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In computing, CUDA is a proprietary [1] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs.
CUDA code runs on both the central processing unit (CPU) and graphics processing unit (GPU). NVCC separates these two parts and sends host code (the part of code which will be run on the CPU) to a C compiler like GNU Compiler Collection (GCC) or Intel C++ Compiler (ICC) or Microsoft Visual C++ Compiler, and sends the device code (the part which will run on the GPU) to the GPU.
The Nvidia CUDA Compiler (NVCC) translates code written in CUDA, a C++-like language, into PTX instructions (an assembly language represented as American Standard Code for Information Interchange text), and the graphics driver contains a compiler which translates PTX instructions into executable binary code, [2] which can run on the processing ...
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In computing, the exit status (also exit code or exit value) of a terminated process is an integer number that is made available to its parent process (or caller). In DOS , this may be referred to as an errorlevel .
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VDPAU was originally designed by Nvidia for their PureVideo SIP block present on their GeForce 8 series and later GPUs. [8]On March 9, 2015, Nvidia released VDPAU version 1.0 which supports High Efficiency Video Coding (HEVC) decoding for the Main, Main 4:4:4, Main Still Picture, Main 10, and Main 12 profiles.