The New Breed of Accelerators from NVIDIA, Intel and AMD Square Off

By Michael Feldman

December 6, 2012

With the recent introduction of Intel’s first Xeon Phi coprocessors, NVIDIA’s latest Kepler GPUs, and AMD’s new FirePro S10000 graphics cards, the competition for HPC chip componentry has entered a new phase. The three chipmakers have taken somewhat different paths, though, and it will be up to the market to decide which vendor’s approach will win the day.

It is tempting to think that there might be room for all three accelerator designs in the market, but as it stands today that’s unlikely. The HPC space is too small and homogeneous to support that much architectural diversity. Just consider how the CPU side has, for the most part, consolidated to a single ISA (the x86), and to a large degree, a single vendor (Intel). While there may be a case to be made that these accelerators can offer different advantages for different applications, in their current incarnation they all are built principally as vector accelerators for CPU hosts.

That implies that the chip design that does that best, that is, delivers the most application FLOPS per dollar and per watt, will be the HPC consumer’s top choice – unless you believe that one or the other of these platforms will be substantially easier to program than the others. We’ll get to that particular aspect in a moment.

First though, it’s worthwhile just looking at the specs for the three accelerators. All of them offer teraflop-plus double precision performance with several gigabytes of ECC memory, but not all with the same power draw. And it’s the performance-per-watt that is most likely to become the driving criteria for many HPC users as they try to squeeze maximum FLOPS from a static datacenter power supply.

The NVIDIA Tesla K20X is the one to beat in this regard. It offers 1.3 teraflops in a 235 watt package – so 5.6 gigaflops/watt. Intel’s new “Knights Corner” Xeon Phi, the 5110P, delivers 1.011 teraflops with a TDP of 225 watts, which works out to 4.5 gigaflops/watt. The AMD FirePro S10000 card that sports two “Tahiti” GPUs, is rated at 1.48 teraflops. But the FirePro draws 375 watts, so its 3.9 gigaflops/watt is actually the lowest of the bunch.

The FirePro does somewhat better in the single precision FP department, delivering 15.8 gigaflops/watt to the K20X’s 16.8 gigaflops/watt and the 5110P’s 9.0 gigaflops/watt (estimated). But if you’re really focused on single precision performance, the go-to device is the NVIDIA K10, which delivers over 20 gigaflops/watt.

Memory-wise, the Intel 5110P is tops with 8 GB and 320 GB/sec of bandwidth. The K20X is supplied with 6 GB and 250 GB/sec, so less capacity, but with roughly the same bandwidth per byte. The new FirePro is also equipped with 6 GB, but at 450 GB/sec, offers considerably more bandwidth. That’s all with ECC turned off, though, so your actual mileage will vary depending on the error correction smarts on each of these platforms.

It’s not surprising that NVIDIA’s silicon specs out so well here. They’ve been the dominant player in the accelerator business for the last several years and have spent a lot of time designing the devices for this role. But the hardware alone will not be the sole determinant. Porting applications to these accelerators and getting them to draw on those abundant FLOPS will be the biggest challenge.

It is here that Intel believes it has an advantage. The company’s line has been that existing programs, using just standard MPI and OpenMP as the framework for parallelism, will port to the Xeon Phi platform with a simple recompile and link. And while that’s true, that doesn’t necessarily guarantee good performance. In fact, it is more than likely that porting applications that lend themselves to vector acceleration on Xeon Phi will have to be modified in ways not so different than what is done for GPUs – namely splitting the code across the CPU and accelerator, such that performance is optimized across the serial and parallel parts of the application.

Until there are a number of well-known HPC applications running on the Xeon Phi, proof of easy porting with impressive performance are just claims. And in any case, OpenMP’s new accelerator directives are supposed to level the software playing field across all these platforms – at least with regard to a standard high-level software framework. As of today, though, that standard has not been ratified and it’s not clear if GPUs will be supported adequately on the initial go-around, which, given the current accelerator landscape, sort of defeats the purpose for a hardware-independent API.

This is just the beginning of the accelerator era of high performance computing, or perhaps more accurately, the end of the beginning. Especially with Intel’s entrance into the space, the accelerator model for high performance computing has been legitimized in a way that NVIDIA could not have done on its own. And while accelerators are not the be-all and end-all of HPC, right now they are driving much of the rapid performance gains we see in the industry.

That means the stakes are high for all three vendors. Whoever comes out on top is likely to establish itself as the dominant supercomputing chipmaker for the latter half of the petascale era and the first part of the exascale era, when the technology will almost certainly be integrated into the CPU die. With Intel, NVIDIA and AMD now focusing more interest in their accelerator lines, we’re apt to see an even more rapid evolution of the hardware and the software.

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!

IBM Touts OpenPOWER Ecosystem, Announces New Customers, Products for AI and Hyperscale

March 20, 2018

At SC17 in Denver four months ago, Ken King, GM, OpenPOWER, IBM Systems Group, told a somewhat jaundiced trio of journalists that 2018 would, finally, after several years of expectations, be the year OpenPOWER and IBM’ Read more…

By Doug Black

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate scientists the ability to use machine learning to identify e Read more…

By Rob Farber

Mellanox Reacts to Activist Investor Pressures in Letter to Shareholders

March 16, 2018

Activist investor Starboard Value has been exerting pressure on Mellanox Technologies to increase its returns. In response, the high-performance networking company on Monday, March 12, published a letter to shareholders outlining its proposal for a May 2018 extraordinary general meeting (EGM) of shareholders and highlighting its long-term growth strategy and focus on operating margin improvement. Read more…

By Staff

HPE Extreme Performance Solutions

Harness the Full Power of HPC Servers with an Effective Cooling Approach

High performance computing (HPC) innovation is rapidly transforming the way we operate – with an onslaught of cutting-edge technologies designed to optimize applications and workloads, increase productivity, and enable better business outcomes. Read more…

Quantum Computing vs. Our ‘Caveman Newtonian Brain’: Why Quantum Is So Hard

March 15, 2018

Quantum is coming. Maybe not today, maybe not tomorrow, but soon enough. Within 10 to 12 years, we’re told, special-purpose quantum systems will enter the commercial realm. Assuming this happens, we can also assume that quantum will, over extended time, become increasingly general purpose as it delivers mind-blowing power. Read more…

By Doug Black

IBM Touts OpenPOWER Ecosystem, Announces New Customers, Products for AI and Hyperscale

March 20, 2018

At SC17 in Denver four months ago, Ken King, GM, OpenPOWER, IBM Systems Group, told a somewhat jaundiced trio of journalists that 2018 would, finally, after sev Read more…

By Doug Black

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

Stephen Hawking, Legendary Scientist, Dies at 76

March 14, 2018

Stephen Hawking passed away at his home in Cambridge, England, in the early morning of March 14; he was 76. Born on January 8, 1942, Hawking was an English theo Read more…

By Tiffany Trader

Hyperion Tackles Elusive Quantum Computing Landscape

March 13, 2018

Quantum computing - exciting and off-putting all at once - is a kaleidoscope of technology and market questions whose shapes and positions are far from settled. Read more…

By John Russell

Part Two: Navigating Life Sciences Choppy HPC Waters in 2018

March 8, 2018

2017 was not necessarily the best year to build a large HPC system for life sciences say Ari Berman, VP and GM of consulting services, and Aaron Gardner, direct Read more…

By John Russell

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

SciNet Launches Niagara, Canada’s Fastest Supercomputer

March 5, 2018

SciNet and the University of Toronto today unveiled "Niagara," Canada's most-powerful supercomputer, comprising 1,500 dense Lenovo ThinkSystem SD530 high-perfor Read more…

By Tiffany Trader

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Japan Unveils Quantum Neural Network

November 22, 2017

The U.S. and China are leading the race toward productive quantum computing, but it's early enough that ultimate leadership is still something of an open questi Read more…

By Tiffany Trader

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. 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

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

Leading Solution Providers

GlobalFoundries, Ayar Labs Team Up to Commercialize Optical I/O

December 4, 2017

GlobalFoundries (GF) and Ayar Labs, a startup focused on using light, instead of electricity, to transfer data between chips, today announced they've entered in Read more…

By Tiffany Trader

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

V100 Good but not Great on Select Deep Learning Aps, Says Xcelerit

November 27, 2017

Wringing optimum performance from hardware to accelerate deep learning applications is a challenge that often depends on the specific application in use. A benc Read more…

By John Russell

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

AMD Wins Another: Baidu to Deploy EPYC on Single Socket Servers

December 13, 2017

When AMD introduced its EPYC chip line in June, the company said a portion of the line was specifically designed to re-invigorate a single socket segment in wha Read more…

By John Russell

World Record: Quantum Computer with 46 Qubits Simulated

December 18, 2017

Scientists from the Jülich Supercomputing Centre have set a new world record. Together with researchers from Wuhan University and the University of Groningen, Read more…

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Te Read more…

By John Russell

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