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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. General-purpose computing on graphics processing units

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

    Cards from such vendors differ on implementing data-format support, such as integer and floating-point formats (32-bit and 64-bit). Microsoft introduced a Shader Model standard, to help rank the various features of graphic cards into a simple Shader Model version number (1.0, 2.0, 3.0, etc.).

  4. 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).

  5. 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.

  6. Keras - Wikipedia

    en.wikipedia.org/wiki/Keras

    Up until version 2.3, Keras supported multiple backends, including TensorFlow, Microsoft Cognitive Toolkit, Theano, and PlaidML. [7] [8] [9] As of version 2.4, only TensorFlow was supported. Starting with version 3.0 (as well as its preview version, Keras Core), however, Keras has become multi-backend again, supporting TensorFlow, JAX, and ...

  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. 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]

  9. Fn key - Wikipedia

    en.wikipedia.org/wiki/Fn_key

    The majority of portable computer manufacturers today (including HP, Dell, and Samsung) currently place the Fn key between the left Control key and the left Windows key, making it the second key from the left on the bottom row of the keyboard. This usually means that the Control key is reduced in size, but allows it to remain in the lowest-left ...

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