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In computing, CUDA is a proprietary [2] 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.
Installation (or setup) of a computer program (including device drivers and plugins), is the act of making the program ready for execution. Installation refers to the particular configuration of software or hardware with a view to making it usable with the computer. A soft or digital copy of the piece of software (program) is needed to install it.
As of July 2017, the Graphics Core Next instruction set has seen five iterations. The differences between the first four generations are rather minimal, but the fifth-generation GCN architecture features heavily modified stream processors to improve performance and support the simultaneous processing of two lower-precision numbers in place of a single higher-precision number.
An AI accelerator, deep learning processor or neural processing unit (NPU) is a class of specialized hardware accelerator [1] or computer system [2] [3] designed to accelerate artificial intelligence (AI) and machine learning applications, including artificial neural networks and computer vision.
waifu2x is an image scaling and noise reduction program for anime-style art and other types of photos. [1]waifu2x was inspired by Super-Resolution Convolutional Neural Network (SRCNN).
PlaidML is a portable tensor compiler.Tensor compilers bridge the gap between the universal mathematical descriptions of deep learning operations, such as convolution, and the platform and chip-specific code needed to perform those operations with good performance.