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 ...

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 ...

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 ...

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 Nvidia’s decade and a half push to make GPU acceleration core to all kinds of high performance computing, a key component has been the CUDA parallel computing platform that made it easier for ...

CUDA is a parallel computing programming model for Nvidia GPUs. With the proliferation over the past decade of GPU usage for speeding up applications across HPC, AI and beyond, the ready availability ...

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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 ...