Numba-CUDA
Numba-CUDA provides a CUDA target for the Numba Python JIT Compiler. It is used for writing SIMT kernels in Python, for providing Python bindings for accelerated device libraries, and as a compiler for user-defined functions in accelerated libraries like RAPIDS.
To install Numba-CUDA, see: Installation.
To get started writing CUDA kernels in Python with Numba, see Writing CUDA Kernels.
Browse the Examples to see a variety of use cases of Numba-CUDA.
Contents
- User guide
- Installation
- Writing CUDA Kernels
- Memory management
- Writing Device Functions
- Supported Python features in CUDA Python
- CUDA Fast Math
- Supported Atomic Operations
- Cooperative Groups
- Random Number Generation
- Device management
- The Device List
- Device UUIDs
- Examples
- Debugging CUDA Python with the the CUDA Simulator
- GPU Reduction
- CUDA Ufuncs and Generalized Ufuncs
- Sharing CUDA Memory
- CUDA Array Interface (Version 3)
- External Memory Management (EMM) Plugin interface
- CUDA Bindings
- Calling foreign functions from Python kernels
- Compiling Python functions for use with other languages
- On-disk Kernel Caching
- CUDA Minor Version Compatibility
- CUDA Frequently Asked Questions
- Reference documentation