![]() ![]() Ensure you have the latest kernel by selecting Check for updates in the Windows Update section of the Settings app. Once you've installed the above driver, ensure you enable WSL and install a glibc-based distribution (such as Ubuntu or Debian). During the ZED SDK installation, if CUDA is. Install the GPU driver Download and install the NVIDIA CUDA enabled driver for WSL to use with your existing CUDA ML workflows. ii) You must have the NVIDIA GPU drivers installed on your computer. Install Windows 11 or Windows 10, version 21H2 To use these features, you can download and install Windows 11 or Windows 10, version 21H2. ![]() The CUDA installation packages can be found on the CUDA Downloads Page. ![]() For convenience, NVIDIA includes a compatible CUDA driver with the toolkit. CUDA on Windows Subsystem for Linux (WSL) CUDA is an NVIDIA library used by the ZED SDK to run fast AI and computer vision tasks on your graphics card. i) You must have an NVIDIA GPU installed on your computer. NVIDIA CUDA Toolkit and compatible CUDA driver is required for CUDALink to work.With the CUDA Toolkit, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms, and HPC supercomputers. For more info about which driver to install, see: The Nvidia CUDA Toolkit provides a development environment for creating high-performance GPU-accelerated applications. Install the GPU driverÄownload and install the NVIDIA CUDA enabled driver for WSL to use with your existing CUDA ML workflows. To use these features, you can download and install Windows 11 or Windows 10, version 21H2. Install Windows 11 or Windows 10, version 21H2 This includes PyTorch and TensorFlow as well as all the Docker and NVIDIA Container Toolkit support available in a native Linux environment. The toolkit includes a container runtime library and utilities. Windows 11 and Windows 10, version 21H2 support running existing ML tools, libraries, and popular frameworks that use NVIDIA CUDA for GPU hardware acceleration inside a Windows Subsystem for Linux (WSL) instance. The NVIDIA Container Toolkit allows users to build and run GPU accelerated Docker containers. CUDA is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). ![]()
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