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  2. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    For example, TensorFlow Recommenders and TensorFlow Graphics are libraries for their respective functionalities in recommendation systems and graphics, TensorFlow Federated provides a framework for decentralized data, and TensorFlow Cloud allows users to directly interact with Google Cloud to integrate their local code to Google Cloud. [68]

  3. Comparison of deep learning software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_deep...

    Can use Theano, Tensorflow or PlaidML as backends Yes No Yes Yes [20] Yes Yes No [21] Yes [22] Yes MATLAB + Deep Learning Toolbox (formally Neural Network Toolbox) MathWorks: 1992 Proprietary: No Linux, macOS, Windows: C, C++, Java, MATLAB: MATLAB: No No Train with Parallel Computing Toolbox and generate CUDA code with GPU Coder [23] No Yes [24 ...

  4. Keras - Wikipedia

    en.wikipedia.org/wiki/Keras

    Keras was first independent software, then integrated into the TensorFlow library, and later supporting more. "Keras 3 is a full rewrite of Keras [and can be used] as a low-level cross-framework language to develop custom components such as layers, models, or metrics that can be used in native workflows in JAX, TensorFlow, or PyTorch — with ...

  5. Advanced Vector Extensions - Wikipedia

    en.wikipedia.org/wiki/Advanced_Vector_Extensions

    TensorFlow since version 1.6 and tensorflow above versions requires CPU supporting at least AVX. [58] Various CPU-based cryptocurrency miners (like pooler's cpuminer for Bitcoin and Litecoin) use AVX and AVX2 for various cryptography-related routines, including SHA-256 and scrypt. FFTW can utilize AVX, AVX2 and AVX-512 when available.

  6. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    In computing, CUDA is a proprietary [1] 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.

  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. Computer compatibility - Wikipedia

    en.wikipedia.org/wiki/Computer_compatibility

    Software compatibility can refer to the compatibility that a particular software has running on a particular CPU architecture such as Intel or PowerPC. [1] Software compatibility can also refer to ability for the software to run on a particular operating system. Very rarely is a compiled software compatible with multiple different CPU ...

  9. Google Tensor - Wikipedia

    en.wikipedia.org/wiki/Google_Tensor

    "Tensor" is a reference to Google's TensorFlow and Tensor Processing Unit technologies, and the chip is developed by the Google Silicon team housed within the company's hardware division, led by vice president and general manager Phil Carmack alongside senior director Monika Gupta, [15] in conjunction with the Google Research division.