![]() ![]() ![]() By downloading and using the software, you agree to fully comply with the terms and conditions of the CUDA EULA. Then the package_path method can behave differently depending on that option. CUDA Toolkit 11.2 Update 2 Downloads Select Target Platform Click on the green buttons that describe your target platform. We might consider an option to run the download and installation script (instead of raising in the validate). Please Note: Due to an incompatibility issue, we advise users to defer updating to Linux Kernel 5. # Populate 'cpp_info' with the proper information # Depending on 'ttings' the libraries to use will be different # Maybe check output to validate version? n('some CUDA command to check it is installed') We have a policy to not package binaries that haven´t been built on our servers… it basically blocks this kind of recipe. Obviously, these cuda options should be disabled by default, since it’s a non portable feature, but at least consumers with CUDA capable GPU could enable them. With machine learning libs being packaged, it’s just not acceptable to unconditionally disable CUDA in these recipes (I’m not a data scientist, but worked with several people in this field, and I can’t remember someone not using CUDA). It should very likely not try to emulate/override findCUDA.cmake, which is complex The recipe should ensure that proper cuda version is already installed on the system and raise if not. I think that it should not be like current “system” recipes (I mean that version should be tracked). There was a dicussion about a cuda recipe here Normally packaged with the CUDA Toolkit, this stand-alone version of CUPTI provides improvements and bug fixes between toolkit releases. CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs).
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