Parallel Computing Platform – A Complete Approach to Tooling
Parallel computing is a form of computation in which many operations are carried out side by side. This line answers the query about what is parallel processing. Visual Studio 2010, the .NET Framework 4 and Visual C++ 2010 all contain new support for writing, debugging and turning parallel applications. There are several tools with which one can try out parallel programing. CUDA is a parallel computing platform and programming model invented by NVIDIA. It unveiled CUDA in 2006, announcing it as the world’s first solution for general computing on GPUs. It basically dramatic increase in computing performance by churning out the power of the graphics processing unit or GPU. For people looking for the answer of the question what is gpu, it can be said that it is a client that allows users to share CPU resources. GPU allows the creation of computer alliances. NVIDIA provides a complete toolkit for programming on the CUDA architecture, supporting standard computing languages such as C, C++ and Fortran. All these information leads to the answer of the question what is CUDA.
The company cites some example on its site of CUDA’s user base today. In the consumer market, nearly every major consumer video application has been or will soon be, accelerated by CUDA, including products from Adobe, Sony, Elemental Technologies, MotionDSP and LoiLo. In scientific research, CUDA accelerates AMBER, a molecular dynamics simulation program used by researchers to speed up new drug discovery. Generally, developers at scientific companies look to GPU computing for speeding up applications for scientific and engineering computing. With this approach, GPU accelerated applications run the sequential part of their workload on the CPU while accelerating parallel processing on the GPU. Recently it announced of a dressed up version of its CUDA parallel computing platform. It is targeted for engineers, biologist, chemists, physicists, geophysicists and other researchers on fast track computations using GPUs.
The new version features an low level virtual machine based CUDA compiler. It says the new enhancements are ways to advance simulations and computational work for the users. The latest CUDA version offers a trifecta to make parallel programming with GPUs easier and faster. You can stay up to date about the world of CUDA, GPU Computing and other CUDA news from our newsletter. The newsletter also tells the readers about mobile graphics technology and basics of computer graphics. The interested people would gain expert design assistance with the parallel computing platform based solution. The interested people can also follow latest CUDA news on social networking sites.
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