Adding GPU compute support to Windows Subsystem for Linux (WSL) has been the #1 most requested feature since the first WSL release.

Learn how Windows and WSL 2 now support GPU Accelerated Machine Learning (GPU compute) using NVIDIA CUDA, including TensorFlow and PyTorch, as well as all the Docker and NVIDIA Container Toolkit support available in a native Linux environment.

Clark Rahig will explain a bit about what it means to accelerate your GPU to help with training Machine Learning (ML) models, introducing concepts like parallelism, and then showing how to set up and run your full ML workflow (including GPU acceleration) with NVIDIA CUDA and TensorFlow in WSL 2.

Additionally, Clarke will demonstrate how students and beginners can start building knowledge in the Machine Learning (ML) space on their existing hardware by using the TensorFlow with DirectML package.

Learn more:

Gary Explains the release of WSL2.

WSL2 will officially be part of Windows 10, version 2004, which will be rolled out very soon. The design of WSL 2 is quite different to WSL 1. It includes a real Linux kernel, not just a compatibility layer, which means you can run Docker. Here is a quick look at WSL 2 and a quick demo on Ubuntu running inside of Ubuntu running inside Windows!