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  2. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    TensorFlow is available on 64-bit Linux, macOS, Windows, and mobile computing platforms including Android and iOS. [citation needed] Its flexible architecture allows for easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices.

  3. TensorFloat-32 - Wikipedia

    en.wikipedia.org/wiki/TensorFloat-32

    The binary format is: 1 sign bit; 8 exponent bits; 10 fraction bits (also called mantissa, or precision bits) The total 19 bits fits within a double word (32 bits), and while it lacks precision compared with a normal 32 bit IEEE 754 floating point number, provides much faster computation, up to 8 times on a A100 (compared to a V100 using FP32).

  4. Half-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Half-precision_floating...

    The advantage over 8-bit or 16-bit integers is that the increased dynamic range allows for more detail to be preserved in highlights and shadows for images, and avoids gamma correction. The advantage over 32-bit single-precision floating point is that it requires half the storage and bandwidth (at the expense of precision and range).

  5. Windows 7 - Wikipedia

    en.wikipedia.org/wiki/Windows_7

    In February 2020, Microsoft released an update via Windows Update to fix a black wallpaper issue caused by the January 2020 update for Windows 7. [170] [171] In June 2020, Microsoft released an update via Windows Update to roll out the new Chromium-based Microsoft Edge to Windows 7 and 8.1 machines that are not connected to Active Directory.

  6. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo, a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and inference performance across major cloud platforms.

  7. 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 ...

  8. 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.

  9. Windows Anytime Upgrade - Wikipedia

    en.wikipedia.org/wiki/Windows_Anytime_Upgrade

    The Windows Anytime Upgrade in Windows 7. Anytime Upgrade in Windows 7 no longer performs a full reinstallation of Windows. Components for the upgraded editions are instead pre-installed directly in the operating system; a notable result of this change is that the speed of the upgrade process has been significantly increased.