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Ubuntu Weekly Newsletter and Canonical Make It Easier to Install NVIDIA CUDA on Ubuntu
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Ubuntu Fridge ☛ The Fridge: Ubuntu Weekly Newsletter Issue 909
Welcome to the Ubuntu Weekly Newsletter, Issue 909 for the week of September 7 – 13, 2025. The full version of this issue is available here.
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Ubuntu News ☛ Ubuntu Weekly Newsletter Issue 909
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OMG Ubuntu ☛ Canonical Make It Easier to Install NVIDIA CUDA on Ubuntu
Canonical will package and distribute NVIDIA CUDA in the Ubuntu repositories, making it easier for developers to install with a single, simple APT command.
Update
A couple more:
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It's FOSS ☛ Good News for AI Developers! Soon, Installing CUDA on Ubuntu Will Take Just a Single Command
Canonical is steadily evolving Ubuntu into a modern, more secure, and developer-friendly operating system. Recent moves, like implementing the Rust-based sudo-rs to replace sudo and exploring Rust alternatives for core utilities, clearly show a focus on safety and performance.
With these changes, Ubuntu is positioning itself as a platform that can handle all kinds of workloads, from general use and software development to AI applications. Its strong server presence further strengthens its multipurpose nature.
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ZDNet ☛ You can get Nvidia's CUDA on three popular enterprise Linux distros now - why it matters
AI developers use popular frameworks like TensorFlow, PyTorch, and JAX to work on their projects. All these frameworks, in turn, rely on Nvidia's CUDA AI toolkit and libraries for high-performance AI training and inference on Nvidia GPUs.
To help developers get up to speed, Nvidia has partnered with leading enterprise Linux distributors SUSE, Canonical, and CIQ to natively package the toolkit into their enterprise Linux distros -- SUSE Enterprise Linux, Ubuntu, and Rocky Linux.
Don't know CUDA? It's a parallel computing platform and programming model that enables software developers to use Nvidia GPUs for general-purpose processing instead of graphics rendering. By leveraging thousands of GPU cores, CUDA enables massive parallelism, speeding up complex computations in fields like AI, scientific computing, machine learning, and data analysis. CUDA also provides application programming interfaces (APIs) and libraries for C, C++, Python, and other languages.