Search Results for "numba"

Numba CUDA Target is NVIDIA’s maintained CUDA backend for the Numba JIT compiler, enabling developers to write GPU-accelerated code directly in Python. It allows users to define CUDA kernels using Python syntax, which are then compiled into efficient GPU code at runtime using LLVM-based toolchains. This approach significantly lowers the barrier to entry for GPU programming by eliminating the need to write CUDA C++ while still delivering high performance.

Numbast is an automated toolchain that bridges CUDA C++ and Python by generating Numba-compatible bindings directly from CUDA header files. Its primary goal is to eliminate the manual effort required to expose CUDA libraries to Python, enabling developers to use GPU-accelerated functionality in Python environments more easily. The system parses CUDA C++ declarations and converts them into Python bindings that can be used within Numba, allowing seamless integration with Python-based GPU workflows. ...

...Extensible graph framework is suitable for rapid development of custom operators and symbolic optimizations. Implements an extensible graph transpilation framework that currently provides compilation via C, JAX, and Numba. Based on one of the most widely-used Python tensor libraries: Theano.