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 ...

NVIDIA’s rise from graphics card specialist to the most closely watched company in artificial intelligence rests on a ...

Graphics processing units (GPUs) were originally designed to perform the highly parallel computations required for graphics rendering. But over the last couple of years, they’ve proven to be powerful ...

TL;DR: NVIDIA CUDA 13.1 introduces the largest update in two decades, featuring CUDA Tile programming to simplify AI development on Blackwell GPUs. By abstracting tensor core operations and automating ...

NVIDIA's CUDA (Compute Unified Device Architecture) makes programming and using thousands of simultaneous threads straightforward. CUDA turns workstations, clusters—and even laptops—into massively ...

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 ...

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.

NVIDIA has announced that it is porting its popular GPU programming architecture to x86. Once the port is complete, developers will be able to choose from two different architectures—OpenCL and ...

Nvidia Corporation's revenue and net income skyrocketed in fiscal year 2024, driven by their transition from a video game company to an AI company. CUDA, Nvidia's programming interface, gives them a ...