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 industry updates delivered to you every week!

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from its predecessors, including the red-hot H100 and A100 GPUs. Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. While Nvidia may not spring to mind when thinking of the quant Read more…

2024 Winter Classic: Meet the HPE Mentors

March 18, 2024

The latest installment of the 2024 Winter Classic Studio Update Show features our interview with the HPE mentor team who introduced our student teams to the joys (and potential sorrows) of the HPL (LINPACK) and accompany Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the field was normalized for boys in 1969 when the Apollo 11 missi Read more…

Apple Buys DarwinAI Deepening its AI Push According to Report

March 14, 2024

Apple has purchased Canadian AI startup DarwinAI according to a Bloomberg report today. Apparently the deal was done early this year but still hasn’t been publicly announced according to the report. Apple is preparing Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimization algorithms to iteratively refine their parameters until Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimizat Read more…

PASQAL Issues Roadmap to 10,000 Qubits in 2026 and Fault Tolerance in 2028

March 13, 2024

Paris-based PASQAL, a developer of neutral atom-based quantum computers, yesterday issued a roadmap for delivering systems with 10,000 physical qubits in 2026 a Read more…

India Is an AI Powerhouse Waiting to Happen, but Challenges Await

March 12, 2024

The Indian government is pushing full speed ahead to make the country an attractive technology base, especially in the hot fields of AI and semiconductors, but Read more…

Charles Tahan Exits National Quantum Coordination Office

March 12, 2024

(March 1, 2024) My first official day at the White House Office of Science and Technology Policy (OSTP) was June 15, 2020, during the depths of the COVID-19 loc Read more…

AI Bias In the Spotlight On International Women’s Day

March 11, 2024

What impact does AI bias have on women and girls? What can people do to increase female participation in the AI field? These are some of the questions the tech Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Analyst Panel Says Take the Quantum Computing Plunge Now…

November 27, 2023

Should you start exploring quantum computing? Yes, said a panel of analysts convened at Tabor Communications HPC and AI on Wall Street conference earlier this y Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Training of 1-Trillion Parameter Scientific AI Begins

November 13, 2023

A US national lab has started training a massive AI brain that could ultimately become the must-have computing resource for scientific researchers. Argonne N Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire