NERSC Signs Up for Multi-Petaflop “Cascade” Supercomputer

By Michael Feldman

July 3, 2012

The US Department of Energy’s National Energy Research Scientific Computing Center (NERSC) has ordered a two-petaflop “Cascade” supercomputer, Cray’s next-generation HPC platform. The DOE is shelling out $40 million dollars for the system, including about 6.5 petabytes of the company’s Sonexion storage. The contract covers both hardware and services, which will extend over multiple years. Installation is scheduled for sometime in 2013.

The NERSC acquisition represents Cray’s third publicly announced pre-sale of a Cascade system and the first in the US. The other two deals in the pipeline include a multi-petaflop machine destined for HLRS, at the University of Stuttgart, and a 400-teraflop one for Kyoto University.

Cascade is a big step for Cray. Not only does it represent the company’s first foray in Intel-based supercomputing, but it also fills out Cray’s Adaptive Supercomputing vision to a much greater degree than the previous XT and XE product lines. DARPA, which poured hundreds of millions of dollars into the design via the agency’s High Productivity Computing Systems (HPCS) program, helped to make Cascade a much bigger deal than just a platform refresh.

For example, a good portion of the funding went into developing more sophisticated compilers, tools and libraries, including the creation of the Chapel language, all aimed at making the platform more productive and easier to use. The extra money also allowed Cray the breathing room for a critical system redesign, in particular, the opportunity to ditch its AMD Opteron-only architecture.

Although much of the talk surrounding Cascade has been about putting Intel silicon into Cray hardware, the platform is actually designed to support multiple processor types. According to Cray CEO Peter Ungaro, they’ll be able to build blades with AMD processors, as they do now, as well as those with accelerators, like GPUs and Intel MIC (Xeon Phi) coprocessors, and even blades with future ARM chips, if they so desire. “It’s really going to open up our options to have targeted nodes for targeted workloads,” he told HPCwire.

The key is the new Aries interconnect, which is integrated with PCI Express (PCIe), a standard on-board bus that virtually all server processors will support. Prior to this, Cray’s interconnect technology (SeaStar, then Gemini) was tied to HyperTransport, which restricted the company’s supercomputers to AMD CPUs. With the faster speeds of PCIe 3.0, and its ubiquity, the bus technology is now in a position to serve as the underlying substrate for system networks, even for custom interconnects.

All of this potential heterogeneity is likely to be bypassed by NERSC though, at least initially. At a time when many other national labs are opting for GPUs on their fastest machines, NERSC-7 will be based entirely on Intel Xeon CPUs. No GPU or Intel MIC parts are to be used, although future upgrades with those accelerators are theoretically possible. According to Jeff Broughton, who heads NERSC’s Systems Department, the deployment will be based on “the latest generation of Intel processors available at the time of installation.” Given the 2013 timeframe, those chips could very well be Ivy Bridge CPUs rather than the Sandy Bridge parts in the field today.

By going with the more traditional CPU-only platform for NERSC’s first multi-petaflop super, the DOE lab has bucked a trend begun by other national labs like Oak Ridge, NCSA, and TACC , which are using GPUs or, in the case of TACC, Intel MIC accelerators, to get into the double-digit petaflop realm. NERSC-7 was also originally supposed to be a 10-petaflop machine, but getting there via x86 CPUs (that is, not with an IBM Blue Gene or Fujitsu K-type architecture) is not really economically feasible right now without accelerator add-ons.

According to NERSC director Kathy Yelick, the lab supports 4,500 users running hundreds of different codes, across many science disciplines and there is concern about forcing all that software to be rewritten for PCIe-based GPUs or Intel MIC devices. “Current accelerators have a separate memory space and are configured as coprocessors rather than first-class cores, both features that we are hoping will change,” she explained. “So while we are encouraging users to experiment with low-power processor technology, such as GPUs, in our testbeds, we do not think the time is right to transition all of the users.”

They do expect to move their users to some type of low-power manycore architecture over the next several years, but would like to make this transition just once. The first opportunity is likely to present itself with NERSC-8, the next major system procurement following NERSC-7. By the time that system is deployed a few years down the road, the system planners are probably thinking (or at least hoping) there will be a range of integrated low-power manycore architectures to choose from.

That’s a reasonable bet. Certainly, by the middle of the decade, we should at least see the appearance of NVIDIA’s ARM64-GPU “Maxwell” processor, an AMD server-class APU, and an Intel MIC chip integrated with some big Xeon CPU cores.

In the meantime, it should be relatively straightforward to run current user codes on NERSC-7 hardware since the lab’s existing petascale machine, Hopper, is a Cray XE6 system, and from an application point of view, will be nearly indistinguishable from its successor. Getting those codes to scale up to a machine with about twice the performance of Hopper could be somewhat of a challenge, but NERSC sees many potential candidates, both for simulation (LQCD, fusion, turbulence, astrophysics, chemistry, quantum Monte Carlo, molecular dynamics and cloud resolving climate models) and data analysis (bioinformatics and material screening). Of course, few if any applications are expected to use all two petaflops, but these big machines also function quite nicely as capacity clusters.

NERSC is likely to be only one of a number of US national labs signing up for Cascade supercomputers over the next few years. Given DARPA’s DoD pedigree, we should expect, at the very least, to see some defense labs acquire these next-generation Cray machines as they upgrade their HPC machinery.

Cascade will also be an opportunity for Cray to re-establish its dominance at the top of the supercomputing heap in the face of renewed competition from IBM. In the world’s top 100 systems, Blue Gene supercomputers are now the most numerous single platform, outdistancing Cray XT/XE installations by a 21 to 17 margin. That was the result of the recent surge of Blue Gene/Q deployments over the last six months, which was able to capture a lot of new business as it squared off against the now two-year-old Cray XE6.

Cray is certainly expecting great things from Cascade. Over the past eight years, the company has managed to steadily expand sales of its x86 supercomputing portfolio. Starting with its Red Storm supercomputer in 2004, which led to the company’s first commercial x86-based product, XT3, and then to subsequent platforms, XT4, XT5, XT6 and XE6/XK6, Cray has sold more cabinets with each successive generation. “If we keep that trend going,” says Ungaro, “we’ll be in good shape.”

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!

AI in the News: Rao in at Intel, Ng out at Baidu, Nvidia on at Tencent Cloud

March 26, 2017

Just as AI has become the leitmotif of the advanced scale computing market, infusing much of the conversation about HPC in commercial and industrial spheres, it also is impacting high-level management changes in the industry. Read more…

By Doug Black

Scalable Informatics Ceases Operations

March 23, 2017

On the same day we reported on the uncertain future for HPC compiler company PathScale, we are sad to learn that another HPC vendor, Scalable Informatics, is closing its doors. Read more…

By Tiffany Trader

‘Strategies in Biomedical Data Science’ Advances IT-Research Synergies

March 23, 2017

“Strategies in Biomedical Data Science: Driving Force for Innovation” by Jay A. Etchings is both an introductory text and a field guide for anyone working with biomedical data. Read more…

By Tiffany Trader

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

HFT Firms Turn to Co-Location to Gain Competitive Advantage

High-frequency trading (HFT) is a high-speed, high-stakes world where every millisecond matters. Finding ways to execute trades faster than the competition translates directly to greater revenue for firms, brokerages, and exchanges. Read more…

Google Launches New Machine Learning Journal

March 22, 2017

On Monday, Google announced plans to launch a new peer review journal and “ecosystem” Read more…

By John Russell

Swiss Researchers Peer Inside Chips with Improved X-Ray Imaging

March 22, 2017

Peering inside semiconductor chips using x-ray imaging isn’t new, but the technique hasn’t been especially good or easy to accomplish. Read more…

By John Russell

LANL Simulation Shows Massive Black Holes Break ‘Speed Limit’

March 21, 2017

A new computer simulation based on codes developed at Los Alamos National Laboratory (LANL) is shedding light on how supermassive black holes could have formed in the early universe contrary to most prior models which impose a limit on how fast these massive ‘objects’ can form. Read more…

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

New Japanese Supercomputing Project Targets Exascale

March 14, 2017

Another Japanese supercomputing project was revealed this week, this one from emerging supercomputer maker, ExaScaler Inc., and Keio University. The partners are working on an original supercomputer design with exascale aspirations. Read more…

By Tiffany Trader

Nvidia Debuts HGX-1 for Cloud; Announces Fujitsu AI Deal

March 9, 2017

On Monday Nvidia announced a major deal with Fujitsu to help build an AI supercomputer for RIKEN using 24 DGX-1 servers. Read more…

By John Russell

HPC4Mfg Advances State-of-the-Art for American Manufacturing

March 9, 2017

Last Friday (March 3, 2017), the High Performance Computing for Manufacturing (HPC4Mfg) program held an industry engagement day workshop in San Diego, bringing together members of the US manufacturing community, national laboratories and universities to discuss the role of high-performance computing as an innovation engine for American manufacturing. 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

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. 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

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

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

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

Leading Solution Providers

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. 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

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

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Intel and Trump Announce $7B for Fab 42 Targeting 7nm

February 8, 2017

In what may be an attempt by President Trump to reset his turbulent relationship with the high tech industry, he and Intel CEO Brian Krzanich today announced plans to invest more than $7 billion to complete Fab 42. Read more…

By John Russell

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