Dual-Use GPUs for Servers — AMD and NVIDIA Mind Their P’s and Q’s

By Michael Feldman

May 19, 2011

While NVIDIA has managed to capture the mindshare in the GPU computing space, especially in the high performance computing segment, AMD keeps plugging away. AMD’s Fusion processor/OpenCL strategy is its long-term answer to NVIDIA’s CUDA approach, but in the near-term, AMD is looking for other ways to follow NVIDIA’s lead into the GPU server market.

This week AMD announced the FirePro V7800P, its first non-FireStream server GPU part. Unlike the compute-focused FireStreams, however, the new V7800P is designed to serve both graphics/visualization applications and GPU computing.

In particular, it supports Microsoft RemoteFX, a visualization technology for virtual desktop infrastructure (VDI). The idea is to serve up desktop visuals from clusters to various types of thin clients, relieving the local device of doing heavy-duty graphics. The advantage is that a single GPU can support the graphics (and audio) for multiple clients and do so at the price-power-performance efficiency of a datacenter. Microsoft has high hopes for RemoteFX and hopes to draw millions of users to the technology in 2012.

Not surprisingly, AMD would like to be a part of that — thus the FirePro V7800P. But since the device can also double as a GPU accelerator, V7800P-equipped servers can crunch on GPGPU applications when they’re not busy drawing pretty pictures for client devices. It’s easy to imagine a scenario where a GPU cluster would be driving desktop graphics during working hours and running HPC codes at nights and on weekends.

According to Mitch Furman, the senior product manager for AMD’s professional graphics products, the V7800P is essentially a superset of the FireStream 9350 product. While the latter part supports OpenCL and OpenGL, only FirePro supports the OpenGL optimization that are needed for serious CAD and DCC applications. And as mentioned before, only the FirePro card works with RemoteFX for VDI.

Compute-wise though, the two AMD graphics processors are equivalent, both encompassing the same GPU technology (Cypress), core count (1,440) and memory (2 GB). Like the 9350, the V7800P delivers about 2 single precision teraflops or 400 double precision gigaflops. The extra graphics support on the FirePro just makes it a two-for-one deal for the datacenter. “It’s really an IT management ease-of-use solution,” Furman told me.

AMD didn’t invent the dual-use concept. NVIDIA introduced a graphics/visualization-capable Tesla part last year in the M2070Q, a variant of the M2070 with Quadro graphics features enabled (the Q stands for Quadro). Like the FirePro V7800P, the M2070Q is aimed at users who want to build an all-in-one visualization/compute cluster.

A number of OEMs picked up on the M2070Q including IBM, who is offering it with its iDataPlex dx360 M3 as a RemoteFX server that can also moonlight as a GPU computer. IBM literature says 84 of these servers, each with two M2070Qs, can support up to 1,000 users, or about six users per Tesla device, in a RemoteFX VDI environment.

Dell, on the other hand, opted for the FirePro V7800P in its dual-use GPU server offering. For this purpose, the company is using the new FirePro in their PowerEdge M610x blade. That’s a nice endorsement for AMD, especially when you consider that Dell offers the regular NVIDIA M2050 and M2070 modules in that same server for straight up GPU computing.

For visualization applications, and especially VDI, the AMD offering looks somewhat more attractive. According to Furman, the FirePro V7800P can support up to 16 users per card, as opposed to the six claimed for the IBM-M2070Q setup. (That’s for vanilla desktop graphics, not for things like HD Blue Ray streaming or 3D gaming.) That makes sense, given that the FirePro has about twice the raw graphics capability — as evidenced by its 2 teraflops of single-precision — compared to the Tesla part.

HPC-wise, the Tesla offering looks more compelling, with a slight edge over the FirePro part in double-precision performance (515 gigaflops versus 400 gigaflops), a substantial edge in memory capacity (6 GB versus 2 GB), and a huge advantage in its support for features like ECC memory, L1 and L2 caches, asynchronous data transfers, and concurrent kernels. All of that capability comes with a power penalty, however; the M2070Q chews up 225 watts, compared to the V7800P at a more modest 138 watts.

If you can live with some of the compute shortcomings, AMD’s offering is certainly priced to sell. With an MSRP of $1,249, the FirePro V7800P is less than half the cost of a M2070Q. The retail price for the more compute-endowed Tesla module is $5,000 and up, although presumably IBM and other OEMs are getting a better deal than that. The more attractive price and lower wattage could be the reasons Dell decided to go with the AMD part for its M610x blade.

Whether dual-use GPU server infrastructure catches on or not remains to be seen. The compute-loving FireStream and Tesla parts are cheaper than their dual-GPU counterparts, so if you don’t need to serve up graphics, the choice is obvious. The success of these GPUs will hinge on how important server-side visualization becomes, and if technologies like Microsoft’s RemoteFX get some traction.

“We’re definitely excited about putting graphics in the datacenter,” said Furman “We’ve put a lot of CPUs in there. Now we have a reason to put our GPUs in there as well.”

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!

UK to Launch Six Major HPC Centers

March 27, 2017

Six high performance computing centers will be formally launched in the U.K. later this week intended to provide wider access to HPC resources to U.K. Read more…

By John Russell

AI in the News: Rao in at Intel, Ng out at Baidu, Nvidia on at Tencent Cloud

March 26, 2017

Just as AI has become the leitmotif of the advanced scale computing market, infusing much of the conversation about HPC in commercial and industrial spheres, it also is impacting high-level management changes in the industry. Read more…

By Doug Black

Scalable Informatics Ceases Operations

March 23, 2017

On the same day we reported on the uncertain future for HPC compiler company PathScale, we are sad to learn that another HPC vendor, Scalable Informatics, is closing its doors. Read more…

By Tiffany Trader

‘Strategies in Biomedical Data Science’ Advances IT-Research Synergies

March 23, 2017

“Strategies in Biomedical Data Science: Driving Force for Innovation” by Jay A. Etchings is both an introductory text and a field guide for anyone working with biomedical data. Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Quants Achieving Maximum Compute Power without the Learning Curve

The financial services industry is a fast-paced and data-intensive environment, and financial firms are realizing that they must modernize their IT infrastructures and invest in high performance computing (HPC) tools in order to survive. Read more…

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

Google Launches New Machine Learning Journal

March 22, 2017

On Monday, Google announced plans to launch a new peer review journal and “ecosystem” Read more…

By John Russell

Swiss Researchers Peer Inside Chips with Improved X-Ray Imaging

March 22, 2017

Peering inside semiconductor chips using x-ray imaging isn’t new, but the technique hasn’t been especially good or easy to accomplish. Read more…

By John Russell

LANL Simulation Shows Massive Black Holes Break ‘Speed Limit’

March 21, 2017

A new computer simulation based on codes developed at Los Alamos National Laboratory (LANL) is shedding light on how supermassive black holes could have formed in the early universe contrary to most prior models which impose a limit on how fast these massive ‘objects’ can form. Read more…

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

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

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

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

New Japanese Supercomputing Project Targets Exascale

March 14, 2017

Another Japanese supercomputing project was revealed this week, this one from emerging supercomputer maker, ExaScaler Inc., and Keio University. The partners are working on an original supercomputer design with exascale aspirations. Read more…

By Tiffany Trader

Nvidia Debuts HGX-1 for Cloud; Announces Fujitsu AI Deal

March 9, 2017

On Monday Nvidia announced a major deal with Fujitsu to help build an AI supercomputer for RIKEN using 24 DGX-1 servers. Read more…

By John Russell

HPC4Mfg Advances State-of-the-Art for American Manufacturing

March 9, 2017

Last Friday (March 3, 2017), the High Performance Computing for Manufacturing (HPC4Mfg) program held an industry engagement day workshop in San Diego, bringing together members of the US manufacturing community, national laboratories and universities to discuss the role of high-performance computing as an innovation engine for American manufacturing. Read more…

By Tiffany Trader

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

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

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

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

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

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

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

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Leading Solution Providers

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

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. 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

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

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. 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

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