{"id":1586,"library":"nvidia-cuda-cupti","title":"NVIDIA CUDA CUPTI Runtime Libraries","description":"The `nvidia-cuda-cupti` package provides the CUDA Profiling Tools Interface (CUPTI) runtime libraries, essential for profiling CUDA applications. It's a low-level dependency that makes the necessary shared libraries available in the environment. The current version is 13.2.23, and it's released in alignment with NVIDIA's CUDA Toolkit versions.","status":"active","version":"13.2.23","language":"en","source_language":"en","source_url":"https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html","tags":["nvidia","cuda","cupti","profiling","gpu","runtime","low-level","dependency"],"install":[{"cmd":"pip install nvidia-cuda-cupti","lang":"bash","label":"Install via pip"}],"dependencies":[],"imports":[],"quickstart":{"code":"# This library provides low-level CUDA profiling tools runtime libraries.\n# It does NOT expose direct Python APIs for import and use via `import nvidia_cuda_cupti`.\n# Its primary purpose is to make the necessary C/C++ shared libraries (e.g., libcupti.so)\n# available in the environment for other Python libraries (e.g., PyTorch, TensorFlow, Numba, CuPy)\n# that interface with CUDA and CUPTI for profiling and performance analysis.\n\nprint(\"nvidia-cuda-cupti is installed as a runtime dependency.\")\nprint(\"It provides the CUPTI shared libraries for CUDA-enabled applications.\")\nprint(\"To verify its effect, you would typically use a profiling tool or framework that relies on CUPTI,\")\nprint(\"e.g., enabling profilers in PyTorch or TensorFlow, which would then leverage these libraries.\")\nprint(\"No direct Python interaction with this package is expected after installation.\")","lang":"python","description":"This quickstart demonstrates that `nvidia-cuda-cupti` is a runtime dependency without direct Python imports. Its presence is primarily for other CUDA-aware libraries to utilize its underlying C/C++ shared objects for profiling."},"warnings":[{"fix":"Simply install the package. Its effects are indirect, making CUPTI libraries available for other Python libraries like PyTorch or TensorFlow that rely on CUDA profiling.","message":"This package is a runtime distribution of C/C++ libraries, not a Python package with direct Python APIs. Do not attempt to import `nvidia_cuda_cupti` in your Python code, as it does not expose any Python symbols for direct use.","severity":"gotcha","affected_versions":"All versions"},{"fix":"Refer to the NVIDIA CUDA Toolkit release notes and compatibility matrix for the recommended versions. Mismatches can lead to runtime errors or incorrect profiling data.","message":"Compatibility with your CUDA Toolkit and GPU drivers is crucial. Ensure the version of `nvidia-cuda-cupti` is compatible with the CUDA Toolkit version used by your main deep learning frameworks (e.g., PyTorch, TensorFlow) and your NVIDIA GPU driver version.","severity":"gotcha","affected_versions":"All versions"},{"fix":"Prefer using `pip install nvidia-cuda-cupti` if your other libraries are designed to dynamically link to system-provided CUPTI. If a library explicitly bundles CUPTI, ensure its version is compatible or consider using a consistent environment (e.g., containers) to manage library versions.","message":"Potential for conflicts if other Python packages (e.g., specific PyTorch or TensorFlow builds) bundle their own versions of CUPTI libraries. This can lead to symbol conflicts or unexpected behavior.","severity":"gotcha","affected_versions":"All versions"}],"env_vars":null,"last_verified":"2026-04-09T00:00:00.000Z","next_check":"2026-07-08T00:00:00.000Z"}