[NLPL Task Force (A)] [uninett.no #202600] updates of CUDA Toolkit and cuDNN on Saga

[oe@ifi.uio.no via RT]

> We have installed
>
> CUDA/10.1.243-GCC-8.3.0
> cuDNN/7.6.4.38-gcccuda-2019b

many thanks for the quick follow-up, vegard!

i am wondering about the dependencies on specific GCCcore versions,
are they actually necessary in this case?  i am guessing these modules
provide the precompiled libraries and binaries distributed by NVDIA,
which in principle should be compatible with a bit of a range of
versions for GCC, binutils, and friends, or?  for RHEL 7.6, for
example, the CUDA Toolkit pages seem to only require a minimum GCC
version of 4.8.5.

i am asking because these kinds of dependencies can get in the way of
'mixing and matching' of modules, so if there were no actual
dependency on one specific version of GCCcore, it might make things
easier for us to not require GCCcore 8.3, so that one could for
example do something like:

$ module purge; module load Python/3.7.2-GCCcore-8.2.0
cuDNN/7.6.4.38-gcccuda-2019b

could one imagine rewriting the CUDA modules in a manner that would
inspect the current environment of active modules and just accept any
suitable version of GCC and binutils, if preloaded, and only bring in
GCC 8.3 if needed?

with thanks in advance, oe