inducer/pycuda

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

2051 stars · 298 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

PyCUDA is a Python wrapper giving Pythonic access to Nvidia's CUDA parallel computation API, including GPUArray multidimensional arrays and just-in-time kernel compilation. Its C++ base layer adds RAII resource cleanup, automatic error checking, and OpenGL interoperability with near-zero overhead.

Use cases

• run CUDA kernels from Python
• do GPU-accelerated array math with numpy-like GPUArray
• compile CUDA kernels at runtime with SourceModule
• write leak-free CUDA code with automatic resource cleanup
• interoperate CUDA with OpenGL
• accelerate scientific computing workloads on Nvidia GPUs

When to choose

• you need full access to the CUDA driver API from Python
• you want numpy-style GPU arrays and JIT kernel compilation
• you're doing scientific computing on Nvidia hardware and want mature, well-documented tooling

When to avoid

• you need cross-vendor GPU support (use PyOpenCL instead)
• you prefer higher-level frameworks like PyTorch or CuPy for array computing
• you don't have an Nvidia GPU or CUDA toolkit installed

Facets

library · maturity active

gpu-computing sdk math gpu-computing data-science developer-tools python windows cuda nvidia gpu-arrays scientific-computing numpy jit-compilation opengl-interop linux macos gpu

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