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!

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

NSF Seeks Input on Cyberinfrastructure Advances Needed

January 12, 2017

In cased you missed it, the National Science Foundation posted a “Dear Colleague Letter” (DCL) late last week seeking input on needs for the next generation of cyberinfrastructure to support science and engineering. Read more…

By John Russell

NSF Approves Bridges Phase 2 Upgrade for Broader Research Use

January 12, 2017

The recently completed phase 2 upgrade of the Bridges supercomputer at the Pittsburgh Supercomputing Center (PSC) has been approved by the National Science Foundation (NSF) making it now available for research allocations to the national scientific community, according to an announcement posted this week on the XSEDE web site. Read more…

By John Russell

Clemson Software Optimizes Big Data Transfers

January 11, 2017

Data-intensive science is not a new phenomenon as the high-energy physics and astrophysics communities can certainly attest, but today more and more scientists are facing steep data and throughput challenges fueled by soaring data volumes and the demands of global-scale collaboration. Read more…

By Tiffany Trader

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…

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

FPGA-Based Genome Processor Bundles Storage

January 6, 2017

Bio-processor developer Edico Genome is collaborating with storage specialist Dell EMC to bundle computing and storage for analyzing gene-sequencing data. Read more…

By George Leopold

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

Fast Rewind: 2016 Was a Wild Ride for HPC

December 23, 2016

Some years quietly sneak by – 2016 not so much. It’s safe to say there are always forces reshaping the HPC landscape but this year’s bunch seemed like a noisy lot. Among the noisemakers: TaihuLight, DGX-1/Pascal, Dell EMC & HPE-SGI et al., KNL to market, OPA-IB chest thumping, Fujitsu-ARM, new U.S. President-elect, BREXIT, JR’s Intel Exit, Exascale (whatever that means now), NCSA@30, whither NSCI, Deep Learning mania, HPC identity crisis…You get the picture. Read more…

By John Russell

AWI Uses New Cray Cluster for Earth Sciences and Bioinformatics

December 22, 2016

The Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), headquartered in Bremerhaven, Germany, is one of the country's premier research institutes within the Helmholtz Association of German Research Centres, and is an internationally respected center of expertise for polar and marine research. In November 2015, AWI awarded Cray a contract to install a cluster supercomputer that would help the institute accelerate time to discovery. Now the effort is starting to pay off. Read more…

By Linda Barney

Addison Snell: The ‘Wild West’ of HPC Disaggregation

December 16, 2016

We caught up with Addison Snell, CEO of HPC industry watcher Intersect360, at SC16 last month, and Snell had his expected, extensive list of insights into trends driving advanced-scale technology in both the commercial and research sectors. Read more…

By Doug Black

KNUPATH Hermosa-based Commercial Boards Expected in Q1 2017

December 15, 2016

Last June tech start-up KnuEdge emerged from stealth mode to begin spreading the word about its new processor and fabric technology that’s been roughly a decade in the making. 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

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

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

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

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

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

New Genomics Pipeline Combines AWS, Local HPC, and Supercomputing

September 22, 2016

Declining DNA sequencing costs and the rush to do whole genome sequencing (WGS) of large cohort populations – think 5000 subjects now, but many more thousands soon – presents a formidable computational challenge to researchers attempting to make sense of large cohort datasets. Read more…

By John Russell

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

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

Deep Learning Paves Way for Better Diagnostics

September 19, 2016

Stanford researchers are leveraging GPU-based machines in the Amazon EC2 cloud to run deep learning workloads with the goal of improving diagnostics for a chronic eye disease, called diabetic retinopathy. The disease is a complication of diabetes that can lead to blindness if blood sugar is poorly controlled. It affects about 45 percent of diabetics and 100 million people worldwide, many in developing nations. Read more…

By Tiffany Trader

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