[Offload] Allow CUDA Kernels to use arbitrarily large shared memory (#145963)

Previously, the user was not able to use more than 48 KB of shared
memory on NVIDIA GPUs. In order to do so, setting the function attribute
`CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK` is required, which was not
present in the code base. With this commit, we add the ability toset
this attribute, allowing the user to utilize the full power of their
GPU.

In order to not have to reset the function attribute for each launch of
the same kernel, we keep track of the maximum memory limit (as the
variable `MaxDynCGroupMemLimit`) and only set the attribute if our
desired amount exceeds the limit. By default, this limit is set to 48
KB.

Feedback is greatly appreciated, especially around setting the new
variable as mutable. I did this becuase the `launchImpl` method is const
and I am not able to modify my variable otherwise.

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Co-authored-by: Giorgi Gvalia <ggvalia@login33.chn.perlmutter.nersc.gov>
Co-authored-by: Giorgi Gvalia <ggvalia@login07.chn.perlmutter.nersc.gov>

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