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  2. 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.

  3. AMDgpu (Linux kernel module) - Wikipedia

    en.wikipedia.org/wiki/AMDgpu_(Linux_kernel_module)

    AMDgpu is an open source device driver for the Linux operating system developed by AMD to support its Radeon lineup of graphics cards (GPUs). It was announced in 2014 as the successor to the previous radeon device driver as part of AMD's new "unified" driver strategy, [3] and was released on April 20, 2015.

  4. Windows Subsystem for Linux - Wikipedia

    en.wikipedia.org/wiki/Windows_Subsystem_for_Linux

    GUI support for WSL 2 to run Linux applications with graphical user interfaces (GUIs) was introduced in Windows build 21364. [17] Both of them are shipped in Windows 11. In April 2021, Microsoft released a Windows 10 test build that also includes the ability to run Linux graphical user interface (GUI) apps using WSL 2 and CBL-Mariner.

  5. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    When it was first introduced, the name was an acronym for Compute Unified Device Architecture, [3] but Nvidia later dropped the common use of the acronym and now rarely expands it. [4] CUDA is a software layer that gives direct access to the GPU's virtual instruction set and parallel computational elements for the execution of compute kernels. [5]

  6. Free and open-source graphics device driver - Wikipedia

    en.wikipedia.org/wiki/Free_and_open-source...

    Device Dependent X (DDX), another 2D graphics device driver for X.Org Server; The DRM is kernel-specific. A VESA driver is generally available for any operating system. The VESA driver supports most graphics cards without acceleration and at display resolutions limited to a set programmed in the Video BIOS by the manufacturer. [15]

  7. Google JAX - Wikipedia

    en.wikipedia.org/wiki/Google_JAX

    JAX is a machine learning framework for transforming numerical functions. [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).

  8. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    While the reference implementation runs on single devices, TensorFlow can run on multiple CPUs and GPUs (with optional CUDA and SYCL extensions for general-purpose computing on graphics processing units). [18] TensorFlow is available on 64-bit Linux, macOS, Windows, and mobile computing platforms including Android and iOS. [citation needed]

  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.