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posted by cmn32480 on Thursday January 04 2018, @11:42PM   Printer-friendly
from the gotta-be-hip dept.

Nvidia's updated license for NVIDIA GeForce Software bans most usage of gaming-oriented GPUs in data centers, except for the purpose of "blockchain processing":

Nvidia has banned the use of its GeForce and Titan gaming graphics cards in data centers – forcing organizations to fork out for more expensive gear, like its latest Tesla V100 chips. The chip-design giant updated its GeForce and Titan software licensing in the past few days, adding a new clause that reads: "No Datacenter Deployment. The SOFTWARE is not licensed for datacenter deployment, except that blockchain processing in a datacenter is permitted."

In other words, if you wanted to bung a bunch of GeForce GPUs into a server box and use them to accelerate math-heavy software – such as machine learning, simulations and analytics – then, well, you can't without breaking your licensing agreement with Nvidia. Unless you're doing trendy blockchain stuff.

A copy of the license in the Google cache, dated December 31, 2017, shows no mention of the data center ban. Open the page today, and, oh look, data center use is verboten. To be precise, the controversial end-user license agreement (EULA) terms cover the drivers for Nvidia's GeForce GTX and Titan graphics cards. However, without Nvidia's proprietary drivers, you can't unlock the full potential of the hardware, so Nv has you over a barrel.

It's not just a blow for people building their own servers and data centers, it's a blow for any computer manufacturer – such as HPE or Dell – that hoped to flog GPU-accelerated servers, using GTX or Titan hardware, much cheaper than Nvidia charges for, say, its expensive DGX family of GPU-accelerated servers. A DGX-1 with Tesla V100 chips costs about $150,000 from Nvidia. A GeForce or Titan-powered box would cost much less albeit with much less processing power.

NVIDIA's DGX-1 product page.

Also at DataCenter Knowledge.


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  • (Score: 1) by Qlaras on Friday January 05 2018, @05:38PM

    by Qlaras (3198) on Friday January 05 2018, @05:38PM (#618405)

    (Some) uses for GPUs in a server:
    * Desktop virtualization - think Thin Clients; where all the heavy lifting is done by a box hosting anywhere from 1-200 users (depending on workload). Combined with virtualization (De-duplication) you can take 200 users' 100GB disk and make it all fit in 500GB. (Because the base OS and application would de-dupe really well; and make updates really easy to push out - update the master image, and on next login, the users use the updated base image)
    * Application virtualization - Similar to Desktop Virtualization, but you're just running one application remote. Useful for say, someone who has fairly normal office-user workload requirements except for one beefy application.
    * Application acceleration - anything doing math that is massively parallel can be re-written to benefit from the 500-3000 cores in a GPU instead of the 2-32 in a CPU.