Microsoft’s Windows Subsystem for Linux (WSL) enables Windows users to run native, unmodified Linux command-line tools directly on Windows. WSL was announced 4 years ago, at Microsoft Build 2016, and Microsoft says it now runs on more than 3.5 million monthly active devices.
Today Microsoft announced the availability of GPU compute, often used in Machine Learning, on WSL 2.
Microsoft says adding GPU compute support to WSL has been their #1 most requested feature since the first release.
The preview of GPU compute is now available within WSL 2 to Windows Insiders (Build 20150 or higher). This preview will initially support artificial intelligence (AI) and machine learning (ML) workflows, enabling professionals and students alike to run ML training workloads across the breadth of GPUs in the Windows ecosystem.
Enabling professionals through NVIDIA CUDA support
NVIDIA CUDA support has been present on Windows for years. However, there is a variety of CUDA compute applications that only run in a native Linux environment. In support of meeting professional data scientists where they’re at Microsoft, in partnership with NVIDIA, is adding support for CUDA inside WSL 2.
The preview includes support for existing ML tools, libraries, and popular frameworks, including PyTorch and TensorFlow. As well as all the Docker and NVIDIA Container Toolkit support available in a native Linux environment, allowing containerized GPU workloads built to run on Linux to run as-is inside WSL 2.
“Accelerated computing is essential for modern AI and data science, while users want the flexibility to wield this power wherever their work takes them. With CUDA on NVIDIA GPUs in the Public Preview of the Windows Subsystem for Linux 2, a new class of proven, accelerated workloads is available to Windows users.” – Chris Lamb, VP of Computing Software Platforms, NVIDIA
Empowering students and beginners through DirectML
Over the past few years, there has also been an increasing demand for introductory coursework in AI and ML, with online learning platforms playing a key role in educating the workforce and students.
Today, Microsoft is releasing a preview package of TensorFlow with a DirectML backend. Students and beginners can start with the TensorFlow tutorial models or our examples to start building the foundation for their future. In line with this, Microsoft is also engaging with the TensorFlow community through their RFC process. Microsoft plan to open source their extension of the TensorFlow code base that works with DirectML in the coming months. They are also continuing to engage with the community to determine the best path for upstreaming their changes into TensorFlow as it evolves.
“We’re excited to work with Microsoft on these new capabilities and empower students and beginners alike to use their existing AMD hardware and expand their skills in machine learning.” – Andrej Zdravkovic, Corporate Vice President for Software, AMD
“Through working with Microsoft we’re excited that millions of students, researchers and experimenters can now train models leveraging Intel’s GPU hardware acceleration on hundreds of millions of PCs in the world.” – Lisa Pearce, VP Graphics SW Engineering, Intel
Try out the preview
In order to get your system setup users should read Microsoft’s getting started documentation.
Read more at Microsoft’s blog post here.