NVIDIA’s CUDA is a general purpose parallel computing platform and programming model that accelerates deep learning and other compute-intensive apps by taking advantage of the parallel processing ...

Programmers have been interested in leveraging the highly parallel processing power of video cards to speed up applications that are not graphic in nature for a long time. Here, I explain how to do ...

Nvidia has updated its CUDA software platform, adding a programming model designed to simplify GPU management. Added in what the chip giant claims is its “biggest evolution” since its debut back in ...

Every few years or so, a development in computing results in a sea change and a need for specialized workers to take advantage of the new technology. Whether that’s COBOL in the 60s and 70s, HTML in ...

A hands-on introduction to parallel programming and optimizations for 1000+ core GPU processors, their architecture, the CUDA programming model, and performance analysis. Students implement various ...

This isn’t a review, but given the popularity of my last CUDA book review, I thought I’d mention that Addison-Wesley has published a new book called CUDA by Example: An Introduction to General-Purpose ...

Support for unified memory across CPUs and GPUs in accelerated computing systems is the final piece of a programming puzzle that we have been assembling for about ten years now. Unified memory has a ...

Over at the Nvidia blog, Mark Harris has posted a simple introduction to CUDA, the popular parallel computing platform and programming model from NVIDIA. I wrote a previous “Easy Introduction” to CUDA ...

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.

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 ...