NumbaΒΆ
This is the Numba documentation. Unless you are already acquainted with Numba, we suggest you start with the User manual.
- User Manual
- Overview
- Getting started
- Compiling Python code with
@jit
- Flexible specializations with
@generated_jit
- Creating Numpy universal functions
- Compiling python classes with @jitclass
- Creating C callbacks with
@cfunc
- Compiling code ahead of time
- Automatic parallelization with
@jit
- Troubleshooting and tips
- Frequently Asked Questions
- Examples
- Reference Manual
- Numba for CUDA GPUs
- Overview
- Writing CUDA Kernels
- Memory management
- Writing Device Functions
- Supported Python features in CUDA Python
- Supported Atomic Operations
- Random Number Generation
- Device management
- The Device List
- Examples
- Debugging CUDA Python with the the CUDA Simulator
- GPU Reduction
- CUDA Ufuncs and Generalized Ufuncs
- Sharing CUDA Memory
- CUDA Frequently Asked Questions
- CUDA Python Reference
- Numba for HSA APUs
- Extending Numba
- Developer Manual
- Numba Enhancement Proposals
- Glossary
- Release Notes
- Version 0.34.0.dev
- Version 0.33.0
- Version 0.32.0
- Version 0.31.0
- Version 0.30.1
- Version 0.30.0
- Version 0.29.0
- Version 0.28.1
- Version 0.28.0
- Version 0.27.0
- Version 0.26.0
- Version 0.25.0
- Version 0.24.0
- Version 0.23.1
- Version 0.23.0
- Version 0.22.1
- Version 0.22.0
- Version 0.21.0
- Version 0.20.0
- Version 0.19.2
- Version 0.19.1
- Version 0.19.0
- Version 0.18.2
- Version 0.18.1
- Version 0.17.0
- Version 0.16.0
- Version 0.15.1
- Version 0.15
- Version 0.14
- Version 0.13.4
- Version 0.13.3
- Version 0.13.2
- Version 0.13.1
- Version 0.13
- Version 0.12.2
- Version 0.12.1
- Version 0.12
- Version 0.11
- Version 0.10
- Version 0.9
- Version 0.8
- Version 0.7.2
- Version 0.7.1
- Version 0.7
- Version 0.6.1
- Version 0.6
- Version 0.5
- Version 0.4
- Version 0.3.2
- Version 0.3
- Version 0.2