For Proprietary HPC, Hope Springs Eternal

By Michael Feldman

October 14, 2010

Over the past 15 years, commodity-based server computing has probably done more to mainstream HPC than any other single factor.  But specialized HPC certainly hasn’t disappeared, and the market is periodically tested by those who believe that proprietary hardware is the true path to supercomputing Nirvana.

By any measure, commodity-based HPC systems — basically, we’re talking x86 Linux clusters — dominate the industry. But because of the presence of a healthy supercomputing segment (systems over $500K), this dominance is not completely overwhelming. According to IDC’s latest figures standard clusters took 64 percent of the market. At the level of the processor though, the statistics are more skewed. IDC estimates about three-quarters of HPC server revenue comes from x86-based systems, while InterSect360 Research reports fully 90 percent of systems in their most recent site survey use chips from either AMD or Intel.

In general, companies who come up with proprietary technologies (especially proprietary processors) have had limited success in this market. Often very limited. ClearSpeed and SiCortex represent two of the most recent providers of customized solutions who met untimely ends. Although ClearSpeed’s accelerators offered even better performance per watt than GPGPUs, the proprietary nature of the technology kept HPC users away in droves. SiCortex and its MIPS-based clusters also offered up some very compelling performance per watt numbers, but the business couldn’t reach escape velocity before rough economic times hit in 2009.

The dominance of the x86 processor has led to semi-custom designs like the Cray XT/XEs and SGI’s Altix UV line. In these cases, x86 silicon is used to take advantage of the cost benefits of volume server chips (not to mention the x86-centric software ecosystem), but the design is flavored with proprietary node controllers to maximize network performance. This has proved to be an eminently successful approach from a technology standpoint, although given the lack of profits emanating from these two companies, not yet a proven business model.

There are other possible variations on the pure commodity HPC theme, one of which was evident this week in Appro’s introduction of its HF1 server. In this case, the server maker incorporated overclocked x86 Xeon CPUs along with a liquid cooling system to compensate, with the idea of providing a souped-up box for high frequency trading (HFT). The servers are both expensive and warranty-challenged, but this is less of an issue for the lucrative business these servers are aimed at. It will be interesting to see if this industry-vertical customization model is a success here, and if so, if it can be replicated across other domains.

In fact, Convey Computer Corporation is aiming to do just this, in this case, with a “hybrid-core” model that employs x86 processors along with an FPGA as the co-processor. The idea is for the co-processor to be loaded with a “personality” that extends the x86 instruction set for a particular class of applications — bioinformatics, seismic processing, data mining, financial analytics, and so on. The two-year old company has managed to grab some critical acclaim and a handful of customers, but it has yet to take the HPC world by storm.

Traveling further down the proprietary continuum, we have supercomputers like IBM’s Blue Gene and its newer Power7-based HPC servers, both of which rely on custom ASICs and other hardware. Similarly, we have IBM’s QS22 blade, which was incorporated into Roadrunner, the first petaflop supercomputer. That blade was based on the PowerXCell 8i Cell processor, a variant of the Cell processor used in Sony PlayStations. IBM pulled the plug on PowerXCell line when it became apparent that the market wasn’t all that enthralled with Cell as an HPC accelerator.

An even more specialized supercomputer is the MDGRAPE-3 machine, developed by the RIKEN research institute in Japan. That system doesn’t even pretend to be a general-purpose machine; it was designed for a single class of application: molecular dynamics. The design uses a combo of proprietary MDGRAPE-3 processors and Intel Xeon chips. There was talk of an MDGRAPE-4 a couple of years ago, but I’ve heard nothing about it recently

Along the same lines, is the Anton supercomputer from D.E. Shaw Research. Like MDGRAPE-3, the application target is molecular dynamics, but in this case the processing is done entirely on a customized ASIC. An article in Nature this week reported Anton recently demonstrated a protein folding simulation 100 times longer than any previous simulation — a millisecond versus 10 microseconds. It certainly sounds like a game-changer for the protein folding folks; we just have to figure out how to put one in every lab.

Finally, there’s the Green Flash project currently under development at Berkeley Lab. The idea here is to design a special-purpose supercomputer to perform climate simulations based on a much higher resolution cloud model. To be of practical use, the system would need to be about 1,000 times more powerful than supercomputers currently available, but be much more efficient in terms of power, performance, and cost. The proposed design would employ about 20 million semi-custom Tensilica Xtensa processors, cost in the neighborhood of $75 million, and draw 4 MW of power. In May they demonstrated a logical prototype of the machine by emulating the processors building blocks on an FPGA platform.

Of course, if NVIDIA has its way, system vendors will be able to create a general-purpose supercomputer with the performance characteristics approaching that of an Anton or Green Flash a few years down the road. The GPU maker’s future generation processors, Kepler in 2011 and Maxwell in 2013, will be 3 and 10 times more powerful, respectively, than the current Fermi processors. Even though these future GPUs are unlikely to be as efficient as special-purpose hardware, the history of HPC suggests that designs based on commodity parts will eventually carry the day. None of which will keep people from dreaming up ever more powerful custom supercomputers.

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!

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “pre-exascale” award), parsed out additional information ab Read more…

By Tiffany Trader

Tsinghua Crowned Eight-Time Student Cluster Champions at ISC

June 22, 2017

Always a hard-fought competition, the Student Cluster Competition awards were announced Wednesday, June 21, at the ISC High Performance Conference 2017. Amid whoops and hollers from the crowd, Thomas Sterling presented t Read more…

By Kim McMahon

GPUs, Power9, Figure Prominently in IBM’s Bet on Weather Forecasting

June 22, 2017

IBM jumped into the weather forecasting business roughly a year and a half ago by purchasing The Weather Company. This week at ISC 2017, Big Blue rolled out plans to push deeper into climate science and develop more gran Read more…

By John Russell

Intersect 360 at ISC: HPC Industry at $44B by 2021

June 22, 2017

The care, feeding and sustained growth of the HPC industry increasingly is in the hands of the commercial market sector – in particular, it’s the hyperscale companies and their embrace of AI and deep learning – tha Read more…

By Doug Black

HPE Extreme Performance Solutions

Creating a Roadmap for HPC Innovation at ISC 2017

In an era where technological advancements are driving innovation to every sector, and powering major economic and scientific breakthroughs, high performance computing (HPC) is crucial to tackle the challenges of today and tomorrow. Read more…

At ISC – Goh on Go: Humans Can’t Scale, the Data-Centric Learning Machine Can

June 22, 2017

I've seen the future this week at ISC, it’s on display in prototype or Powerpoint form, and it’s going to dumbfound you. The future is an AI neural network designed to emulate and compete with the human brain. In thi Read more…

By Doug Black

Cray Brings AI and HPC Together on Flagship Supers

June 20, 2017

Cray took one more step toward the convergence of big data and high performance computing (HPC) today when it announced that it’s adding a full suite of big data and artificial intelligence software to its top-of-the-l Read more…

By Alex Woodie

AMD Charges Back into the Datacenter and HPC Workflows with EPYC Processor

June 20, 2017

AMD is charging back into the enterprise datacenter and select HPC workflows with its new EPYC 7000 processor line, code-named Naples, announced today at a “global” launch event in Austin TX. In many ways it was a fu Read more…

By John Russell

Hyperion: Deep Learning, AI Helping Drive Healthy HPC Industry Growth

June 20, 2017

To be at the ISC conference in Frankfurt this week is to experience deep immersion in deep learning. Users want to learn about it, vendors want to talk about it, analysts and journalists want to report on it. Deep learni Read more…

By Doug Black

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Tsinghua Crowned Eight-Time Student Cluster Champions at ISC

June 22, 2017

Always a hard-fought competition, the Student Cluster Competition awards were announced Wednesday, June 21, at the ISC High Performance Conference 2017. Amid wh Read more…

By Kim McMahon

GPUs, Power9, Figure Prominently in IBM’s Bet on Weather Forecasting

June 22, 2017

IBM jumped into the weather forecasting business roughly a year and a half ago by purchasing The Weather Company. This week at ISC 2017, Big Blue rolled out pla Read more…

By John Russell

Intersect 360 at ISC: HPC Industry at $44B by 2021

June 22, 2017

The care, feeding and sustained growth of the HPC industry increasingly is in the hands of the commercial market sector – in particular, it’s the hyperscale Read more…

By Doug Black

At ISC – Goh on Go: Humans Can’t Scale, the Data-Centric Learning Machine Can

June 22, 2017

I've seen the future this week at ISC, it’s on display in prototype or Powerpoint form, and it’s going to dumbfound you. The future is an AI neural network Read more…

By Doug Black

Cray Brings AI and HPC Together on Flagship Supers

June 20, 2017

Cray took one more step toward the convergence of big data and high performance computing (HPC) today when it announced that it’s adding a full suite of big d Read more…

By Alex Woodie

AMD Charges Back into the Datacenter and HPC Workflows with EPYC Processor

June 20, 2017

AMD is charging back into the enterprise datacenter and select HPC workflows with its new EPYC 7000 processor line, code-named Naples, announced today at a “g Read more…

By John Russell

Hyperion: Deep Learning, AI Helping Drive Healthy HPC Industry Growth

June 20, 2017

To be at the ISC conference in Frankfurt this week is to experience deep immersion in deep learning. Users want to learn about it, vendors want to talk about it Read more…

By Doug Black

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. Just how close real-wo 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 cam 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 a 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 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

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

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a 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

Leading Solution Providers

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

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

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

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

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 Read more…

By Alex Woodie

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

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

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

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