03-03-2012, 04:28 PM
GPU Implementation of Extended Gaussian Mixture Model for Background Subtraction
GMM on GPU.doc (Size: 290.5 KB / Downloads: 35)
What is GPU Computing?
GPU computing or GPGPU is the use of a GPU (graphics processing unit) to do general purpose scientific and engineering computing.
The model for GPU computing is to use a CPU and GPU together in a heterogeneous co-processing computing model. The sequential part of the application runs on the CPU and the computationally-intensive part is accelerated by the GPU. From the user’s perspective, the application just runs faster because it is using the high-performance of the GPU to boost performance.
SUPERCOMPUTER
A supercomputer is a computer that is at the frontline of current processing capacity, particularly speed of calculation. Today, supercomputers are typically one-of-a-kind custom designs produced by "traditional" companies such as Cray, IBM and Hewlett-Packard, who had purchased many of the 1980s companies to gain their experience. As of July 2009, the Cray Jaguar is the fastest supercomputer in the world.
The term supercomputer itself is rather fluid, and today's supercomputer tends to become tomorrow's ordinary computer.
Supercomputers are used for highly calculation-intensive tasks such as problems involving quantum physics, weather forecasting, climate research, molecular modeling (computing the structures and properties of chemical compounds, biological macromolecules, polymers, and crystals), physical simulations (such as simulation of airplanes in wind tunnels, simulation of the detonation of nuclear weapons, and research into nuclear fusion).
GPU
A graphics processing unit or GPU (also occasionally called visual processing unit or VPU) is a specialized processor that offloads 3D or 2D graphics rendering from the microprocessor. It is used in embedded systems, mobile phones, personal computers, workstations, and game consoles. Modern GPUs are very efficient at manipulating computer graphics, and their highly parallel structure makes them more effective than general-purpose CPUs for a range of complex algorithms