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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

    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. [6] In addition to drivers and runtime kernels, the CUDA platform includes compilers, libraries and developer tools to help programmers accelerate their applications.

  4. Graphics address remapping table - Wikipedia

    en.wikipedia.org/wiki/Graphics_address_remapping...

    A GART is used as a means of data exchange between the main memory and video memory through which buffers (i.e. paging/swapping) of textures, polygon meshes and other data are loaded, but can also be used to expand the amount of video memory available for systems with only integrated or shared graphics (i.e. no discrete or inbuilt graphics ...

  5. Comparison of real-time operating systems - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_real-time...

    This is a list of real-time operating systems (RTOSs). This is an operating system in which the time taken to process an input stimulus is less than the time lapsed until the next input stimulus of the same type.

  6. Tensor Processing Unit - Wikipedia

    en.wikipedia.org/wiki/Tensor_Processing_Unit

    [45] [46] The USB, PCI-e, and M.2 products function as add-ons to existing computer systems, and support Debian-based Linux systems on x86-64 and ARM64 hosts (including Raspberry Pi). The machine learning runtime used to execute models on the Edge TPU is based on TensorFlow Lite. [47]

  7. General-purpose computing on graphics processing units

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

    Due to a trend of increasing power of mobile GPUs, general-purpose programming became available also on the mobile devices running major mobile operating systems. Google Android 4.2 enabled running RenderScript code on the mobile device GPU. [ 25 ]

  8. Direct Rendering Manager - Wikipedia

    en.wikipedia.org/wiki/Direct_Rendering_Manager

    DRM augments the Linux System Call Interface with own system calls. [57] The Linux DRM subsystem includes free and open-source drivers to support hardware from the 3 main manufacturers of GPUs for desktop computers (AMD, NVIDIA and Intel), as well as from a growing number of mobile GPU and System on a chip (SoC) integrators. The quality of each ...

  9. Nvidia Jetson - Wikipedia

    en.wikipedia.org/wiki/Nvidia_Jetson

    It is packaged with newer versions of Tegra System Profiler, TensorRT, and cuDNN from the last release. [21] RedHawk Linux is a high-performance RTOS available for the Jetson platform, along with associated NightStar real-time development tools, CUDA/GPU enhancements, and a framework for hardware-in-the-loop and man-in-the-loop simulations. [22]