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Alea GPU, [19] created by QuantAlea, [20] introduces native GPU computing capabilities for the Microsoft .NET languages F# [21] and C#. Alea GPU also provides a simplified GPU programming model based on GPU parallel-for and parallel aggregate using delegates and automatic memory management. [22]
CUDA is a software layer that gives direct access to the GPU's virtual instruction set and parallel computational elements for the execution of compute kernels. [6] In addition to drivers and runtime kernels, the CUDA platform includes compilers, libraries and developer tools to help programmers accelerate their applications.
TensorFlow serves as a core platform and library for machine learning. TensorFlow's APIs use Keras to allow users to make their own machine-learning models. [33] [43] In addition to building and training their model, TensorFlow can also help load the data to train the model, and deploy it using TensorFlow Serving. [44]
TechPowerUp GPU-Z (or just GPU-Z) is a lightweight utility designed to provide information about video cards and GPUs. [2] The program displays the specifications of Graphics Processing Unit (often shortened to GPU) and its memory; also displays temperature, core frequency, memory frequency, GPU load and fan speeds.
In computer graphics, the render output unit (ROP) or raster operations pipeline is a hardware component in modern graphics processing units (GPUs) and one of the final steps in the rendering process of modern graphics cards.
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 ...
"Tensor" is a reference to Google's TensorFlow and Tensor Processing Unit technologies, and the chip is developed by the Google Silicon team housed within the company's hardware division, led by vice president and general manager Phil Carmack alongside senior director Monika Gupta, [15] in conjunction with the Google Research division.
The following code-block defines a neural network with linear layers using the nn module. import torch from torch import nn # Import the nn sub-module from PyTorch class NeuralNetwork ( nn . Module ): # Neural networks are defined as classes def __init__ ( self ): # Layers and variables are defined in the __init__ method super () . __init__ ...