RTX 3080 recompiling issue in Matlab 2020a

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I set new GPU RTX 3080 in my PC. While trainning my deep learning nework. A warning appears and then long wait. My Matlab version is R2020a. Matlab don't support this GPU model? or is there any other issue which I should do for normal training of my network. Thank you.
CUDA version is 10.1.
The warning is:
Warning: The CUDA driver must recompile the GPU libraries because your device is more recent than the libraries.
Recompiling can take several minutes. Learn more.

Accepted Answer

Ameer Hamza
Ameer Hamza on 30 Oct 2020
The new GPU series by NVIDIA is powered by Ampere Architecture. MATLAB still does not support this GPU properly. You will notice unexpected behavior for now: https://www.mathworks.com/help/parallel-computing/gpu-support-by-release.html
Walter Roberson
Walter Roberson on 30 Oct 2020
If the time-frames are similar to the past, R2021a would be expected to have full support for the Ampere devices.
Typically NVIDIA officially releases hardware quite close to Mathworks being about to issue a new release. For example the RTX 3080 was released to the public on September 17, 2020, whereas R2020b was released on September 16, 2020. Sometimes NVIDIA releases to the public quite late in August or early September; Mathworks most often releases on the Wednesday before the fall equinox, with the software having been out for beta testing for several months.
NVIDIA then has bugs that have to be fixed... though it sounds like they have a few more bugs than typical this time.
With the time for Mathworks to work up appropriate interfaces and do appropriate testing, and get the software to beta-testers, Mathworks would not typically have a compatible release for a new hardware line until spring; if the problems were especially bad, possibly not until the fall release after that.

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More Answers (1)

Joss Knight
Joss Knight on 2 Nov 2020
You should follow the advice on the GPU support by release page carefully, particularly with respect to setting your CUDA_CACHE_MAXSIZE environment variable. This ensures that you only see a single compilation delay rather than it occurring each time you run MATLAB.
Current testing shows that most functions in R2020b (or 20a) work correctly on Ampere cards although there is some incorrect behaviour for convolutional neural networks. Performance is somewhat reduced.
Joss Knight
Joss Knight on 1 Dec 2020
Thanks Walter.
By 'safe', I mean if you're doing Deep Learning you might get wrong answers and you won't necessarily be able to tell exactly when that's going to happen. However, if everything you're doing seems to work and you're not distributing your code or doing anything safely critical, I can't stop you going ahead and using it.
I expect Ampere to be natively supported in R2021a, and a workaround for the forward compatibility issues with Deep Learning is not out of the question for a between-release update in R2020b, if we can work out how to do it. Watch this space.

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