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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, using Google's own TensorFlow software. [2] Google began using TPUs internally in 2015, and in 2018 made them available for third-party use, both as part of its cloud infrastructure and by ...
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).
The idea is having specialized processors offload time-consuming tasks from a computer's CPU, much like how a GPU performs graphics operations in the main CPU's place. The term was coined by Ageia to describe its PhysX chip. Several other technologies in the CPU-GPU spectrum have some features in common with it, although Ageia's product was the ...
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.
Hardware acceleration is the use of computer hardware designed to perform specific functions more efficiently when compared to software running on a general-purpose central processing unit (CPU). Any transformation of data that can be calculated in software running on a generic CPU can also be calculated in custom-made hardware, or in some mix ...
In computing and computer science, a processor or processing unit is an electrical component (digital circuit) that performs operations on an external data source, usually memory or some other data stream. [1]
In other words, the CPU(s) run (possibly in parallel), then when that subtask completes, the next subtask is handed to the GPU(s). When they finish the next subtask is handed to the TPU(s). [2] Adding software pipelining allows the second subtask to run using partial results from the first subtask, which improves resource utilization. [2]
1.6×10 9: PowerVR MBX Lite 3D GPU on iPhone 1, 2007; 8×10 9: PowerVR SGX535 GPU on iPad 1, 2010; 136×10 9: PowerVR GXA6450 GPU on iPhone 6 and iPhone SE, 2014; 148×10 9: Intel Core i7-980X Extreme Edition commercial computing 2010 [4]