inducer/pycuda

What it solves

PyCUDA provides a way to access Nvidia's CUDA parallel computation API directly from Python, allowing developers to leverage GPU acceleration for computation-heavy tasks without writing full C++ applications.

How it works

It acts as a Pythonic wrapper around the CUDA driver API. It uses a C++ base layer for speed and implements RAII (Resource Acquisition Is Initialization) to automatically manage memory and object cleanup, preventing leaks and crashes. It provides high-level abstractions like SourceModule for managing CUDA kernels and GPUArray for handling data on the GPU.

Who it’s for

Developers and researchers who need to perform high-performance parallel computing on Nvidia GPUs using the Python language.

Highlights

• Automatic Resource Management: Uses RAII to ensure memory is freed and contexts are detached in the correct order.
• C++ Performance: The base layer is written in C++, ensuring that the Python wrappers add minimal overhead.
• Full API Access: Provides access to the full power of the CUDA driver API, including interoperability with OpenGL.
• Error Handling: Automatically translates CUDA errors into Python exceptions for easier debugging.