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  2. ROCm - Wikipedia

    en.wikipedia.org/wiki/ROCm

    Nvidia's CUDA is closed-source, whereas AMD ROCm is open source. There is open-source software built on top of the closed-source CUDA, for instance RAPIDS . CUDA is able run on consumer GPUs, whereas ROCm support is mostly offered for professional hardware such as AMD Instinct and AMD Radeon Pro .

  3. Nvidia CUDA Compiler - Wikipedia

    en.wikipedia.org/wiki/Nvidia_CUDA_Compiler

    CUDA code runs on both the central processing unit (CPU) and graphics processing unit (GPU). NVCC separates these two parts and sends host code (the part of code which will be run on the CPU) to a C compiler like GNU Compiler Collection (GCC) or Intel C++ Compiler (ICC) or Microsoft Visual C++ Compiler, and sends the device code (the part which will run on the GPU) to the GPU.

  4. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    In computing, CUDA is a proprietary [2] 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.

  5. 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]

  6. Parallel Thread Execution - Wikipedia

    en.wikipedia.org/wiki/Parallel_Thread_Execution

    The Nvidia CUDA Compiler (NVCC) translates code written in CUDA, a C++-like language, into PTX instructions (an assembly language), and the graphics driver contains a compiler which translates PTX instructions into executable binary code, [2] which can run on the processing cores of Nvidia graphics processing units (GPUs).

  7. 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] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.

  8. Nvidia System Tools - Wikipedia

    en.wikipedia.org/wiki/Nvidia_System_Tools

    NVIDIA System Tools (previously called nTune) is a discontinued collection of utilities for accessing, monitoring, and adjusting system components, including temperature and voltages with a graphical user interface within Windows, rather than through the BIOS.

  9. Ada Lovelace (microarchitecture) - Wikipedia

    en.wikipedia.org/wiki/Ada_Lovelace_(micro...

    NVENC AV1 hardware encoding with support for up to 8K resolution at 60FPS in 10-bit color is added, enabling higher video fidelity at lower bit rates compared to the H.264 and H.265 codecs. [20] Nvidia claims that its NVENC AV1 encoder featured in the Lovelace architecture is 40% more efficient than the H.264 encoder in the Ampere architecture ...