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 ...

Not every developer who might like to learn CUDA has access to an NVIDIA GPU, so by expanding the hardware that CUDA can target to include x86, you'll be able to get your feet wet with CUDA on ...

When used correctly, atomic operations can help implement a wide range of generic data structures and algorithms in the massively threaded GPU programming environment.

In addition, Nvidia announced that more than 20 universities around the world have adopted CUDA for multicore and parallel processing programming, with several more also exploring CUDA for inclusion ...

Nvidia has unveiled a new compiler source code to add new languages to its parallel programming and boost the adoption of GPUs.