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Nvidia NVENC (short for Nvidia Encoder) [1] is a feature in Nvidia graphics cards that performs video encoding, offloading this compute-intensive task from the CPU to a dedicated part of the GPU. It was introduced with the Kepler -based GeForce 600 series in March 2012 (GT 610, GT620 and GT630 is Fermi Architecture).
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. [2]
The pixel pipelines take pixel (each pixel is a dimensionless point) and texel information and process it, via specific matrix and vector operations, into a final pixel or depth value; this process is called rasterization. Thus, ROPs control antialiasing, when more than one sample is merged into one pixel.
Nvidia VDPAU Feature Sets [18] are different hardware generations of Nvidia GPU's supporting different levels of hardware decoding capabilities. For feature sets A, B and C, the maximum video width and height are 2048 pixels , minimum width and height 48 pixels, and all codecs are currently limited to a maximum of 8192 macroblocks (8190 for VC ...
nVidia introduced the Video Processing Engine or VPE with the GeForce 4 MX. It is a feature of nVidia's GeForce graphics processor line that offers dedicated hardware to offload parts of the MPEG2 decoding and encoding. The GeForce Go FX 5700 rolled out the VPE 3.0. The VPE later developed into nVidia's PureVideo.
Hardware accelerated video encoding (via NVENC) and decoding (via NVDEC) is supported on NVIDIA Quadro products with Kepler, Maxwell, Pascal, Turing, Ampere and Ada generation GPUs. [ 325 ] [ 326 ] Fermi based GPUs support decoding only.
General-purpose computing on graphics processing units (GPGPU, or less often GPGP) is the use of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU).
A Data Matrix on a Mini PCI card, encoding the serial number 15C06E115AZC72983004. The most popular application for Data Matrix is marking small items, due to the code's ability to encode fifty characters in a symbol that is readable at 2 or 3 mm 2 (0.003 or 0.005 sq in) and the fact that the code can be read with only a 20% contrast ratio. [1]