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Will The GPU Replace The CPU Or Will It Be The Other Way Around?

Here we discuss about the coordinated and synchronized use of CPU and GPU to improve efficiency of applications even further than using either device independently. This is made possible with the help NVIDIA’s parallel computing architecture, CUDA.

Computing is evolving from “central processing” on the CPU to “co-processing” on the CPU and GPU. To enable this new computing paradigm, NVIDIA invented the CUDA parallel computing architecture that is now shipping in GeForce, ION, Quadro, and Tesla GPUs, representing a significant installed base for application developers.

CUDA parallel computing architecture which is now being shipped with GeForce, ION,Quadro and Tesla GPUs ,make the new computing paradigm possible. The CUDA architecture’s applications can now be found in Medical Simulations like in analysis of CT and MRI scan images, Fluid Dynamics Simulation, Seismic Analysis and much more. The buzz is that in the near future itself almost every application which uses video rendering will be accelerated by CUDA.

With the recent launches of Microsoft Windows 7 and Apple Snow Leopard, GPU computing has got even more better with the GPU being evolved GPGPU which stands for General Purpose Graphical Processing Unit. It’s being said that BOINC distributed computing now uses CUDA technology for it’s better efficiency.

OpenCL (Open Computing Language) and Microsoft’s DirectCompute, a new GPU Computing API are just two tools which make the developers possible to harness the power of GPU computing. A Fortran language solution is also in development which can use the power GPU computing.

Download CUDA SDK, Developer’s Drivers, Code Samples and Toolkits for Windows, Linux and MacOS.

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Author is a novice blogger from Kerala. He likes to blog about the techie-st things happening around in the web. He is also an Open Source enthusiast and a Linux User.