Comments (3)
Sorry for lack of response @chr1sj0nes. Your ask implies you want to build cuda-python from source yourself. May I ask why?
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Within Google we build everything from source.
from cuda-python.
Within Google we build everything from source.
Yes, so I was told 🙂 But, I was also told that Google maintains a fork of the whole universe internally (and patch them as needed). Since NVRTC APIs are dlopen'd, it should be possible to patch setup.py with appropriate flags in your internal fork.
Currently we're hesitant to support this feature because of two reasons:
- We rely on public PyPI to deliver software, and we must do everything we can to avoid generating over-sized wheels. Static linking simply does not play well with the constraints we're facing.
- We do not have enough bandwidth to develop/maintain/test this additional option (and because of 1 we would basically treat this option as nonexistent)
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Related Issues (20)
- cross compilation failed HOT 23
- The tutorial in Overview page shows unexpected error HOT 4
- cuFFT support HOT 9
- getLocalRuntimeVersion return val wrong when exisit different version of cuda lib HOT 2
- test triage- will be deleted
- [EPIC] Python Object Model for CUDA HOT 2
- Produce stable artifacts HOT 2
- `nvrtcCreateProgram` only accepts lists HOT 1
- `cuLibraryLoadData` raises `TypeError: 'int' object is not iterable` HOT 2
- [EPIC] Python Object Model for Events HOT 1
- RFC: `cuda` namespace cleanup HOT 1
- Design stage
- Code implementation stage HOT 1
- Test coverage stage (test suite developed by engineering)
- Documentation stage
- QA test stage
- Set up a public, GitHub-Action-based CI infrastructure HOT 2
- "pip install ." fails with compile error HOT 1
- Add cudaMemcpyToSymbol HOT 4
- python HOT 1
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