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  2. CuPy - Wikipedia

    en.wikipedia.org/wiki/CuPy

    CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.

  3. 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.

  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. List of Rockchip products - Wikipedia

    en.wikipedia.org/wiki/List_of_Rockchip_products

    Rockchip announced the first member of the RK33xx family at the CES show in January 2015. The RK3368 is a SoC targeting tablets and media boxes featuring a 64-bit octa-core Cortex-A53 CPU and an OpenGL ES 3.1-class GPU. [40] Octa-Core Cortex-A53 64-bit CPU, up to 1.5 GHz; PowerVR SGX6110 GPU with support for OpenGL 3.1 and OpenGL ES 3.0; 28 nm ...

  6. 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).

  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]

  8. ROCm - Wikipedia

    en.wikipedia.org/wiki/ROCm

    ROCm [3] is an Advanced Micro Devices (AMD) software stack for graphics processing unit (GPU) programming. ROCm spans several domains: general-purpose computing on graphics processing units (GPGPU), high performance computing (HPC), heterogeneous computing.

  9. OpenCL - Wikipedia

    en.wikipedia.org/wiki/OpenCL

    OpenCL (Open Computing Language) is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors or hardware accelerators.