Linking of cudart
gfardell opened this issue · 4 comments
As you know, for use with CIL we build tigre with conda and host under the ccpi channel
The environment we build in to contains the right version of the cudart redistributable shared library, and this should be automatically found and linked when running within the virtual environment.
However we have an issue where users need to install the cuda sdk installed in order to run tigre.
Commenting out these lines:
TIGRE/Python/tigre/__init__.py
Lines 9 to 19 in 729f146
The correct version of cudart is found automatically. With conda it's in somewhere like
C:\Users\[USER]\miniforge3\envs\[ENV]\Library\bin
With the lines it forces it to use the system installation - which if you're building and running on the same system isn't an issue but obviously our aim is easy redistribution and CUDA_HOME
is therefore often None
. Even if it's not None
it may not point to the right CUDA version.
I've read through the linked issues to the code, and still struggle to see why it would be necessary if PATH was set correctly to something like: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin
which contains cudart
.
Specifications
- MATLAB/python version: Python 3.10/3.11/3.12
- OS: win11 (and confirmed on win10)
- CUDA version: Building with 11.8, but previously had 10.2
Heya,
Admittedly, I don't know why this was changed. It always worked for me. I wonder if it for the cases where users install CUDA but not add it to PATH?
Is there maybe an alternative we can add that joins two things? something like if built_via_conda: elif hasattr(os, "add_dll_directory"):
that we can do, such that everyone is happy? All this is not much my strength admitedly.