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 ...

This course focuses on developing and optimizing applications software on massively parallel graphics processing units (GPUs). Such processing units routinely come with hundreds to thousands of cores ...

Back in 2000, Ian Buck and a small computer graphics team at Stanford University were watching the steady evolution of computer graphics processors for gaming and thinking about how such devices could ...

The Seeker quantum processor from Quantum Circuits now supports Nvidia's CUDA-Q, enabling developers to combine quantum ...

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 ...

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 ...

WEST LAFAYETTE, Ind. - Purdue University announced that it has been named a CUDA® Research Center by NVIDIA, a global leader in visual computing. CUDA Research Centers are institutions that embrace ...