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By now I had hear a lot about CUDA. It is a revolutionary API developed by nvidia to benefit from the computational power of its GPUs . I am interested in the thing by downloading the latest drivers, CUDA toolkit including compiler and NVCC CUDA SDK. While searching I managed to find some information which I unfortunately was not enough to compile it. The version which I download Cuda Meme v2.6 caused error while compilation.
To compile a CUDA program, you need to either buy the GPU which available at NVIDIA which is necessary to build emulation/ Indeed, the SDK provided by NVIDIA is free but you need the card that goes with it to compare the computing power compared to your CPU/ In the examples provided by NVIDIA, there are examples that ou can already try to compile. First try them out.
The Cuda technology by Nvidia is an particular environment that allows C language to access the processing power of GPUs from nVidia. You can do lot with this. It offers you to work on complex calculation and other complex operations. It is possible to compile a program in that if you have a Nvidia GPU support with appropriate updates on your system.
I am using TMPGenc. It is a MPEG encoder which is able to take charge on SpursEngine. To recall, the SpursEngine is a chip based on the architecture of the Cell, but with only four PES and without the PowerPC processor. TMPGenc was already CUDA support for some of the filters and for decoding the video to be encoded, it is now also compatible SpursEngine.
NVIDIA CUDA need some recommend settings before using the same. This framework consists of three components to install first. The first is the driver for your NVIDIA. The second is that you will need to download NVIDIA CUDA toolkit from the official site of Nvidia. Then the last thing you need to work in this is NVIDIA CUDA SDK which available on the same official site.
Just get the toolkit from the official sources. The toolkit contains NVIDIA C compiler which is called as NVCC that can compile C code with the NVIDIA CUDA framework. The NVIDIA SDK is a development kit with lots of programming examples. The examples are in the file NVIDIA CUDA SDK projects and there are also a mask (template) to create own project. Thus, it is important to develop a first time its own code within the folder structure of NVIDIA CUDA SDK.
Do not be frightened by seeing the code for the first time, for indeed there are many lines of code to write for a task so basic as calculating the square root of a value. The GPU is physically separated from the CPU and any load and any memory allocated for the CPU is not accessible to the GPU. The function that performs the calculations on the GPU.