Hacker News Reader

Comment by ur-whale | Hacker News Reader

> Amazing! Simply amazing!

If it's such a cool feature, why does NVidia lock it away non-Tesla H/W?

[EDIT]: Funny, but the answers to this question actually provide way better answers to the other question I posted in this thread (as in: what is this for).

View on HN

Entirely for market segmentation. The ones they allow it on are much more expensive. With this someone could create a cloud game streaming service using normal consumer cards and dividing them up for a much cheaper experience than the $5k+ cards that they currently allow it on. The recent change to allow virtualization at all (removing the code 43 block) does allow some of that, but does not allow you to say take a 3090 and split it up for 4 customers and get 3060-like performance for each of them for a fraction of the cost.

The RTX A6000 is at USD 4650, with 48GB of VRAM and the full chip enabled (+ECC, vGPU, pro drivers of course)

The RTX 3090, with 24GB of VRAM is at USD 1499.

Customer dGPUs from other HW providers do not have virtualisation capabilities either.

Well, I believe intel has it on iGPUs just very well hidden

https://news.ycombinator.com/item?id=26367726

Not anymore.

I am interested in the recent change you are referring to. Is there a good article on how to use it on Windows or at least Linux?

The OP is referring to GPU passthrough setup[1], which passes through a GPU from Linux host to Windows guest (e.g. for gaming). This is done by detaching the GPU from the host and pass it to the VM, thus most setup requires two GPUs since one need to remain with the host (although single GPU passthrough is also possible).

Nvidia used to detect if the host is a VM and return error code 43 blocking them from being used (for market segmentation between GeForce and Quadro). This is usually solved by either patching VBIOS or hiding KVM from the guest, but it was painful and unreliable. Nvidia removed this limitation with RTX 30 series.

This vGPU feature unlock (TFA) would allow GPU to be virtualized without requiring the GPU to first be detached from the host, vastly simplify the setup and open up the possibility of having multiple VMs running on a single GPU, all with its own dedicated vGPU.

[1]: https://wiki.archlinux.org/index.php/PCI_passthrough_via_OVM...

Because otherwise, people would be able to use non-Tesla GPUs for cloud compute workloads, drastically reducing the cost of cloud GPU compute, and it would also enable the use of non-Tesla GPUs as local GPGPU clusters - additionally reducing workstation GPU sales due to more efficient resource use.

GPUs are a duopoly due to intellectual property laws and high costs of entry (the only companies I know of that are willing to compute are Chinese and only a result of sanctions), so for NVidia this just allows for more profit.

Interestingly, Intel is probably the most open with its GPUs, although it wasn't always that way; perhaps they realised they couldn't compete on performance alone.

Openness usually seems to be a feature of the runners up.

I think AMD is on par with Intel, no?

AMD do have great open source drivers, but they have longer lag behind with their code merges compared to Intel. Also at least a while ago their open documentation was quite lacking for newer generations of GPUs.

trivial arithmetic will tell you it's not the cost of the hardware that makes AWS and Azure GPU instances expensive.

Certainly, and both AWS, GCP and Azure even on CPU are much beyond simply hardware cost - there are hosts that are 2-3x cheaper for most uses with equivalent hardware resources.

Yeah, but now the comparison for many companies (e.g. R&D dept. is dabbling a bit in machine learning) becomes "buy one big box with 4x RTX 3090 for ~$10k and spin up VMs on that as needed", versus the cloud bill. Previously the cost of owning physical hardware with that capability would be a lot higher.

This has the potential to challenge the cloud case for sporadic GPU use, since cloud vendors cannot buy RTX cards. But it would require that the tooling becomes simple to use and reliable.

Ngreedia - the way it's meant to be paid™

To make people pay more.

Nvidia sells an ever greater percentage of their sales to the data-center market, and consumers purchase a shrinking portion. They do not want to flatten their currently upward trending data-center sales of high-end cards.

NVIDIA's stock price has doubled since March 2020, and most of these gains can be largely attributed to the outstanding growth of its data center segment. Data center revenue alone increased a whopping 80% year over year, bringing its revenue contribution to 37% of the total. Gaming still contributes 43% of the company's total revenues, but NVIDIA's rapid growth in data center sales fueled a 39% year-over-year increase in its companywide first-quarter revenues.

The world's growing reliance on public and private cloud services requires ever-increasing processing power, so the market available for capture is staggering in its potential. Already, NVIDIA's data center A100 GPU has been mass adopted by major cloud service providers and system builders, including Alibaba (NYSE:BABA) Cloud, Amazon (NASDAQ:AMZN) AWS, Dell Technologies (NYSE:DELL), Google (NASDAQ:GOOGL) Cloud Platform, and Microsoft (NASDAQ: MSFT) Azure.

https://www.fool.com/investing/2020/07/22/data-centers-hold-...

Reply on news.ycombinator.com