Putting AI/ML aside, I have a question for graphics experts or/and gamers: what is the practical [1] ceiling of the current champion, the 1080ti? I was under impression that that card already was much more than most people needed. In other words, is the new generation only useful for 4K gaming? [1] By "practical" I mean on 1440p@144Hz monitors.
VR, for one, is going to (eventually) have insane resolution and performance requirements: a flat 90 to 120fps with perhaps 4K resolution for each eye.
Even my regular 1080 has trouble with a few current-gen games.
video professionals should use the Turing powered Quadros, these are for gamers
It's a spectrum. Not every professional wants and/or can afford the top end cards. Many professionals (i.e. those who make money doing a thing) have been using high-end gaming cards for work pretty much since they existed. There's also the long-running debate as to the actual value of the 'pro' line of video cards for non-mission critical purposes (enough of one that nVidia in their license prohibited the use of gami…
But they are the low-to-mid segment of professionals doing weddings and local business presentations with median income around $50k. The ones doing interesting work can't live without real 10-bit HDR on calibrated 4k screens for realistic printing/video projections, without proper 5k+ RAW cameras and top-end lens etc. and those are extremely expensive.
Wow you have really compelling arguments as to why crypto isn't collapsing! Thanks you for you insight
Let's see your argument for it collapsing. It's been very volatile sure, but you'd still get insane gains if you invested just last year. BTC has gone up 45% in the past year. 1015% in 2 years. source: https://cryptowat.ch/ Collapsing.
The cost to settle a transaction is prohibitively high on GPUs, so is mining. Crypto might be fine with ASICs after this downward movement, perhaps, but GPUs are quickly going out of the loop due to cost/performance ratio.
Prices must include VAT in Europe, which seems to account for that 20% plus you’re referring to.
But that's about covered by the difference in exchange rate. A few years ago prices where mostly 1:1 in USD before taxes and EUR after taxes. So the situation got worse. I think the main reason is not that anything makes selling the cards there more expensive, but simply that they try to charge more.
Exchange rates fluctuate, often it’s been ~1.05:1 which is a long way from covering the 20% VAT. Add some uncertainty, stronger consumer protection laws, and smaller markets and the price difference is relatively small.
Wow you have really compelling arguments as to why crypto isn't collapsing! Thanks you for you insight
Let's see your argument for it collapsing. It's been very volatile sure, but you'd still get insane gains if you invested just last year. BTC has gone up 45% in the past year. 1015% in 2 years. source: https://cryptowat.ch/ Collapsing.
Anyone know if the raytracing cores on these things can be used to accelerate Shadertoy style raymarching stuff? This technique has been threatening to break through into the mainstream for a while now.
It could, but to the best of my knowledge the OpenGL(/es) Vulkan extensions for raytracing don't exist yet as standards or implementation. But most of the Shadertoy raymarching scenes could be implemented using the raytracing API and custom intersecting functions.
I'm personally curious about the performance on custom intersections with the new hardware. Shadertoy demos have a lot of flexibility and tend more towards procedural geometry, since polygonal ray intersection is hard. The new hardware raytracing will be highly optimized for polygonal geometry though, since that's the bread and butter of current realtime engines.
Guessing that you'll provide a simple bounding primitive for it to do the ray test against, and then it will fall back on more or less identical shader code to resolve the custom ray intersection.
Hmm, 24%-42% performance increase (14/16TFlops vs 11.3TFlops) for 70-90% price increase... And prices were already inflated by crypto that is now collapsing. Not sure who is the target market for this tech honestly. Still only 11GB RAM, even if 50% faster, making it a nonsense purchase for Deep Learning enthusiasts (state-of-art models are already larger). Unless somebody invented RTX-based coin of course, then this…
Whether it's substantially better for deep learning depends on whether they chose to neuter fp16 like they did in all other consumer GPUs. The main bottleneck is not actually the size of the model per se (sizes of the models have been mostly going _down_ as of late), it's the size of the batch during training. Both batch size and model size determine the size of the main memory hog: activations that you need to keep to do training. You don't need to keep activations to do inference: you can discard them after they're fed into the next layer. So it's not entirely accurate to say that this is useless for DL. What could make it totally kickass for AI would be a proper, non-neutered implementation of fp16, similar to what you'd find in P100, V100 and (surprisingly) Jetson TX2, which would effectively double the possible batch size, which in turn leads to quicker convergence. It could also halve the model size as an added bonus. This is NVIDIA, however, so I would bet good money fp16 is still neutered in "consumer" SKUs.
Realtime ray tracing will take us there and this is the first hardware generation to offer dedicated hardware acceleration for that which makes it practical for games for the first time. Don't expect things to change over night though, it will be a while before this hardware is mainstream and a while before rendering engines are designed around it. We'll see hybrid rendering approaches first and there's no upper limi…
Triangles and fragments per second for rasterization grew exponentially because of growth in circuit performance . Ray tracing needs to grow say 3 orders of magnitude in performance now (at least) but do so without (that) massive advances in semiconductors. That will be a challenge.
Depends what you mean by 'needs'. The combination of dedicated ray tracing acceleration hardware and APIs to drive it with some remarkable advances in denoising, in part driven by deep learning plus associated dedicated hardware, means that we are at a threshold where hybrid techniques that mix rasterization with ray tracing are viable for games and can advance the state of the art in real time rendered image quality.
That certainly doesn't mean real time rendering is 'solved'. We could certainly use another 3 orders of magnitude compute performance (and more) if we had it to get better visuals. That's pretty much always been true for graphics though.