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  2. Windows Display Driver Model - Wikipedia

    en.wikipedia.org/wiki/Windows_Display_Driver_Model

    Hardware-accelerated GPU scheduling: masked as an additional option in the system settings, when enabled offloads high-frequency tasks to a dedicated GPU-based scheduling processor, reducing CPU scheduling overhead. Requires ad-hoc hardware and driver support. [61] Sampler Feedback, allowing a finer tune of the resources usage in a scene. [62]

  3. RDNA 2 - Wikipedia

    en.wikipedia.org/wiki/RDNA_2

    Real-time hardware accelerated ray tracing is a new feature for RDNA 2 which is handled by a dedicated ray accelerator inside each CU. [10] Ray tracing on RDNA 2 relies on the more open DirectX Raytracing protocol rather than the Nvidia RTX protocol.

  4. Hardware acceleration - Wikipedia

    en.wikipedia.org/wiki/Hardware_acceleration

    Hardware acceleration is the use of computer hardware designed to perform specific functions more efficiently when compared to software running on a general-purpose central processing unit (CPU). Any transformation of data that can be calculated in software running on a generic CPU can also be calculated in custom-made hardware, or in some mix ...

  5. Desktop Window Manager - Wikipedia

    en.wikipedia.org/wiki/Desktop_Window_Manager

    Under Windows 7 and with WDDM 1.1 drivers, DWM only writes the program's buffer to the video RAM, even if it is a graphics device interface (GDI) program. This is because Windows 7 supports (limited) hardware acceleration for GDI [2] and in doing so does not need to keep a copy of the buffer in system RAM so that the CPU can write to it.

  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. GPU virtualization - Wikipedia

    en.wikipedia.org/wiki/GPU_virtualization

    This technique achieves 96–100% of native performance [3] and high fidelity, [1] but the acceleration provided by the GPU cannot be shared between multiple virtual machines. As such, it has the lowest consolidation ratio and the highest cost, as each graphics-accelerated virtual machine requires an additional physical GPU. [1]

  8. PhysX - Wikipedia

    en.wikipedia.org/wiki/PhysX

    Nvidia started enabling PhysX hardware acceleration on its line of GeForce graphics cards [7] and eventually dropped support for Ageia PPUs. [ 8 ] PhysX SDK 3.0 was released in May 2011 and represented a significant rewrite of the SDK, bringing improvements such as more efficient multithreading and a unified code base for all supported platforms.

  9. Windows Subsystem for Linux - Wikipedia

    en.wikipedia.org/wiki/Windows_Subsystem_for_Linux

    It was also backported to Windows 10 version 1903 and 1909. [15] GPU support for WSL 2 to run GPU-accelerated machine learning was introduced in Windows build 20150. [16] 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.