NVIDIA 5090 in 2024b

81 次查看（过去 30 天）
ジュアキム カレーラス
评论： Walter Roberson 2025-7-11
I upgraded gpu from nvidia 4080super to 5090, and now using matlab 2024b to train a resnet18 for image classification (transfer learning). I note that GPU is not working. As I understand from a previous comment, it is too early for native support of 5090 on date 2025/06/07.
(1) Is the support enabled in 2025a?
(2) I saw a comment with a solution. As I understood, I just add this code before my own code
tf = parallel.gpu.enableCUDAForwardCompatibility()
parallel.gpu.enableCUDAForwardCompatibility(tf)
(3) However, I read "Enabling forward compatibility can result in wrong answers and unexpected behavior during GPU computations." Not sure what this exactly means, will the matlab-gpu make "mistakes" during the deep learning computation and/or network performance will be degradated? If this is the case, then better reinstall 4080super?
Thank you very much for your understanding and help.
  2 个评论
MANUEL
MANUEL 2025-7-11

I installed Matlab R2025a today and my RTX 5090 is not working. Parallel indicates that this GPU is not supported. I will switch to my RTX 4070 ti.

Walter Roberson
Walter Roberson 2025-7-11
@MANUEL
Make sure you do
parallel.gpu.enableCUDAForwardCompatibility(1)

请先登录，再进行评论。

请先登录，再回答此问题。

回答（1 个）

Joss Knight
Joss Knight 2025-6-6

We don't test MATLAB under forward compatibility, in the past it has had missing features in some NVIDIA libraries, and by its nature it is guaranteed to be less well optimized (you can't optimize for future hardware). So what we're saying is, use at your own risk.

That said, we have run some tests and everything seems to work, and basic performance tests have given reasonable results. This is a result of some extra effort from NVIDIA in CUDA 12 so well done them.

In answer to your question, if your Blackwell cards are not faster I'd say wait for R2025b.

  3 个评论
显示 1更早的评论
Joss Knight
Joss Knight 2025-6-6
编辑：Joss Knight 2025-6-6

By the way, your code doesn't look right, you need parallel.gpu.enableCUDAForwardCompatibility(true)

Still, looks like whatever you did it worked.

ジュアキム カレーラス
ジュアキム カレーラス 2025-6-6
tf = parallel.gpu.enableCUDAForwardCompatibility()
parallel.gpu.enableCUDAForwardCompatibility(1)
tf = parallel.gpu.enableCUDAForwardCompatibility()
gpuDeviceCount("available")
gpuDeviceTable
gpuDevice(1);
A = ones(100,'gpuArray');

请先登录，再进行评论。

类别

在 Help Center 和 File Exchange 中查找有关 GPU Computing 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by