You can optionally download NVIDIA’s CUDA code samples and review CUDA’s Programming Guide to learn more about developing software to take advantage of a GPU instance. Open a terminal app and run the command nvcc -version. In some situations, you might not be able to upgrade NVIDIA CUDA drivers on a regular basis. Getting the Version Number of Installed CUDA. This procedure is considered experimental. You should now be ready to run your CUDA-optimized workloads. The output will display the version number of the NVIDIA driver installed on your Linux machine and the maximum version of CUDA supported by that driver. This command should output details about the driver version, CUDA version, and the GPU itself. Run nvidia-smi to verify that the NVIDIA drivers and CUDA Toolkit are installed successfully. Reboot the GPU instance after all the commands have completed successfully. The Download Installer (or similar) section should appear and display a list of commands needed to download and install the CUDA Toolkit. Installer Type: rpm (local) for distributions using rpm packages or deb (local) for distributions deb packages.If you have not installed a stand-alone driver, install the driver from the NVIDIA CUDA Toolkit. ![]()
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