Breaking: Detailed Results from Today’s Top 500 Fastest Supercomputers List

By Nicole Hemsoth

June 23, 2014

Greetings from Germany and the International Supercomputing Conference (ISC14) where, as happens each year, the bi-annual list of the top 500 fastest supercomputers is unveiled.

Usually, this happens with a great deal of fanfare and speculation over which machine will take the top position. However, this year, there is little surprise in the finding that the Chinese Tianhe-2 system, which blew all others out of the water when it was announced last year, held firmly onto its number one position. While you can view the specs of each of the machines in more detail at the TOP500 site, we wanted to use this time to gauge some of the overarching trends we’ve been observing in terms of performance curves over time, accelerator adoption, architecture choices and more. In short, after you browse this very familiar top ten, take a look at what’s really happening…

Top500_Top10

To review, the Tianhe-2 system, which stands at 33.86 petaflops (compared to the number two system at Oak Ridge National Lab, the Cray “Titan” machine, which offers 17.59 petaflops/s) has 16,000 nodes, each of which are outfitted with two Ivy Bridge and three Xeon Phis for a total of over 3 million cores is going to be a tough one to beat. As we noted earlier this year, China has plans to continue the build-out of this system in hopes of reaching exascale potential. The system is unique with a number of homegrown parts, including the TH Express-2 interconnect, OS, tooling and front-end processors. While it may be a powerhouse, the energy efficiency lags behind the “smaller” Titan machine. Tianhe-2 runs Linpack at 17.8 megawatts while the 261,632 core NVIDIA K20-boosted Cray system at Oak Ridge runs at 8.21 megawatts.

The IBM Sequoia system at Lawrence Livermore is holding steady at number three, which in its three years alive has topped out at 17.17 petaflops/s, not far behind Titan. For those not familiar with the list this further shows the Linpack benchmark performance chasm between the number one system and those that trail it—all of which in the top ten range between 17.59 petaflops/s at the top to 3.1 petaflops/s for #10. The 500th machine on the list runs at just a tick over the 133 teraflop/s peak mark.

For those familiar with the list in its last form in November, you’ll notice that there is only one change in the top ten—a Cray XC30 is now in place and running at 3.14 petaflops at an undisclosed U.S. government site. While other than this new, mysterious addition, there might not be any earth-shattering news on this Top 500 list, there are some trends that we’ve been monitoring over the last few list iterations—and some that have evolved since November. For instance, the United States, which once dominanted the Top 500, dropped from 265 systems during November’s listing to 233 on this 43rd Top 500.

Meanwhile, the number of Chinese systems in increasing. In addition to securing the number one spot by a significant margin, there are an additional 13 machines from China, bringing their total share of the Top 500 to 76. To put that in some perspective, the UK has 30, France has 27 and Germany has 23. Japan has contributed an additional two machines, bringing their total to 30.

When it comes to the overall list, performance is continuing to climb. The total of all machines on the November list is now 274 petaflops, compared to 250. To add further perspective, the total petaflop count across all machines reporting results was 223 petaflops. That sounds like a rather noteworthy increase until one takes a look at the long term growth line in performance…

Remember that strong performance development staircase we’ve steadily been climbing? If you take a look at the graphic below using the latest data from today’s Top 500 announcement, you’ll see that slight planing off in reach that we began to spot over the last year and a half. As our friends at TOP500 noted today, “From 1994 to 2008 [performance] grew by 90% per year. Since 2008 it only grows by 55% per year.” And when you take a close look at the list over the last couple of years, you’ll see that the reason why that declining figure isn’t more pronounced is simply because the top tier of the list is propping it up—most notably with the addition of the Tianhe-2 system, which holds 13.7% of the performance share of the entire list.

When examined as a whole, we’re falling off except at the highest end…but what does this mean for end user applications? Is high end computing getting smarter in terms of efficiency and software to where, for real-world applications, FLOPS no longer matter so much? Many argue that’s the case…and some will await the new HPCG benchmark and forgo Linpack altogether in favor of a more practical benchmark. That hasn’t had an impact yet on this summer’s list but over time it will be interesting to watch.

top500-performance

One gamechanger for the historical performance trends is certainly the mighty accelerator/coprocessor. But even the accelerator story has some interesting twists and turns to report. A total of 62 systems are using some form of accelerator or coprocessor technology, which is up slightly from 53 machines on the November list. Of those, 44 are using NVIDIA GPUs, 17 have deployed Xeon Phi and two have ATI Radeon as the booster of choice.

With that in mind, there’s another phenomenon that stands out. While this isn’t a suggestion that the performance leveling off is because of this, the trend around accelerator use isn’t quite as strong as it used to be either, as you can see on the historical development chart below. There are many reasons why this might be the case. For instance, national labs and scientific computing centers tend to be among the first to experiment with new technologies, although for GPUs in particular, this doesn’t completely match up since the real spike in NVIDIA-powered systems happens late in 2011–quite a long time after GPU computing began to take off. It’s possible to see in that spike for Intel when Xeon Phi landed in several shops as experimental technology as well, but even with a spike visible now, it’s difficult to see widespread adoption.

 

top500-acceleratorOf course, keep in mind that a tapering off of GPU or other accelerated systems doesn’t exactly mean that there is an overall slowdown. This is one segment of the HPC arena–there are many, many machines from academia and enterprise, that do not choose to run the HPL benchmark. Even if there are 20% of these machines missing from the list, the effect on that list would be felt in such a graphic. We asked Addison Snell of Intersect360 Research about the accelerator graphic above and he echoed this, noting that “Change in share in the Top 500 doesn’t necessarily reflect market trends. While Intel did gain share in microprocessors in 2013 over AMD and IBM Power, we also have seen a number of HPC systems with GPUs installed, which has risen to 44% of systems installed since the beginning of 2012.”

The real story that’s developing further with this list–and we expect, given changes at IBM in particular–is on the chip front. A great deal more will be revealed about the nature of such shifts in November and next June…and definitely by the end of 2015 if the many developments at IBM, Intel, NVIDIA and elsewhere are on schedule.

To put those in more accurate light, Intel has an 85% share of the systems on the list with IBM Power at 8 percent and AMD Opterons moving down three percent in terms of share to 6%. TOP500 reports that among these systems, 96% are sporting six or more cores with 83% harnessing eight or more.  To say that Intel continues to dominate is an understatement. But despite any perceived stagnation of this chart from the last couple of years, get ready, because the new few years are set to bring strong winds of change due to momentum with OpenPower and perhaps even AMD. The arrival of 64-bit ARM will shake things up as will new choices in chips, but expect a flat list at least through this time next year unless something completely unexpected happens. Fill in the blank on what that might be, but free, easy to program quantum computing systems seems the only option.

top500-chip

Right now, IBM’s Blue Gene/Q holds the majority of systems in the top ten. However, with changes at IBM, which is now focusing its efforts on the future of OpenPower and Power more generally, once these systems are decommissioned, along with the many others on the list (176 currently), it’s hard to say what their position will be. We talked with IBM’s Dave Turek this week in advance of ISC and we have an interview coming during our special coverage that will offer a sense of what’s next for Big Blue in HPC, so keep an eye out for that.

On the network front, there haven’t been any major changes. 222 systems are sporting Infiniband on this most recent list, up from 207 in fall. 75 entries are reporting 10 GbE, which is two less than the last list A total of 127 systems are outfitted with standard GbE (compared to 135 in November). There are 52 custom interconnects and 5 proprietary interconnects (which now includes the Cray Aries assets, which used to be counted under their own system name). The Gemini interconnect can be found on 18 systems, including, of course, Titan.

For some additional background on this summer’s list, we thought it might be useful to show two figures that demonstrate where a few trends in the list and its participants. The first will also not offer much in the way of difference or surprises compared to November’s iteration of the Top 500, although it’s thrilling to see growing industry participation take a slight rise.

top500-typeThe figure below puts all of this in context by showing the dominant trend in terms of systems–again, not a surprise, but a useful visualization.

top500-architectures

Of all of these systems, HP has a 36% share (down from 39% in November), IBM has 35% (up from 33% on the fall list) and Cray sits in third position for vendor share with 51 systems—a total of just a tick over 10% of the 500 machines.

What’s more enlightening on those figures is the performance share. As noted above, the Tianhe-2 system itself provides over 13% of the performance share for the list. But by vendor, IBM has a 32% performance share, Cray edged up to 18.6% (up by two percentage points, in part due to the new #10 government XC30), and although they sell more systems than the others, HP’s performance share is just a tick below Cray’s at 15.6%.

Stay tuned for our visual feature set go live later this morning CET that showcases other subtle trends on this summer’s TOP500 list.

And in the meantime, stop by the HPCwire booth to say hello. You’re welcome to bring a pot of coffee with you. I take it with milk, no sugar. And I will drink it all. Thank you.

 

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 U.S. 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 U.S. 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

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

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

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