TOP500 Sluggish, But Chinese Supers May Portend Big Changes Ahead

By Michael Feldman

May 31, 2010

A Chinese supercomputer called Nebulae, powered by the latest Fermi GPUs, grabbed the number two spot on the TOP500 list announced earlier today. The new machine delivered 1.27 petaflops of Linpack performance (against a record peak performance of 2.98 petaflops), yielding only to the 1.76 petaflop Jaguar system, which retained its number one berth.

The new Chinese machine is installed at the National Supercomputing Centre in Shenzhen (NSCS) and was built by Chinese HPC vendor Dawning. Nebulae is based on Dawning’s TC3600 blades, which house Intel X5650 CPUs connected to NVIDIA Tesla C2050 GPUs. Although of hybrid design, the majority of the FLOPS originate with the system’s 4,640 NVIDIA GPUs, which, by themselves, provide 2.32 of the 2.98 peak petaflops. Power consumption on Linpack for this latest petaflop machine is not recorded, but I’m guessing it’s between 2.5 and 3.0 MW, which would be more than twice the power efficiency of the Opteron-based Jaguar super.

Nebulae represents the second Chinese machine in the top 10. Tianhe-1, now at number 7, is a 563-teraflop system that captured the number 5 slot last November. It is housed at the National Supercomputer Center in Tianjin/NUDT. Like Nebulae, Tianhe-1 is a CPU-GPU hybrid, in this case using ATI Radeon GPUs from AMD.

Yet another Fermi GPU-accelerated system from China that made the list is Mole-8.5, the supercomputer announced last week in a Mellanox press release. That system achieved 207 Linpack teraflops (out of a possible 1,138), garnering the 19th spot on the TOP500. It’s installed at the Institute of Process Engineering, Chinese Academy of Sciences.

Whether Nebulae, Tianhe-1, and Mole-8.5 foreshadow a coming of age for high-end GPU computing remains to seen. These three Chinese systems represent three quarters of all the GPU-equipped machines on the current list, which is still dominated by x86-based CPUs. However, multi-petaflop systems powered by GPUs are now in the pipeline. The Keeneland Project, an NSF Track 2D grant will fund an HP system accelerated by NVIDIA GPUs. Georgia Tech, the University of Tennessee and Oak Ridge National Laboratory will build and manage this system. Keeneland is supposed to deliver about 2 peak petaflops, and be deployed sometime in 2012. In Japan, TSUBAME 2.0 is also going to be built using NVIDIA GPUs. That system is slated to hit 2.4 petaflops and is scheduled to be installed later this year. This is all good news for GPU vendors, especially NVIDIA, which has invested most heavily in HPC and the GPGPU movement over the past four years.

It’s also good news for China. That country is developing its supercomputing resources at a rapid pace now, especially at the top end of the spectrum. This latest list puts 24 Chinese systems in the TOP500 — tied with Germany, and trailing only the US, UK, and France. And from an aggregate performance standpoint, China is second only to the US.

Besides the China-GPU excitement, the rest of the TOP500 news was rather humdrum. For example, the top systems barely budged, which is somewhat of a rarity. With the exception of Nebulae, the only other noteworthy change in the top 10 is the upgraded NASA Pleiades system, which got outfitted with additional SGI Altix ICE 8400 blades. That upped its Linpack performance from 544 teraflops to 722 teraflops, but failed to improve its ranking at the number 6 slot. Ranger, the Sun Constellation system at TACC, was the only machine that got bumped out of the top 10.

The increase in aggregate performance for the entire list was the lowest in TOP500 history, reflected by the fact that only 143 of the 500 systems were replaced. Even the bottom of the list barely moved. The 500th system six month ago was 20 teraflops, which increased to only 24.7 teraflops on the current list.

Perhaps more ominous is that multicore scaling seems to be slowing. According to TOP500 list co-founder Erich Strohmaier, the move from predominantly dual-core systems to quad-core systems took about two years. If that pace had kept up, we would be seeing many more six- and eight-core system, which is not the case (425 systems on the list are still quad-core).

This may be due to a temporary hiccup in the CPU rollout cycle. This spring Intel, AMD and IBM started rolling out 6-, 8-, and 12-core CPUs, and they should start showing up in HPC installations very shortly. But because bandwidth to RAM is not keeping pace with the additional cores, memory-bound problems can’t benefit by simply increasing the CPU core count. This could be encouraging chipmakers to spend relatively more of the transistor budget provided by Moore’s Law on features like bigger caches or new instructions, rather than on additional compute engines.

Another unfortunate trend seems to be developing. Although the T0P500 has only been keeping tabs on system power consumption for a couple of years, that metric seems to be steadily rising for the list as a whole, and is rising especially fast for the top 10 systems. Fortunately power efficiency is going up too, but not fast enough to keep pace with user demand for bigger machines. If that curve can’t be bent, a larger and larger percentage of the expense of a supercomputer is going to be consumed by power and cooling.

The trend toward Intel CPUs continues. The vast majority of systems — 408, to be precise — are based on Intel processors. AMD chips are in just 47 systems, despite being used in a disproportionate number of the top systems, including the number 1 (Jaguar), 3 (Roadrunner), and 4 (Kraken) machines. IBM Power-based systems are in third place with 42.

Finally, the trend toward InfiniBand remains unabated. There are now 207 systems on the list using InfiniBand fabric, up from 181 just six months ago. Interestingly, Gigabit Ethernet-based machines took a hit, dropping from 259 systems in November 2009, to 242 today. The battle between 10 GigE and InfiniBand awaits.

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!

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

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

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…

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

Nvidia P100 Shows 1.3-2.3x Speedup Over K80 GPU on Financial Apps

April 20, 2017

When it comes to the true performance of the latest silicon, every end user knows that the best processor is the one that works best for their application. Read more…

By Tiffany Trader

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

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

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 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

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

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