Intel Sets High Water Mark of One Teraflop with ‘Knights Corner’

By Michael Feldman

November 16, 2011

At SC11 in Seattle, Intel showed off an early silicon version of Intel’s Many Integrated Core (MIC) “Knight Corner,” the codename for its first commercial product based on their MIC architecture. The demonstration was performed for the benefit of reporters and analysts, who got to see the new chip in action at a press briefing here on Tuesday afternoon. The jury-rigged test setup had the chip running DGEMM (the double precision floating point version of the general matrix multiply algorithm) at a rather amazing one teraflop/second.

Rajeeb Hazra, GM of Intel’s Technical Computing, Datacenter and Connected Systems Group, waved one of the pre-production chip in front of audience, saying that they had produced “a few tens of chips” for early testing. According to Hazra, they were manufactured at one of their fabs using their 22nm process technology.

He was less forthcoming about other details on the chip however, dodging questions about core counts (once again reiterating that it will be more than 50), processor clock speed, and power consumption. On that last point, it’s likely that TDP is likely to be in the GPU-like 200 to 275 watt range, inasmuch as the coprocessors are destined for servers and workstations, which only have so much leeway with regard to power envelopes.

I did manage to find out the Knight Corner does indeed support ECC memory, although it wasn’t turned on for the DGEMM demo. According to the attending engineer, it doesn’t effect the flops on that code, but will lower performance somewhat on more general applications.

As Hazra pointed out in the briefing, this is the first general-purpose chip in history that is able to hit the one teraflop mark. And while that is true, it should be noted that NVIDIA’s “Kepler” GPU, which is likely to be in production prior to Knights Corner, will probably deliver somewhere between 1.2 to 1.4 double precision teraflops, or about twice that of the current Fermi-class Tesla GPUs.

Nonetheless, the early edition Knight Corner is a remarkable achievement by Intel, and something of a watershed moment for x86 chip making. In 1997, ASCI Red, an Pentium II Xeon-based supercomputer, needed 9,298 processor to hit this same one teraflop mark. And that machine, which was spread out over 72 cabinets, sucked up 800 KW of power.

The production Knights Corner chips delivered in a year or so may actually end up delivering something north of one teraflop, so it’s not a given that NVIDIA will win the flops battle in 2012. In any case, Intel is probably not overly concerned about absolute performance. It’s made a good case that the programming model for MIC will be the real differentiator here.

For some time Intel has been touting that its own x86 parallel compiler and development tools will offer complete support for MIC coprocessors, making the application porting effort much more productive than CUDA. When the code in question incorporates MIC-friendly parallel frameworks like OpenMP, initial porting may amount to no more than a recompile and a re-link. If that pans out as advertised, the ease-of-programming feature will ultimately be the deciding factor in MIC’s favor.

During the press briefing, R. Glenn Brook, a computational scientist at the National Institute for Computational Sciences, University of Tennessee, reported that his team had ported tens of million of lines of legacy science codes to MIC (on prototype “Knights Ferry” coprocessor-powered clusters) in under three months. According to Brook, some of these applications will probably never be ported to GPUs because the complexity of these codes would make the endeavor too onerous.

Clearly, Intel sees their manycore architecture as a path to exascale. In this realm power efficiency is the whole ball game, and MIC is inherently superior to more traditional x86 CPUs in this regard. If we assume Knights Corner is a 250 watt part, it will be able to deliver 4 gigaflops/watt today. That still a far cry from the 50 gigaflops/watt target for an exaflop system (which also has to include memory, interconnects, power supplies, etc.), but the performance/watt trajectory is much more in line with exascale efficiency compared Intel’s mainstream Xeon line.

Speaking of which, Hazra offered up some interesting performance stats on their new Xeon E5 (Sandy Bridge EP) processors. According to Intel testing, the Xeon E5-2680 chip delivers 172 gigaflops of peak performance. And while that bests any of the AMD Opteron 6200 series processors, it’s still well under 2 gigaflops/watt (hard to tell exactly since Intel hasn’t provided TDPs on these pre-launched parts). From that perspective, a traditional Xeon, at least without an on-chip MIC coprocessor, has a rather uncertain future in the exascale era.

But at least for the early petascale era, the Xeon processor is doing just fine. The previous generation Xeon 5600 line is in 223 of the top 500 supercomputers in the world. And the aforementioned Xeon E5 is already in 10 systems, despite the fact that the product won’t be officially launched until the first half of 2012 (which, to my mind, makes the term launch kind of meaningless).

In addition, the E5 will also be making an appearance in future top 10 systems, like GENCI’s 2-petaflop “Curie” super. It is also the CPU of choice for TACC’s 10-petaflop “Stampede” supercomputer, which is scheduled for deployment in early 2013. In this case though, the E5 will be eclipsed by the Knights Corner coprocessors, which will provide 8 of those 10 petaflops. If that trend holds, then MIC will indeed be Intel’s dominant supercomputing architecture for the second half the decade.

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!

Quantinuum Reports 99.9% 2-Qubit Gate Fidelity, Caps Eventful 2 Months

April 16, 2024

March and April have been good months for Quantinuum, which today released a blog announcing the ion trap quantum computer specialist has achieved a 99.9% (three nines) two-qubit gate fidelity on its H1 system. The lates Read more…

Mystery Solved: Intel’s Former HPC Chief Now Running Software Engineering Group 

April 15, 2024

Last year, Jeff McVeigh, Intel's readily available leader of the high-performance computing group, suddenly went silent, with no interviews granted or appearances at press conferences.  It led to questions -- what's Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Institute for Human-Centered AI (HAI) put out a yearly report to t Read more…

Crossing the Quantum Threshold: The Path to 10,000 Qubits

April 15, 2024

Editor’s Note: Why do qubit count and quality matter? What’s the difference between physical qubits and logical qubits? Quantum computer vendors toss these terms and numbers around as indicators of the strengths of t Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips are available off the shelf, a concern raised at many recent Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announced its second fund targeting €200 million. The very idea th Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announce Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. I Read more…

Google Announces Homegrown ARM-based CPUs 

April 9, 2024

Google sprang a surprise at the ongoing Google Next Cloud conference by introducing its own ARM-based CPU called Axion, which will be offered to customers in it Read more…

Computational Chemistry Needs To Be Sustainable, Too

April 8, 2024

A diverse group of computational chemists is encouraging the research community to embrace a sustainable software ecosystem. That's the message behind a recent Read more…

Hyperion Research: Eleven HPC Predictions for 2024

April 4, 2024

HPCwire is happy to announce a new series with Hyperion Research  - a fact-based market research firm focusing on the HPC market. In addition to providing mark Read more…

Google Making Major Changes in AI Operations to Pull in Cash from Gemini

April 4, 2024

Over the last week, Google has made some under-the-radar changes, including appointing a new leader for AI development, which suggests the company is taking its 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…

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…

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…

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…

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…

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…

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…

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…

Leading Solution Providers

Contributors

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…

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…

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…

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

March 18, 2024

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

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

Intel’s Xeon General Manager Talks about Server Chips 

January 2, 2024

Intel is talking data-center growth and is done digging graves for its dead enterprise products, including GPUs, storage, and networking products, which fell to Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire