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  2. JAX (software) - Wikipedia

    en.wikipedia.org/wiki/Google_JAX

    JAX is a machine learning framework for transforming numerical functions developed by Google with some contributions from Nvidia. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).

  3. 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).

  4. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    In January 2019, the TensorFlow team released a developer preview of the mobile GPU inference engine with OpenGL ES 3.1 Compute Shaders on Android devices and Metal Compute Shaders on iOS devices. [30] In May 2019, Google announced that their TensorFlow Lite Micro (also known as TensorFlow Lite for Microcontrollers) and ARM's uTensor would be ...

  5. 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 ...

  6. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    CUDA is designed to work with programming languages such as C, C++, Fortran and Python. This accessibility makes it easier for specialists in parallel programming to use GPU resources, in contrast to prior APIs like Direct3D and OpenGL , which require advanced skills in graphics programming. [ 7 ]

  7. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    Modern libraries provide runtime-optimized implementations of the above functionality or allow to speed up the slow loop by just-in-time compilation. Apache Singa; Caffe: Created by the Berkeley Vision and Learning Center (BVLC). It supports both CPU and GPU. Developed in C++, and has Python and MATLAB wrappers.

  8. 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.

  9. Graphics processing unit - Wikipedia

    en.wikipedia.org/wiki/Graphics_processing_unit

    Components of a GPU. A graphics processing unit (GPU) is a specialized electronic circuit initially designed for digital image processing and to accelerate computer graphics, being present either as a discrete video card or embedded on motherboards, mobile phones, personal computers, workstations, and game consoles.