What about support for NVidia cards for option TargetDevice->"GPU" in such things as Classify and other neural net-related functions?

That is already supported out-of-the-box in 11.3.0.

Given the long-time status of Mathematica as essentially platform-independent, it seems really constricting that only CUDA with NVidia is supported whereas OpenCL with AMD is not.

That has more to do with CUDA being the de-facto standard for most of the state-of-the-art neural network libraries (like MXNet), which Mathematica uses under the hood. If the libraries we use add support for OpenCL then we'd certainly investigate adding support from our end.

I meant: "What about support for AMD cards". Sorry for the confusion.

In regards to the neural network framework in Mathematica 11.3, the reason why OpenCL isn't supported is that it hasn't been implemented in ML library/framework, MXNet. Please do reference the following Github issue:

MXNet Support for other Device Types, OpenCL AMD GPU

We had hoped to have updated CUDALink paclets ready for 11.3 release but we ran into some technical issues that had to be resolved first. We plan to release updated CUDALink paclets with CUDA 9.1 support in the next few days, assuming the lingering issues can be ironed out in time.

Do you support MacBook Pros with NVIDIA cards (from 2014 and before)?

For quite some time now (i.e. even in 11.2), TargetDevice -> "GPU" works for me only if I load CUDALink first, and then successfully evaluate CUDAQ[]. By "successfully" I mean that I'm lucky and it doesn't cause a crash. Often, the kernel just crashes after CUDAQ[].

In earlier versions (11.0? 11.1? I don't remember) both TargetDevice -> "GPU" and CUDALink used to work fine on this machine.

I have macOS 10.13, the NVIDIA web driver, and CUDA driver version 387.128.

I must have mixed up my versions ... I was certain that I just tried this in 11.3 ("ReleaseID" -> "11.3.0.0 (5944637, 2018030701)") and it did not work. Now I tried it again and TargetDevice -> "GPU" seems to be working fine.

Sorry to say Sebastian, but you are really out of touch with what got delivered to your customers with 11.3 release.... Your team member (and customers) had to tell you that the CUDA paclet was downgraded with 11.3 release

I am one of the developers of the neural net framework. I have nothing to do with CUDALink (and as mentioned in this thread, CUDALink is not used by the neural net framework at all), and indeed I had no idea what issues CUDALink faced in 11.3.

I can however speak authoritatively about the neural net framework, which is the title of this post (ie neural net slowdowns in 11.3, for which the discussion seems to have ended). You are replying to a subthread where I claimed that this is fixed:

For quite some time now (i.e. even in 11.2), TargetDevice -> "GPU" works for me only if I load CUDALink first

This was a bug in the neural net framework, which I was involved with fixing. It seems your real issues are about CUDALink, for which I have nothing to add to the discussion.

The issue I described above is fixed by upgrading the NVidia driver to version 391.03. This release was mentioned by Nettrain (387+) that didn't work in MM11.3 but did work with 11.2. Windows claimed the driver was up to date but the NVidia site showed newer versions.

Thank you very much!

Finally CUDA 9.1 with Visual Studio 2017 compiler supported :-)

But CUDACCompilers is still like in Mathematica 11.2 not funtional. But in SytemInformation Toolkit Version 4. is listed. Should this not be 9.1 ? And the Core Count says 320 while my GeForce GTX1060 with Max-Q Design has 1280 cores!

One thing that should also be mentioned: Neural Nets in the WL don't use CUDALink` at all, so this issue has no effect on the neural net framework which uses CUDA 8 on OSX and CUDA 9.1 for Windows + Linux.

So CUDA 9.1 is present in the installation of Mathematica 11.3. Is this all precompiled code? Or do you need a C++ compiler like would be needed with the CUDA paclet?

We have now released updated CUDALink paclets for Mathematica 11.3. Please run CUDAResourcesInstall[Update -> True] to get the new version. We apologize for the delay.

Try doing PacletSiteUpdate/@PacletSites[] and then try again. You should get a paclet that has version "11.3.51".

The new ImageRestyle function continues to fail however. Is this a problem with CUDA or a problem with Neural Network package? Stefan? Sebastian?

Attachments:

Both say they are current for my OS version macOS 11.13.2 (17C89). See pictures below:

Attachments:

Stefan, this solution worked for me. Also, I see the correct results when evaluating SystemInformation[]

Sebastian, thank you for the information. Yes, the BatchSize seems to default to a much smaller value in 11.3 from 11.2, raising it from the default of 256 to 700 gets the timing down to 247 seconds in my test example. The MaxTrainingRounds seems to be the same value of 10 between the versions of MMA. The 247 seconds on MMA 11.3 is about 50 seconds faster than the results on 11.2. Raising the BatchSize above 700 (until the kernel crashes around 900) does not yield any improvement in speed. Is there anyway MMA can detect the limits of the GPU and not just crash?

Still evaluating error results.