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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]

  3. Nvidia NVDEC - Wikipedia

    en.wikipedia.org/wiki/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. [2]

  4. Nvidia NVENC - Wikipedia

    en.wikipedia.org/wiki/Nvidia_NVENC

    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).

  5. Data Matrix - Wikipedia

    en.wikipedia.org/wiki/Data_Matrix

    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]

  6. Convolutional code - Wikipedia

    en.wikipedia.org/wiki/Convolutional_code

    To convolutionally encode data, start with k memory registers, each holding one input bit.Unless otherwise specified, all memory registers start with a value of 0. The encoder has n modulo-2 adders (a modulo 2 adder can be implemented with a single Boolean XOR gate, where the logic is: 0+0 = 0, 0+1 = 1, 1+0 = 1, 1+1 = 0), and n generator polynomials — one for each adder (see figure below).

  7. General-purpose computing on graphics processing units

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

    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).

  8. Low-density parity-check code - Wikipedia

    en.wikipedia.org/wiki/Low-density_parity-check_code

    This LDPC code fragment represents a three-bit message encoded as six bits. Redundancy is used, here, to increase the chance of recovering from channel errors. This is a (6, 3) linear code, with n = 6 and k = 3. Again ignoring lines going out of the picture, the parity-check matrix representing this graph fragment is

  9. Video Processing Engine - Wikipedia

    en.wikipedia.org/wiki/Video_Processing_Engine

    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.