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  2. Kepler (microarchitecture) - Wikipedia

    en.wikipedia.org/wiki/Kepler_(microarchitecture)

    [2] [3] The efficiency aim was achieved through the use of a unified GPU clock, simplified static scheduling of instruction and higher emphasis on performance per watt. [4] By abandoning the shader clock found in their previous GPU designs, efficiency is increased, even though it requires additional cores to achieve higher levels of performance.

  3. Direct Rendering Manager - Wikipedia

    en.wikipedia.org/wiki/Direct_Rendering_Manager

    The Direct Rendering Manager (DRM) is a subsystem of the Linux kernel responsible for interfacing with GPUs of modern video cards.DRM exposes an API that user-space programs can use to send commands and data to the GPU and perform operations such as configuring the mode setting of the display.

  4. 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.

  5. 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]

  6. Stream processing - Wikipedia

    en.wikipedia.org/wiki/Stream_processing

    The software stack for these systems includes components such as programming models and query languages, for expressing computation; stream management systems, for distribution and scheduling; and hardware components for acceleration including floating-point units, graphics processing units, and field-programmable gate arrays. [2]

  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. 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.

  9. VDPAU - Wikipedia

    en.wikipedia.org/wiki/VDPAU

    The VDPAU interface is to be implemented by device drivers, such as Nvidia GeForce driver, nouveau, amdgpu, to offer end-user software, such as VLC media player or GStreamer, a standardized access to available video decompression acceleration hardware in the form of application-specific integrated circuit (ASIC) blocks on graphics processing ...