Registry / ai-ml / nvidia-cuda-cupti-cu11

nvidia-cuda-cupti-cu11

library11.8.87pypypiunverified

This package provides the CUDA Profiling Tools Interface (CUPTI) runtime libraries specifically for CUDA 11.x. It's a low-level dependency, typically used by higher-level deep learning frameworks like PyTorch and TensorFlow to enable GPU acceleration and profiling capabilities. The current version is 11.8.87. Releases are tied to NVIDIA CUDA Toolkit updates.

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INSTALL

IMPORT

SIG · NVIDIA-CUDA-CUPTI-

nvidia-cuda-cupti-cu11

ai-mlpythonv11.8.87

harness data pending

Install & Compatibility

Where this runs

No compatibility data collected yet for this library.

Code

Verified usage

This package itself does not expose direct Python symbols for import. Its successful installation enables other libraries, like PyTorch, to utilize CUDA. This quickstart demonstrates how to verify CUDA availability using PyTorch, which indirectly confirms the underlying CUDA libraries are functioning.

import os try: import torch if torch.cuda.is_available(): print("SUCCESS: CUDA is available via PyTorch!") print(f" CUDA device name: {torch.cuda.get_device_name(0)}") print(" This indicates underlying CUDA libraries (like CUPTI) are functional.") else: print("FAILURE: CUDA is NOT available via PyTorch.") print(" Check NVIDIA drivers, CUDA Toolkit installation, and compatibility.") except ImportError: print("WARNING: PyTorch not installed. Cannot directly verify CUDA availability.") print(" The 'nvidia-cuda-cupti-cu11' package provides C-level libraries, not direct Python imports.") print(" Its functionality is typically observed indirectly when deep learning frameworks use CUDA.")

Debug

Known issues

gotchaVersion Mismatch: The '-cu11' suffix denotes compatibility with CUDA 11.x. Using this package with environments set up for CUDA 12.x (e.g., 'nvidia-cuda-runtime-cu12') or other major versions will lead to runtime errors or failed GPU detection. Ensure all 'nvidia-cuda-*' packages match your intended CUDA major version.

fix

Align all `nvidia-cuda-*` packages (e.g., `nvidia-cuda-cupti-cu11`, `nvidia-cuda-runtime-cu11`) to the same CUDA major version (e.g., `cu11` for CUDA 11.x) that your deep learning framework expects.

affects: All versions

gotchaNo Direct Python Imports: This package provides C/C++ shared libraries (e.g., .so or .dll files) that deep learning frameworks link against at runtime. It is not intended for direct Python 'import' statements (e.g., `import cupti` will fail).

fix

Do not attempt to import this package directly in Python code. Its presence is verified indirectly when other CUDA-dependent libraries function correctly.

affects: All versions

gotchaIncomplete CUDA Environment: `nvidia-cuda-cupti-cu11` provides only the CUPTI component. A complete CUDA runtime environment typically requires other `nvidia-cuda-*` packages, such as `nvidia-cuda-runtime-cu11`, `nvidia-cuda-nvcc-cu11`, etc., depending on the framework's needs.

fix

Refer to the documentation of your deep learning framework (e.g., PyTorch, TensorFlow) for a list of recommended `nvidia-cuda-*` packages required for full CUDA functionality.

affects: All versions

gotchaPyPI vs. System CUDA Toolkit: These `nvidia-cuda-*` PyPI packages are designed to provide necessary CUDA libraries within your Python environment, often avoiding a full system-wide CUDA Toolkit installation. However, mixing these PyPI packages with a separate, manually installed system-wide NVIDIA CUDA Toolkit can lead to library conflicts (e.g., `LD_LIBRARY_PATH` issues).

fix

Prefer either a purely PyPI-based CUDA environment (if your framework supports it) or a system-wide CUDA Toolkit. Avoid installing both or ensure proper isolation (e.g., virtual environments) and careful management of library paths if combining them.

affects: All versions

Errors

Common errors & fixes

CUPTI could not be loaded or symbol could not be found.

A higher-level deep learning framework (e.g., TensorFlow, PyTorch) cannot find or properly initialize the CUDA Profiling Tools Interface (CUPTI) library, often due to incorrect environment variable settings, an incomplete CUDA Toolkit installation, or a version mismatch.

fix

Ensure the CUDA Toolkit is fully installed and the directory containing `libcupti.so` (typically `CUDA_PATH/extras/CUPTI/lib64` on Linux or `CUDA_PATH\extras\CUPTI\libx64` on Windows) is added to your `LD_LIBRARY_PATH` (Linux) or `PATH` (Windows) environment variable. Verify compatibility between your framework and CUDA versions.

Could not load dynamic library 'libcupti.so.X.Y'; dlerror: libcupti.so.X.Y: cannot open shared object file: No such file or directory

The system or an application is unable to locate a specific version of the `libcupti.so` shared library (or `cupti64_X.Y.dll` on Windows), usually because it's missing from the expected paths, the CUDA Toolkit installation is incomplete, or there's a version mismatch.

fix

Locate the actual `libcupti.so` file on your system (e.g., `find /usr/local/cuda -name 'libcupti.so*'`). If a different version exists, create a symbolic link to the expected version (e.g., `sudo ln -s /path/to/libcupti.so.INSTALLED_VERSION /path/to/libcupti.so.EXPECTED_VERSION`). Ensure the directory containing the library is in `LD_LIBRARY_PATH` (Linux) or `PATH` (Windows).

ImportError: libcupti.so.X.Y: cannot open shared object file: No such file or directory

A Python-based framework (like PyTorch) requires the `libcupti.so` shared library for GPU profiling but cannot find it, typically due to an incorrect `LD_LIBRARY_PATH` environment variable or a mismatch between the CUDA version expected by the framework and the one installed.

fix

Set the `LD_LIBRARY_PATH` environment variable to include the path to the `libcupti.so` file (e.g., `export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/extras/CUPTI/lib64`). In Conda environments, ensure `cudatoolkit` and `cuda-tools` packages are installed and compatible with your PyTorch version.

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Version history

11.8.87latest on PyPI · released Oct 3, 2022

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Dependencies

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Agent activity

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Resources

packagehttps://pypi.org/project/nvidia-cuda-cupti-cu11/ ↗

homepagehttps://developer.nvidia.com/cuda-zone ↗