Distributing CUDA runtime to customers but it's too big
At my company, we are building software that we need to push to customers when we update software (It's being pushed to custom hardware).
We have a GPU on that custom hardware that is fixed, but sometimes, we might need to upgrade the CUDA and CUDNN runtime if we upgrade things in our software (such as libtorch).
The problem now is that because of this, we have to ship CUDA and CUDNN together, which bloats the size of the binaries to over 2GB.
While the actual size of our executable is only 100MB. Is there any smart way around this?

https://pytorch.org doesn't advertize it, but there is a static version of libtorch available (replace 'shared' with 'static' in the URL).
Link against those libraries instead. Your binary will be a bit bigger (depending on how much of the library your code is using), but on the plus side you'll be saving 1.2GB there, because you don't have to ship the libraries.
CUDA and cuDNN should also have static versions available, although they might be missing in some re-distributions (like in Anaconda).
