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The CUDA toolkit is now packaged with Rocky Linux, SUSE Linux, and Ubuntu.
This will make life easier for AI developers on these Linux distros.
It will also speed up AI development and deployments on Nvidia hardware.
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.
Nvidia's move from graphics to high-end development has been years in the making. Now, with CUDA, Nvidia dominates AI software almost as much as it does AI hardware.
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