- You have to scale down your problem to make sure it does not timeout (e.g. with a smaller network, or data size) or use a different card that does not timeout.
- Some GPUs allow one to set the compute mode to computations (TCC) only but others don't. As a possible workaround check if your GPU allows changing to that mode.
- Another possible workaround is to modify the registry to increase the TDR delay value as explained in the web page below:
Why do I get CUDA execution errors when training my network on a GPU?
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MathWorks Support Team
on 12 Jan 2021
Edited: MathWorks Support Team
on 19 May 2021
Why do I get the following error when training my neural network:
An unexpected error occurred during CUDA execution. The CUDA error was:
all CUDA-capable devices are busy or unavailable
The above only happens on a GPU and not on the CPU.
Accepted Answer
MathWorks Support Team
on 19 May 2021
Edited: MathWorks Support Team
on 19 May 2021
We suspect that the most likely issue is a kernel execution timeout.
To confirm this you can try running some GPUarray commands, such as:
A = gpuArray(rand(10))
B = A+1
If the above runs without any warnings and errors, it is likely due to kernel timeouts.
Some possible workarounds:
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