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  2. GeForce 16 series - Wikipedia

    en.wikipedia.org/wiki/GeForce_16_series

    The GeForce 16 series includes the GTX 1650, 1650 Super, 1660, 1660 Super, 1660 Ti, and a lower-end GTX 1630, which was released later. The GTX 1650 features both a GDDR5 and GDDR6 version. Like the GeForce 20 series, the GeForce 16 series was followed by the GeForce 30 series. The 16 series was the last GPU generation of the GeForce series ...

  3. Nvidia NVDEC - Wikipedia

    en.wikipedia.org/wiki/Nvidia_NVDEC

    Nvidia NVDEC. Nvidia NVDEC (formerly known as NVCUVID[ 1]) is a feature in its graphics cards that performs video decoding, offloading this compute-intensive task from the CPU. [ 2] NVDEC is a successor of PureVideo and is available in Kepler and later NVIDIA GPUs. It is accompanied by NVENC for video encoding in Nvidia's Video Codec SDK.

  4. GeForce - Wikipedia

    en.wikipedia.org/wiki/GeForce

    Like the RTX Super refresh, Nvidia on October 29, 2019, announced the GTX 1650 Super and 1660 Super cards, which replaced their non-Super counterparts. On June 28, 2022, Nvidia quietly released their GTX 1630 card, which was meant for low-end gamers.

  5. GeForce 20 series - Wikipedia

    en.wikipedia.org/wiki/GeForce_20_series

    The GeForce 20 series is a family of graphics processing units developed by Nvidia. [ 8] Serving as the successor to the GeForce 10 series, [ 9] the line started shipping on September 20, 2018, [ 10] and after several editions, on July 2, 2019, the GeForce RTX Super line of cards was announced. [ 11]

  6. Nvidia PureVideo - Wikipedia

    en.wikipedia.org/wiki/Nvidia_PureVideo

    NVIDIA TITAN Xp, TITAN X, GeForce GTX 1080 Ti: GP102 VP8 H August 2016 ... GeForce GTX 1650 Super, GTX 1660, GTX 1660 Super, GTX 1660 Ti: TU116 VP10 J February 2019

  7. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    In computing, CUDA (originally Compute Unified Device Architecture) 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 ( GPGPU ).

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