numba
https://github.com/numba/numba
Python
NumPy aware dynamic Python compiler using LLVM
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- Issues
- Slight Difference in Float Results When Using @jit
- General matrix product (GEMM) segfault on M3 Max for "scipy<1.9"
- Inconsistent Results with jit and `np.digitize`/`np.quantile`
- NumPy 2.2 support
- Lint `core/tracing.py` using `flake8`
- Lint `core/withcontexts.py` using `flake8`
- Support for `complex64` & `complex128` in `numba.cfunc` signature
- [Doc] Add paddle as adopted the CUDA Array
- Large overhead when launching kernel with torch tensors
- ENH: Support for unicode_type in guvectorize
- Docs
- Python not yet supported