Have you wanted to get into GPU programming with CUDA but found the usual textbooks and guides a bit too intense? Well, help is at hand in the form of a series of increasingly difficult programming ...

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.

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 ...

Graphics processing units (GPUs) are traditionally designed to handle graphics computational tasks, such as image and video processing and rendering, 2D and 3D graphics, vectoring, and more.

In this video from PyData NYC 2012, Andreas Klöckner from New York University presents a brief introduction to GPU programming with Python, including run-time code generation and use of high-level ...

When I wrote about password guessing using GPUs last week, I mentioned that password guessing is an embarrassingly parallel problem, right up there with 3-D rendering, face recognition, Monte Carlo ...

Nvidia has made improvements to its underlying software tools to make it easier to write programs for faster execution across CPUs and graphics processors. The company on Thursday announced CUDA 6, ...

In a move that shouldn't be that surprising, NVIDIA has announced that its popular CUDA platform is being ported to x86. The obvious angle here is that this will give NVIDIA a weapon against OpenCL ...

NVIDIA has revealed the GB300 Blackwell Ultra, a massive step forward in its AI accelerator lineup. This chip builds on the already powerful GB200 but increases compute resources, memory size, and ...