Jaguar Scales TOP500

By Nicole Hemsoth

November 19, 2009

When first deployed in 2005, the Jaguar supercomputer at Oak Ridge National Lab booted up with a peak speed of only 26 teraflops. Since then it has been continuously enhanced with additional cabinets and new AMD Opteron processors. The latest upgrade involved replacing the quad-core Opteron chips with AMD’s latest six-core version, which propelled it to the number one spot on the newly announced TOP500 list.

With a Linpack mark of 1.759 petaflops, it outran the number two Roadrunner system by a good 750 teraflops. Jaguar also managed to come out on top in the HPC Challenge STREAM benchmark, with a sustainable memory bandwidth of 398 terabytes per second.

We asked John Fruehe, AMD’s director of Opteron product marketing, and Buddy Bland, the project director for the ORNL Leadership Computing Facility, about the significance of this accomplishment and what it means for the most demanding supercomputing applications.

HPCwire: What do you think is the significance of the first multi-petaflop machine powered purely by x86 CPUs?

John Fruehe: The number one position is really significant because it shows a culmination of supercomputing’s shift to industry-standard systems. These mammoth, world-class machines are no longer out of reach for the more average academic or enterprise HPC user. The market for a Cray XT5 or an Appro HyperCluster goes beyond the U.S. national labs and you see HPC customers monitoring regional weather patterns or searching out oil and gas reserves on the very same systems as what you have in the Top 10.

Let’s face it, most folks can’t go out and buy an Earth Simulator or a Blue Gene. x86 has made world-class supercomputing a lot more democratic. And of course, this number one win shows the raw processing capability of x86 and specifically AMD’s brand of x86 in the form of the game-changing Opteron processor. In the past, larger, more expensive and proprietary systems ruled the top of the chart. Today, more economical and scalable x86 platforms are rapidly becoming the norm for supercomputing and that gives customers more flexibility and choice.

HPCwire: In performance-per-watt, Jaguar still lags other more exotic supercomputing architectures. Given the escalating concern of energy efficiency in these large-scale machines, what does that say about the role of the x86 in future supercomputing systems?

Fruehe: Certainly an architecture like Cell is quite the power miser. But as we’ve seen with “Roadrunner,” frankly, the Cell architecture needs Opteron to get the job done. A system like “Jaguar” or any of the other systems that are near the top of the list are deployed to do a specific job. Many times, power is certainly a concern, but not the overriding concern.

For more mainstream HPC, I think we will continue to see x86 dominate because of economics and because it delivers the performance and is what the industry knows best. We’ll continue to see the additional low-power improvements that AMD is implementing — above and beyond what we’ve already done — take hold and bring HPC overall more in line with an acceptable level of power draw.

As AMD moves to its future generations, you will continue to see an emphasis on power efficiency in the data center as we continue to drive greater amounts of performance and scalability while staying within approximately the same power/thermal ranges, resulting in increasingly greater performance per watt with each generation.

HPCwire: Jaguar’s Linpack performance is certainly impressive. But what types of applications are going to be able to fully utilize the scale of this machine?

Buddy Bland: While Linpack is a test of the computational performance of computer systems, Jaguar was designed to run applications that are demanding on all of the aspects of the system. Within just a few weeks of completing the upgrade of Jaguar, we have several applications that are scaling to use the full performance of the system. Three of this year’s Gordon Bell award finalists are running on Jaguar using the full scope of the machine. We also have many of our key applications in areas such as materials science, computational chemistry, fusion energy, superconductivity, and bioenergy using all of Jaguar today. We expect that as the remainder of our users get access to the upgraded system, we will see most of our applications taking full advantage of the size of the system.

HPCwire: What other types of applications are slated to get time on Jaguar?

Bland: The DOE INCITE program allocates time on the leadership systems: Jaguar at ORNL and Intrepid at ANL. A small number of scientifically important, time critical applications from government laboratories, academia and industry are awarded large blocks of time. In 2009, 38 projects received allocations of time on Jaguar as part of the INCITE program.

Jaguar is supporting some of the most important projects of our time such as:

  • understanding the causes, impacts, and mitigations of climate change.
  • energy storage such as new batteries and capacitors, which are needed to make technologies like solar cells and wind power more useful.
  • fusion energy which will harness the power that fuels the sun to generate clean, carbon-free power.
  • bioenergy projects that are understanding how to convert waste cellulose products such a switch grass into renewable biofuels.
  • nuclear power projects that are designing new types of reactors that are safer and do not pose the threats of nuclear proliferation.

HPCwire: Is there an upgrade path for Jaguar beyond its current configuration?

Bland: The socket replaceable line of processors from AMD and the board compatible line of systems from Cray have been a key part of the success of Jaguar. We have been able to upgrade cabinets from single-core to dual-core to quad-core and now to 6-core processors while preserving much of our investment. This allowed ORNL and Cray to upgrade Jaguar, stepping up from 26 teraflops to 54 TF, 119 TF, 263 TF, and now 2.3 petaflops. Without this series of increasingly powerful systems, we would not have been able to continuously move the users and their applications to higher and higher performance, resulting in the scientific success we have seen from the system. Cray’s line of systems may yet provide another upgrade path for Jaguar.

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!

TACC Helps ROSIE Bioscience Gateway Expand its Impact

April 26, 2017

Biomolecule structure prediction has long been challenging not least because the relevant software and workflows often require high-end HPC systems that many bioscience researchers lack easy access to. Read more…

By John Russell

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

IBM, Nvidia, Stone Ridge Claim Gas & Oil Simulation Record

April 25, 2017

IBM, Nvidia, and Stone Ridge Technology today reported setting the performance record for a “billion cell” oil and gas reservoir simulation. Read more…

By John Russell

ASC17 Makes Splash at Wuxi Supercomputing Center

April 24, 2017

A record-breaking twenty student teams plus scores of company representatives, media professionals, staff and student volunteers transformed a formerly empty hall inside the Wuxi Supercomputing Center into a bustling hub of HPC activity, kicking off day one of 2017 Asia Student Supercomputer Challenge (ASC17). Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Remote Visualization Optimizing Life Sciences Operations and Care Delivery

As patients continually demand a better quality of care and increasingly complex workloads challenge healthcare organizations to innovate, investing in the right technologies is key to ensuring growth and success. Read more…

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of a new generation of chips designed specifically for deep learning workloads. Read more…

By Alex Woodie

Musk’s Latest Startup Eyes Brain-Computer Links

April 21, 2017

Elon Musk, the auto and space entrepreneur and severe critic of artificial intelligence, is forming a new venture that reportedly will seek to develop an interface between the human brain and computers. Read more…

By George Leopold

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

ASC17 Makes Splash at Wuxi Supercomputing Center

April 24, 2017

A record-breaking twenty student teams plus scores of company representatives, media professionals, staff and student volunteers transformed a formerly empty hall inside the Wuxi Supercomputing Center into a bustling hub of HPC activity, kicking off day one of 2017 Asia Student Supercomputer Challenge (ASC17). Read more…

By Tiffany Trader

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of a new generation of chips designed specifically for deep learning workloads. Read more…

By Alex Woodie

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Read more…

By John Russell

Knights Landing Processor with Omni-Path Makes Cloud Debut

April 18, 2017

HPC cloud specialist Rescale is partnering with Intel and HPC resource provider R Systems to offer first-ever cloud access to Xeon Phi "Knights Landing" processors. The infrastructure is based on the 68-core Intel Knights Landing processor with integrated Omni-Path fabric (the 7250F Xeon Phi). Read more…

By Tiffany Trader

CERN openlab Explores New CPU/FPGA Processing Solutions

April 14, 2017

Through a CERN openlab project known as the ‘High-Throughput Computing Collaboration,’ researchers are investigating the use of various Intel technologies in data filtering and data acquisition systems. Read more…

By Linda Barney

DOE Supercomputer Achieves Record 45-Qubit Quantum Simulation

April 13, 2017

In order to simulate larger and larger quantum systems and usher in an age of “quantum supremacy,” researchers are stretching the limits of today’s most advanced supercomputers. Read more…

By Tiffany Trader

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference phase of neural networks (NN). 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

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

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

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

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

Leading Solution Providers

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

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

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

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. 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

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

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

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