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 ...

Readers already comfortable with parallel programming will find clear explanations of the Tesla GPU architecture and the performance implications of its hardware features, as well as a solid ...

NVIDIA today announced NVIDIA® CUDA® 6, the latest version of the world's most pervasive parallel computing platform and programming model.

In high performance computing, machine learning, and a growing set of other application areas, accelerated, heterogeneous systems are becoming the norm. With that state come several parallel ...

One size does not fit all, and it never will. Parallel programming looks to level the playing field by leveraging multicore hardware.

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

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 ...

SUPERCOMPUTING 2007—RENO, NEVADA—NOVEMBER 14, 2007—As the computing industry rapidly moves to multi-core and parallel processing architectures, tomorrow’s software engineer must be educated on the ...

The CUDA 6 platform makes parallel programming easier than ever, enabling software developers to dramatically decrease the time and effort required to accelerate their scientific, engineering ...