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Tensor Processing Unit (TPU) is an AI accelerator application-specific integrated circuit (ASIC) developed by Google for neural network machine learning, ...
General-purpose computing on graphics processing units (GPGPU, or less often GPGP) is the use of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU).
Components of a GPU. A graphics processing unit (GPU) is a specialized electronic circuit initially designed for digital image processing and to accelerate computer graphics, being present either as a discrete video card or embedded on motherboards, mobile phones, personal computers, workstations, and game consoles.
The CPU first detects OpenCL devices (GPU in this case) and then invokes a just-in-time compiler to translate the OpenCL source code into target binary. CPU then sends data to GPU to perform computations. When the GPU is processing data, CPU is free to process its own tasks.
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.
The term is frequently used to refer to the central processing unit (CPU), the main processor in a system. [7] However, it can also refer to other coprocessors , such as a graphics processing unit (GPU).
Graphics cards are sometimes called discrete or dedicated graphics cards to emphasize their distinction to an integrated graphics processor on the motherboard or the central processing unit (CPU). A graphics processing unit (GPU) that performs the necessary computations is the main component in a graphics card, but the acronym "GPU" is ...
Microsoft HoloLens, which includes an accelerator referred to as a holographic processing unit (complementary to its CPU and GPU), aimed at interpreting camera inputs, to accelerate environment tracking and vision for augmented reality applications. [6] Eyeriss, a design from MIT intended for running convolutional neural networks. [7]