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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. Graphics processing unit - Wikipedia

    en.wikipedia.org/wiki/Graphics_processing_unit

    The Kepler line of graphics cards by Nvidia were released in 2012 and were used in the Nvidia's 600 and 700 series cards. A feature in this GPU microarchitecture included GPU boost, a technology that adjusts the clock-speed of a video card to increase or decrease it according to its power draw. [42]

  4. Single instruction, multiple threads - Wikipedia

    en.wikipedia.org/wiki/Single_instruction...

    The SIMT execution model has been implemented on several GPUs and is relevant for general-purpose computing on graphics processing units (GPGPU), e.g. some supercomputers combine CPUs with GPUs. The processors, say a number p of them, seem to execute many more than p tasks.

  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

    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. [5] In addition to drivers and runtime kernels, the CUDA platform includes compilers, libraries and developer tools to help programmers accelerate their applications.

  7. GPU virtualization - Wikipedia

    en.wikipedia.org/wiki/GPU_virtualization

    GPU virtualization refers to technologies that allow the use of a GPU to accelerate graphics or GPGPU applications running on a virtual machine. GPU virtualization is used in various applications such as desktop virtualization , [ 1 ] cloud gaming [ 2 ] and computational science (e.g. hydrodynamics simulations).

  8. 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

  9. ROCm - Wikipedia

    en.wikipedia.org/wiki/ROCm

    ROCm [3] is an Advanced Micro Devices (AMD) software stack for graphics processing unit (GPU) programming. ROCm spans several domains: general-purpose computing on graphics processing units (GPGPU), high performance computing (HPC), heterogeneous computing.

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