If you're using GPUs for deep learning or other computationally intensive tasks, you may encounter a common error message that says "could not load dynamic library libcudart.so.11.0." This error can occur when there is a mismatch between the version of CUDA installed on your system and the version required by your software.
In this guide, we'll walk through the steps to troubleshoot and resolve this error on Linux systems.
Prerequisites
Before we begin, make sure you have the following prerequisites installed:
- NVIDIA GPU drivers
- CUDA Toolkit
- cuDNN library
If you haven't installed these yet, you can find instructions on the NVIDIA website: https://developer.nvidia.com/cuda-downloads
Step-by-step solution
Check the version of CUDA installed on your system by running the following command:
nvcc --version
Check the version of the libcudart library required by your software. This information is usually provided in the software documentation or error message.
If the version of libcudart required by your software is different from the version installed on your system, you can install the required version by running the following command:
sudo apt-get install libcudart<VERSION>
Replace <VERSION> with the version number of libcudart required by your software.
If you have multiple versions of CUDA installed on your system, you may need to set the LD_LIBRARY_PATH environment variable to point to the directory containing the required version of libcudart. For example:
export LD_LIBRARY_PATH=/usr/local/cuda-11.0/lib64:$LD_LIBRARY_PATH
Replace /usr/local/cuda-11.0 with the directory containing the required version of libcudart.
Restart any software that was giving the error message, and it should now be able to load the required version of libcudart.
FAQ
Q1. What is libcudart.so.11.0?
libcudart.so.11.0 is a library file that is part of the CUDA Toolkit. It provides functions and resources for GPU computing, such as memory management and kernel launching.
Q2. Why am I getting the "could not load dynamic library libcudart.so.11.0" error?
This error can occur when there is a mismatch between the version of CUDA installed on your system and the version required by your software.
Q3. How do I know which version of libcudart is required by my software?
This information is usually provided in the software documentation or error message.
Q4. How do I install a specific version of libcudart?
You can install a specific version of libcudart using the sudo apt-get install libcudart<VERSION> command, replacing <VERSION> with the version number you want to install.
Q5. How do I set the LD_LIBRARY_PATH environment variable?
You can set the LD_LIBRARY_PATH environment variable using the export command, followed by the directory containing the required version of libcudart. For example: export LD_LIBRARY_PATH=/usr/local/cuda-11.0/lib64:$LD_LIBRARY_PATH
Related links
- NVIDIA CUDA Toolkit documentation: https://docs.nvidia.com/cuda/
- cuDNN library download: https://developer.nvidia.com/cudnn-download-survey