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  2. General-purpose computing on graphics processing units

    en.wikipedia.org/wiki/General-purpose_computing...

    Alea GPU also provides a simplified GPU programming model based on GPU parallel-for and parallel aggregate using delegates and automatic memory management. [ 22 ] MATLAB supports GPGPU acceleration using the Parallel Computing Toolbox and MATLAB Distributed Computing Server , [ 23 ] and third-party packages like Jacket .

  3. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    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]

  4. Direct Rendering Manager - Wikipedia

    en.wikipedia.org/wiki/Direct_Rendering_Manager

    The Direct Rendering Manager (DRM) is a subsystem of the Linux kernel responsible for interfacing with GPUs of modern video cards.DRM exposes an API that user-space programs can use to send commands and data to the GPU and perform operations such as configuring the mode setting of the display.

  5. Nvidia Optimus - Wikipedia

    en.wikipedia.org/wiki/Nvidia_Optimus

    Nvidia Optimus is a computer GPU switching technology created by Nvidia which, depending on the resource load generated by client software applications, will seamlessly switch between two graphics adapters within a computer system in order to provide either maximum performance or minimum power draw from the system's graphics rendering hardware.

  6. Tensor Processing Unit - Wikipedia

    en.wikipedia.org/wiki/Tensor_Processing_Unit

    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 ...

  7. OpenCL - Wikipedia

    en.wikipedia.org/wiki/OpenCL

    OpenCL (Open Computing Language) is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors or hardware accelerators.

  8. WebGPU - Wikipedia

    en.wikipedia.org/wiki/WebGPU

    WebGPU enables 3D graphics within an HTML canvas.It also has robust support for general-purpose GPU computations. [3]WebGPU uses its own shading language called WGSL that was designed to be trivially translatable to SPIR-V, until complaints caused redirection into a more traditional design, similar to other shading languages.

  9. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    In computing, CUDA (Compute Unified Device Architecture) 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.

  1. Related searches tensorflow 2 not using gpu command line or online version of linux server

    google tpu tensorflowgoogle tensor flow
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