numba
https://github.com/numba/numba
Python
NumPy aware dynamic Python compiler using LLVM
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- Issues
- Elapsed running time of parallel jit for the logistic regression documentation example is dozens of seconds
- Shall we consider using an envvar to disable refct atomic instructions
- In some cases, Numba 0.57.1 (can also be reproduced in 0.59.0) does not assign values to a NumPy array
- Add .tobytes() method
- Added is identity comparison for numpy records and added tests as is_comparison_tests.py
- Cannot find source for CUDA kernels decorated with `lineinfo=True` when executed from Jupyter notebook cell
- numpy records do not support "is" identity comparison.
- emit a warning/error if enabling `boundscheck=True` together with `parallel=True` (raising exceptions from within threads has unspecified behaviour)
- Support parallel dynamic gufuncs
- Change definition of complex sign if numpy does
- Docs
- Python not yet supported