To update the distro to your favorite distro from the command line and to review other WSL commands, refer to the following resources:įrom this point you should be able to run any existing Linux application which requires CUDA. Refer to the system requirements in the Appendix.) Install NVIDIA GeForce Game Ready or NVIDIA RTX Quadro Windows 11 display driver on your system with a compatible GeForce or NVIDIA RTX/Quadro card from. Step 1: Install NVIDIA Driver for GPU Support To get started with running CUDA on WSL, complete these steps in order: 2.1. Refer to the NCCL Installation guide for Linux x86. Ģ2.04 or later 1.10 - Experimental Support for single GPU. Latest Linux CUDA toolkit package - WSL-Ubuntu from 11.x releases can be downloaded from. (Using driver r520+)ĭeveloper tools - Profilers - Volta and later (Using driver r525+ and Windows 11) Nsight Systems CLI, and CUPTI (Trace) - Volta and laterĭeveloper tools - Debuggers - From Pascal to Ampere. Refer to the NVIDIA Docker Deployment Guide for Linux x86. NVIDIA Container Toolkit - Minimum versions - v2.6.0 with libnvidia-container - 1.5.1+ Windows x86 drivers can be directly downloaded from for WSL 2 support on Pascal or later GPUs. Legacy CUDA IPC APIs are support from R510. NVIDIA-SMI will have a Limited Feature Set on WSL 2. R495 and later windows will have CUDA support for WSL 2. Use the latest Windows x86 production driver. This table captures the readiness and suggested software versions for NVIDIA software stack for WSL 2. NVIDIA Compute Software Support on WSL 2 This document describes a workflow for getting started with running CUDA applications or containers in a WSL 2 environment. Illustration of the possibilities with NVIDIA CUDA software stack on WSL 2 This offers flexibility and versatility while also serving to open up GPU accelerated computing by making it more accessible.įigure 1. WSL 2 is a key enabler in making GPU acceleration to be seamlessly shared between Windows and Linux applications on the same system a reality. NVIDIA driver support for WSL 2 includes not only CUDA but also DirectX and Direct ML support. GPU acceleration also serves to bring down the performance overhead of running an application inside a WSL like environment close to near-native by being able to pipeline more parallel work on the GPU with less CPU intervention. With NVIDIA CUDA support for WSL 2, developers can leverage NVIDIA GPU accelerated computing technology for data science, machine learning and inference on Windows through WSL. WSL 2 support for GPU allows for these applications to benefit from GPU accelerated computing and expands the domain of applications that can be developed on WSL 2. More importantly WSL 2 enables applications that were hitherto only available on Linux to be available on Windows. WSL enables users to have a seamless transition across the two environments without the need for a resource intensive traditional virtual machine and to improve productivity and develop using tools and integrate their workflow. Also this has historically restricted the development of seamless, well integrated tools and software systems across two dominant ecosystems. In both cases, developers have to stop all the work and then switch the system or reboot. install Linux and Windows in separate partitions on the same or different hard disks on the system and boot to the OS of choice. Use different systems for Linux and Windows, orĭual Boot i.e. Typically, developers working across both Linux and Windows environments have a very disruptive workflow. WSL 2 is tightly integrated with the Microsoft Windows operating system, which allows it to run Linux applications alongside and even interop with other Windows desktop and modern store apps.įor the rest of this user guide, WSL and WSL 2 may be used interchangeably. WSL 2 is characteristically a VM with a Linux WSL Kernel in it that provides full compatibility with mainstream Linux kernel allowing support for native Linux applications including popular Linux distros.įaster file system support and that’s more performant. Linux applications can run as is in WSL 2. CUDA support in this user guide is specifically for WSL 2, which is the second generation of WSL that offers the following benefits WSL or Windows Subsystem for Linux is a Windows feature that enables users to run native Linux applications, containers and command-line tools directly on Windows 11 and later OS builds. NVIDIA GPU Accelerated Computing on WSL 2 The guide for using NVIDIA CUDA on Windows Subsystem for Linux.
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