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  2. General-purpose computing on graphics processing units

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

    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).

  3. GPU cluster - Wikipedia

    en.wikipedia.org/wiki/GPU_cluster

    A GPU cluster is a computer cluster in which each node is equipped with a graphics processing unit (GPU). By harnessing the computational power of modern GPUs via general-purpose computing on graphics processing units (GPGPU), very fast calculations can be performed with a GPU cluster. Titan, the first supercomputer to use GPUs

  4. Graphics processing unit - Wikipedia

    en.wikipedia.org/wiki/Graphics_processing_unit

    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.

  5. Graphics card - Wikipedia

    en.wikipedia.org/wiki/Graphics_card

    A modern consumer graphics card: A Radeon RX 6900 XT from AMD. A graphics card (also called a video card, display card, graphics accelerator, graphics adapter, VGA card/VGA, video adapter, display adapter, or colloquially GPU) is a computer expansion card that generates a feed of graphics output to a display device such as a monitor.

  6. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    When it was first introduced, the name was an acronym for Compute Unified Device Architecture, [4] but Nvidia later dropped the common use of the acronym and now rarely expands it. [5] 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]

  7. rCUDA - Wikipedia

    en.wikipedia.org/wiki/RCUDA

    rCUDA, which stands for Remote CUDA, is a type of middleware software framework for remote GPU virtualization. Fully compatible with the CUDA application programming interface (), it allows the allocation of one or more CUDA-enabled GPUs to a single application.

  8. 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.

  9. Graphics pipeline - Wikipedia

    en.wikipedia.org/wiki/Graphics_pipeline

    With increasing demands on the GPU, restrictions were gradually removed to create more flexibility. Modern graphics cards use a freely programmable, shader-controlled pipeline, which allows direct access to individual processing steps. To relieve the main processor, additional processing steps have been moved to the pipeline and the GPU.