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CUBA_ parallel _programing_ for_ GPUs

CUDA, heard about this before? – Parallel programming for GPUs

CUBA_ parallel _programing_ for_ GPUsWith programming world ever in its peak advances, there comes another marvellous invention named CUDA – a parallel computing platform and programming model which is developed by Nvidia generally for computing on their own GPUs (graphics processing units). Speaking in simple language, CUDA is a programming platform which enables developers to speed up their compute-intensive applications by basically connecting the power of their GPUs for parallelizable activity part of the computation to happen.

Graphics cards are hilariously and hypothetically compared to the days old invention of computer era, that is, if you consider that 1981 IBM Monochrome Display Adapter a type of graphics card then by 1988, you got 16-bit 2D VGA Wonder card from ATI (the company in the long run acquired by AMD) and by 1996, you also got to buy a 3D graphics accelerator from 3dfx Interactive. By the name, you could now search deep into your memories for its use? You could run the first-person shooter Quake at full speed.

Way back in 1996, Nvidia started their trial to compete in the 3D accelerator market amongst the weaker products, but later learned as it went through and in 1999 introduced the successful GeForce 256, the first graphics card is popularly known as GPU to the world. At this time, the principal reason behind having a GPU was basically for the gaming process and it wasn’t until later that people used GPUs for math, science, engineering and various other fields.

Now coming back to CUBA; In spite of various other proposed APIs ( Application programming interface ) for GPUs, popularly known names being OpenCL, and they also consist of competitive GPUs from other companies especially like AM with the combination of CUDA and Nvidia GPUs dominating several application areas which also includes deep learning which acts as a foundation for some of the fastest computers in the world.

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