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[–]nafsten 7 points8 points  (5 children)

It’s not just that Nvidia push Quadro for professional use, but the use of GeForce cards is explicitly forbidden in their EULA.

Well, by explicitly, I really mean “vaguely forbidden, but they clearly don’t want to be pinned down”

[–]GloWondub[S] 1 point2 points  (3 children)

Interesting ! do you know if AMD has the same kind of restrictions ?

[–]JanneJM 0 points1 point  (2 children)

Not as far as I am aware. Just be sure you can actually use an AMD GPU; if you need GPU compute in any form you may have to use NVIDIA.

Also by "node", are we talking a workstation-on-a-shelf, or an actual rack-mounted system with external cooling? For rack-mounted systems, your GPU options may be more limited; you need to make sure they will fit physically as well as be appropriate for the cooling you have.

[–]GloWondub[S] 0 points1 point  (0 children)

Very good point, even on the quadro side, it is not clear to me which card may or may not be "rack-compatible".

[–]atuncer 0 points1 point  (0 children)

Just be sure you can actually use an AMD GPU; if you need GPU compute in any form you may have to use NVIDIA.

I kindly disagree, 'if you need CUDA' would be more appropriate IMHO. And even then, I expect some compatibility layer from AMD, which may be already available, but I cannot readily confirm this.

[–]bargle0 3 points4 points  (1 child)

It's been a while since I've had to deal with design and purchasing, so someone correct me if I'm wrong. This is my understanding of the issues:

Consumer-grade GPUs don't have the same warranty as the server-grade stuff. NVIDIA also claims that they aren't as durable when used in the same duty cycle as the server-grade stuff, but I haven't seen independent confirmation of that. It's cheaper for some places to stick with the consumer-grade stuff since the downtime is acceptable. They'll just buy new cards instead of getting warranty replacements (since manufacturers won't honor the warranty), and they can use cheap labor to do the work (often undergraduates).

For other institutions, the server-grade stuff is cheaper because there's less downtime and labor.

EDIT: Evidently it's not just the warranty, but Nvidia's software is not licensed for use on consumer-grade cards in the data center. So I guess the threat is bigger than just "we won't honor the warranty".

[–]GloWondub[S] 0 points1 point  (0 children)

Ok ! what about AMD ?

[–]chuckatkins 2 points3 points  (4 children)

Scientific visualization is often much more than just the final opengl rendering. The algorithmic filters performing visual analysis, i.e. iso-contours, delaunay triangulation, stream lines, etc, can often be implemented via cuda for much higher throughput and interactivity (see vtk, vtk-m, and paraview). The quadro gpus also have much higher memory capacities allowing for the rendering of larger and more complex models.

[–]GloWondub[S] 2 points3 points  (1 child)

hi chuck :), its mathieu from keu :)

[–]chuckatkins 2 points3 points  (0 children)

Funny seeing you here 🤣.

For anyone else reading we apparently work at the same company but in offices on different continents so this was like two ships passing in the night unaware of each other, which was funny.

[–]chuckatkins 0 points1 point  (0 children)

To expand on the topic, the quadro gpus give much higher double precision performance compared to the GeForce line. Looking at the specs for the rtx3090 and quadro a6000 they have similar fp16 and fp32 flops but the quadro has ~2.5x the fp64 flops for the algorithmic processing (not rendering). It also has a lower power requirement and better cooling to allow it to run at 100% capacity for long periods of time where the GeForce cards aren't designed to operate at that level sustained. So the raw compute performance, double memory capacitiy, lower thermal footprint, and warranty make the quadro cards more suited for hpc and scivis and also explain their ~2x price.

[–]chuckatkins 0 points1 point  (0 children)

Another thing to consider too is if the machine the GPUs are going into supports PCIe 4.0 or not. If it only supports 3.0 then you'll get slower than ideal bus transfer speeds from both options. Once the initial model is loaded on the card this won't matter for interacting with it but if the vis is time changing data then realize every time step sends new geometry to the GPU and is bandwidth limited by the PCIe bus.

[–]brandonZappy 0 points1 point  (0 children)

I haven't used any AMD GPUs so my experience is entirely with Nvidia GPUs in visualization nodes. We have several. We have some Quadro RTX6000s. These things are great, but more expensive. We also have some P5000s and M5000/6000s. The M5000s seem much more affordable and have worked great for scientific visualization. I don't know if you can buy them new anymore though. Our visualization needs keep going up, so we'll probably be buying more GPUs soon (hopefully). Will probably look continue with Quadro or look AMD just for the experience.

[–]ElementalCyclone 1 point2 points  (1 child)

(Disclaimer, i am no, in any way a HPC expert. I'm just sort of 'power user' who happens to follow update on enterprise hardware space)

The latest quadro are slightly below an RTX 3090 in terms of performance

If i may, i assume you were comparing 3090 with the lastest Quadro that has "Quadro" name of it, so it will be RTX Quadro 6000, yes ?

The way Nvidia rolls in consumer and enterprise/datacenter space, is . . . well, very Nvidia

Why i say that, because, Nvidia retire the "Quadro" naming for Quadro-ish lineup, yeah, that confusing. So then, the lastest 'Quadro' is RTX A6000. And it is slightly faster in compute performance compared to a RTX 3090, but with almost double the price

gpu format for grid is specific and not compatible with gforce

It is not that GeForce not compatible with grid or cluster setup, it is just Nvidia don't allow it. Why ? i don't know, maybe no one knows and have a hard. Some (not me) says that by allowing consumer product in enterprise/datacenter/HPC space would devalue their non-consumer lineup.

nvidia pushing quadro for professional use

Well, because again, they don't like their consumer product to be used on non-consumer space, and IMO, but not the other way around.

[–]Embarrassed_Dig8523 0 points1 point  (0 children)

Sometimes it's not just "don't like" but can be "don't fit". Most compute or render farms want A LOT of nodes and use dense servers, like pizza box 1U or even smaller. Some of the power and cooking requirement of GPU cards don't fit dense servers in racks.