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  2. GPU-Z - Wikipedia

    en.wikipedia.org/wiki/GPU-Z

    TechPowerUp GPU-Z (or just GPU-Z) is a lightweight utility designed to provide information about video cards and GPUs. [2] The program displays the specifications of Graphics Processing Unit (often shortened to GPU) and its memory; also displays temperature, core frequency, memory frequency, GPU load and fan speeds.

  3. List of Nvidia graphics processing units - Wikipedia

    en.wikipedia.org/wiki/List_of_Nvidia_graphics...

    This number is generally used as a maximum throughput number for the GPU and generally, a higher fill rate corresponds to a more powerful (and faster) GPU. Memory subsection. Bandwidth – Maximum theoretical bandwidth for the processor at factory clock with factory bus width. GHz = 10 9 Hz. Bus type – Type of memory bus or buses used.

  4. Radeon 300 series - Wikipedia

    en.wikipedia.org/wiki/Radeon_300_series

    Originally introduced with the previous generation R9 285 and R9 290 series graphics cards, this feature allows users to run games with higher image quality by rendering frames at above native resolution. Each frame is then downsampled to native resolution. This process is an alternative to supersampling which is not supported by all games.

  5. Comparison of Nvidia nForce chipsets - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_Nvidia_n...

    This is a comparison of chipsets designed by Nvidia. Nvidia stopped producing chipsets in 2009. [ 1 ] Nvidia codenames its chipsets MCPs (Media and Communications Processors).

  6. RDNA 2 - Wikipedia

    en.wikipedia.org/wiki/RDNA_2

    RDNA 2 is a GPU microarchitecture designed by AMD, released with the Radeon RX 6000 series on November 18, 2020. Alongside powering the RX 6000 series, RDNA 2 is also featured in the SoCs designed by AMD for the PlayStation 5 , Xbox Series X/S , and Steam Deck consoles.

  7. Radeon RX 5000 series - Wikipedia

    en.wikipedia.org/wiki/Radeon_RX_5000_series

    The Navi GPUs are the first AMD GPUs to use the new RDNA architecture, [6] whose compute units have been redesigned to improve efficiency and instructions per clock (IPC). It features a multi-level cache hierarchy, which offers higher performance, lower latency, and less power consumption compared to the previous series.

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  9. Comparison of video codecs - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_video_codecs

    GPU usage by codec – some codecs can drastically increase their performance by taking advantage of GPU resources. So, for example, codec A (being optimized for memory usage – i.e., uses less memory) may, on modern computers (which are typically not memory-limited), give slower performance than codec B.

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