to announcements of nCUBE’s 1024-microprocessor system and Thinking Machines’ 65,536-element array, made a public $100 wager that no one could get a parallel speedup of over 200 on real HPC workloads. Read more…

By John Gustafson & Lenore Mullin

Flipping the Flops and Reading the Top500 Tea Leaves

November 13, 2017

The 50th edition of the Top500 list, the biannual publication of the world’s fastest supercomputers based on public Linpack benchmarking results, was released Read more…

By Tiffany Trader

Intel Launches Software Tools to Ease FPGA Programming

September 5, 2017

Field Programmable Gate Arrays (FPGAs) have a reputation for being difficult to program, requiring expertise in specialty languages, like Verilog or VHDL. Easin Read more…

By Tiffany Trader

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