An end-to-end data science ecosystem, open source RAPIDS gives you Python dataframes, graphs, and machine learning on Nvidia GPU hardware Building machine learning models is a repetitive process.

Nvidia has been more than a hardware company for a long time. As its GPUs are broadly used to run machine learning workloads, machine learning has become a key priority for Nvidia. In its GTC event ...

Nvidia has released a new mathematical Python library specialized for Cuda-X. It offers direct, Python-like access to the mathematical core operations of Cuda-X without having to use additional C/C++ ...

CUDA enables faster AI processing by allowing simultaneous calculations, giving Nvidia a market lead. Nvidia's CUDA platform is the foundation of many GPU-accelerated applications, attracting ...

Nvidia has placed Warp under an Apache 2 license. The Python framework is used for performance-hungry physical simulations, data generation and spatial computing. It compiles Python functions just in ...

NVIDIA has announced partnerships with several operating system providers and package managers to redistribute its CUDA parallel computing platform, aiming to simplify software deployment for ...

In this video from the ECSS Symposium, Abe Stern from NVIDIA presents: CUDA-Python and RAPIDS for blazing fast scientific computing. We will introduce Numba and RAPIDS for GPU programming in Python.