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 ...

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 ...

Most notably, the chipmaker announced a compiler source code enabling software developers to add new languages and architecture support to Nvidia’s CUDA parallel programming model. The new ...

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 ...

“Our course focuses heavily on helping our students understand the general principles of parallelism and NVIDIA has been instrumental in helping us build and integrate this course into our curriculum, ...

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 ...

Getting started with parallel programming is easier than ever. In fact, now you can develop right on your Macbook Pro using its built-in Nvidia GeForce GPU. Over at QuantStart, Valerio Restocchi has ...

In this Programming Throwdown podcast, Mark Harris from Nvidia describes CUDA programming for GPUs. “CUDA is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic ...

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 ...

This week is the eighth annual International Workshop on OpenCL, SYCL, Vulkan, and SPIR-V, and the event is available online for the very first time in its history thanks to the coronavirus pandemic.

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 ...