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  2. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    In computing, CUDA 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.

  3. Hardware compatibility list - Wikipedia

    en.wikipedia.org/wiki/Hardware_compatibility_list

    A hardware compatibility list (HCL) is a list of computer hardware (typically including many types of peripheral devices) that is compatible with a particular operating system or device management software. The list contains both whole computer systems and specific hardware elements including motherboards, sound cards, and video cards. [1]

  4. Nvidia CUDA Compiler - Wikipedia

    en.wikipedia.org/wiki/Nvidia_CUDA_Compiler

    CUDA code runs on both the central processing unit (CPU) and graphics processing unit (GPU). NVCC separates these two parts and sends host code (the part of code which will be run on the CPU) to a C compiler like GNU Compiler Collection (GCC) or Intel C++ Compiler (ICC) or Microsoft Visual C++ Compiler, and sends the device code (the part which will run on the GPU) to the GPU.

  5. Maxwell (microarchitecture) - Wikipedia

    en.wikipedia.org/wiki/Maxwell_(microarchitecture)

    Photo of James Clerk Maxwell, eponym of architecture. Maxwell is the codename for a GPU microarchitecture developed by Nvidia as the successor to the Kepler microarchitecture. . The Maxwell architecture was introduced in later models of the GeForce 700 series and is also used in the GeForce 800M series, GeForce 900 series, and Quadro Mxxx series, as well as some Jetson produ

  6. PyTorch Lightning - Wikipedia

    en.wikipedia.org/wiki/PyTorch_Lightning

    PyTorch Lightning is an open-source Python library that provides a high-level interface for PyTorch, a popular deep learning framework. [1] It is a lightweight and high-performance framework that organizes PyTorch code to decouple research from engineering, thus making deep learning experiments easier to read and reproduce.

  7. Hopper (microarchitecture) - Wikipedia

    en.wikipedia.org/wiki/Hopper_(microarchitecture)

    Hopper allows CUDA compute kernels to utilize automatic inline compression, including in individual memory allocation, which allows accessing memory at higher bandwidth. This feature does not increase the amount of memory available to the application, because the data (and thus its compressibility ) may be changed at any time.

  8. ROCm - Wikipedia

    en.wikipedia.org/wiki/ROCm

    ROCm is free, libre and open-source software (except the GPU firmware blobs [4]), and it is distributed under various licenses. ROCm initially stood for Radeon Open Compute platfor m ; however, due to Open Compute being a registered trademark, ROCm is no longer an acronym — it is simply AMD's open-source stack designed for GPU compute.

  9. Nvidia PureVideo - Wikipedia

    en.wikipedia.org/wiki/Nvidia_PureVideo

    The PureVideo SIP core needs to be supported by the device driver, which provides one or more interfaces such as NVDEC, VDPAU, VAAPI or DXVA.One of these interfaces is then used by end-user software, for example VLC media player or GStreamer, to access the PureVideo hardware and make use of it.