Measurement of real time information using GPU

Parallel programming is about performance, for otherwise we’d write a sequential program. A problem is where to find truly parallel hardware that can be dedicated to the task, One answer is graphical processing units (GPUs), which can have hundreds of cores and are found in millions of desktop and laptop computers. GPU computing with Open CL is a new approach to computing where hundreds of on-chip processor cores simultaneously communicate and cooperate to solve complex computing problems, transforming the GPU into a massively parallel processor. The NVIDIA C-compiler for the GPU provides a complete development environment that gives developers the tools they need to solve new problems in computation-intensive applications such as product design, data analysis, technical computing, and game physics. In this paper we are going to analyze the speed of GPU in comparison to CPU. 1