use CMake builtin mechanisms for setting target CUDA architecture(s) #122
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Contributes to #115
As described at https://cmake.org/cmake/help/latest/variable/CMAKE_CUDA_ARCHITECTURES.html, if the target GPU architectures isn't explicitly provided to
CMake
, it falls back to a concrete (but system-and-compiler-specific) version.To help with that, #81 introduced two things:
CUDA_ARCH
native
(whatever GPU is detected on the system where the build is running)This proposes preserving that functionality, but in a different way:
CUDAARCHS
, which CMake has supported since v3.18 (docs link), instead of introducing a custom onepip install
Notes for Reviewers
Benefits of these changes
Reduces complexity in managing CUDA architecture, by reducing the number of paths through which configuration flows to CMake. This will be important when we introduce yet another build pattern (conda builds) here.
How I tested this
Added code like this at the bottom of the top-level
CMakeLists.txt
.Found the expected behavior for regular CMake builds,
build.sh
, andpip install
.