The buzz has been loud at times. Almost sounds to good to be true. Use your video card for HPC and get a 10, or maybe even 50 times, speed up of your application. Those kind of comments get my attention. Initially there were some skeptics, but the results keep coming. And, the results were not from some academic lab with some esoteric application.
GpuCV is an open-source GPU-accelerated image processing and Computer Vision library. It offers an Intel's OpenCV-like programming interface for easily porting existing OpenCV applications, while taking advantage of the high level of parallelism and computing power available from recent graphics processing units (GPUs). It is distributed as free software under the CeCILL-B license.
With Intel bracing itself for the discrete GPU market with its upcoming Larrabee chip, Nvidia and AMD are expected to make an earnest attempt at luring millions of users of integrated graphics with their low-end discrete graphics solutions – quid pro quo.
“The GPU is a powerful, programmable platform that is perfect for computing applications such as seismic processing for oil and gas exploration, computing in bioscience, and financial modeling,” says Andy Keane, general manager of the GPU computing business at NVIDIA, a pioneer in using GPUs for HPC. “The GPU will change the way engineers and researchers approach these problems.”
Modern graphics processing units (GPUs) contain hundreds of arithmetic units and can be harnessed to provide tremendous acceleration for many numerically intensive scientific applications. The key to effective utilization of GPUs for scientific computing
Open GPU Documentation: This page contains register level documentation on AMD graphics processors for chip initialization, displays, and overlays. Documents for mobile chips are a superset of the desktop chip documentation; they contain all the desktop chip information as well as any relevant mobile additions.
OpenVIDIA : GPU accelerated Computer Vision Library The OpenVIDIA project implements computer vision algorithms on computer graphics hardware, using OpenGL and Cg. The project provides useful example programs which run real time computer vision algorit