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posted by martyb on Wednesday June 23 2021, @10:34AM   Printer-friendly [Skip to comment(s)]

Testing AMD's FidelityFX Super Resolution (FSR): Image Analysis and Preliminary Performance

The most prominent form of [upscaling algorithm] today is Nvidia's [Deep Learning Super Sampling (DLSS)], the company's proprietary AI-based temporal upscaling solution that runs on GeForce RTX GPUs. Temporal upscaling means data is accumulated from multiple frames and combined into the final image, with the AI component running on Nvidia's Tensor cores to assist with this reconstruction. DLSS has gone through more than one iteration, and right now at version 2.0, it's a major improvement over the initial release and it's also gathered decent game support after much work from Nvidia.

[AMD's FidelityFX Super Resolution (FSR)] takes a different approach. Instead of using temporal upscaling, FSR relies exclusively on spatial upscaling. AMD tells us that AI is not used at any stage of the FSR process (so FSR is not the technology described in that patent that's been floating around). This greatly simplifies the algorithm – spatial upscaling does not rely on data from multiple frames, or motion vectors, which makes it easier to integrate into games as there are less data inputs. However, with less data to work with, spatial upscaling algorithms need to be really good at figuring out how to reconstruct the image, and traditionally this is where they've fallen short.

AMD hasn't gone into great detail on how their algorithm works, but they tell us this is not a simple rehash of bilinear upscaling, which is the 'standard' method for spatial upscaling. AMD calls their technique an "advanced edge reconstruction algorithm," which is combined with a sharpening pass to create the final image. There is only one input to the algorithm, which is the lower resolution frame.

[...] Despite being a simpler technique, FSR still requires per-game integration. This is because FSR needs to be run before the final effects stage in the pipeline, so before the HUD is rendered, and before things like film grain are implemented. If FSR was applied to the final frame output from a game, many elements (like the HUD) would be upscaled, likely with artifacts and other visual problems. By optimizing each game, you can make sure only the intended portion of the game is run at a reduced render resolution.

At launch, FSR only works with a handful of games. It works on older GPUs and some from its competitors, such as AMD's RX 480 or Nvidia's GTX 1060. Direct comparisons to DLSS aren't possible until a game adds support for both features.

Gamers Nexus (26m58s) and Hardware Unboxed (38m44s) videos about FSR.

Nvidia hopes to step up adoption of DLSS, and recently announced support for games running on Linux under Proton (Wine fork).

NVIDIA Releasing DLSS Support For Vulkan API Games On Linux Tomorrow

NVIDIA announced earlier this month that they would be bringing DLSS to Linux / Steam Play and tomorrow they will be introducing that initial driver support.

There aren't yet any Linux native games making use of DLSS but this support is focused on Steam Play (Proton) for Windows DLSS-enabled games to also benefit from that upscaling technology under Linux.

Tomorrow NVIDIA will provide their initial Linux driver for supporting DLSS on Linux with Vulkan API games. It won't be until autumn that all the pieces are in place for allowing Direct3D-based DLSS games to make use of the functionality with DXVK/VKD3D-Proton under Steam Play.

Previously: AMD at Computex 2021: 5000G APUs, 6000M Mobile GPUs, FidelityFX Super Resolution, and 3D Chiplets


Original Submission

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AMD at Computex 2021: 5000G APUs, 6000M Mobile GPUs, FidelityFX Super Resolution, and 3D Chiplets 10 comments

AMD's Ryzen 5000G APUs now have a release date for the DIY market: August 5th. The 8-core Ryzen 7 5700G has a suggested price of $359, while the 6-core Ryzen 5 5600G will be $259.

AMD announced the Radeon RX 6800M, 6700M, and 6600M discrete GPUs for laptops, promising better performance, efficiency, and battery-constrained performance. The Radeon RX 6800M is a 40 compute unit design (equivalent to the Radeon RX 6700 XT on desktop) with 12 GB of VRAM.

AMD biggest announcements were the introduction of FidelityFX Super Resolution (FSR) and the demonstration of a 3D chiplet design. FSR uses a spatial scaling algorithm to upscale game graphics for higher frame rates at a given resolution. The algorithm competes with Nvidia's Deep Learning Super Sampling (DLSS), but will be released as open source and work with some older AMD GPUs, integrated graphics, as well as competing products from Nvidia and Intel (it was shown running on an Nvidia GTX 1060).

AMD CEO Lisa Su also showed off a modified, delidded Ryzen 9 5900X CPU prototype, with "3D V-Cache technology". It was identical to the standard 5900X with the exception of through-silicon via (TSV) stacked L3 cache. This allowed the 5900X prototype to have 192 MB of total L3 cache instead of 64 MB (96 MB per 8-core chiplet). AMD claims it can run games with an average of +15% performance (simply due to the larger cache size), and some version of this will appear in products that are starting production at the end of 2021.

Related: TSMC "5nm", "3nm", Stacked Silicon, and More


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  • (Score: 4, Informative) by Mojibake Tengu on Wednesday June 23 2021, @10:54AM (3 children)

    by Mojibake Tengu (8598) Subscriber Badge on Wednesday June 23 2021, @10:54AM (#1148349) Journal

    TFA:

    AMD hasn't gone into great detail on how their algorithm works, but they tell us this is not a simple rehash of bilinear upscaling, which is the 'standard' method for spatial upscaling. AMD calls their technique an "advanced edge reconstruction algorithm," which is combined with a sharpening pass to create the final image. There is only one input to the algorithm, which is the lower resolution frame.

    is pure anti-AMD propaganda.

    The whole FidelityFX thing is open source (MIT license):
    https://www.amd.com/en/technologies/radeon-software-fidelityfx [amd.com]
    https://gpuopen.com/effects/ [gpuopen.com]

    That's why people of dozens engines already use it. Funny enough, it works on some NVidia hardware too.

    "Create wonder. No black boxes."

    --
    The edge of 太玄 cannot be defined, for it is beyond every aspect of design
    • (Score: -1, Troll) by Anonymous Coward on Wednesday June 23 2021, @02:04PM (1 child)

      by Anonymous Coward on Wednesday June 23 2021, @02:04PM (#1148374)

      If only there were some way to demonstrate how well these algorithms work. At least we have pages of marketing spiel we can read.

      • (Score: 3, Interesting) by Mojibake Tengu on Wednesday June 23 2021, @02:28PM

        by Mojibake Tengu (8598) Subscriber Badge on Wednesday June 23 2021, @02:28PM (#1148378) Journal

        Current Unreal Engine 5 is the topmost of over 50 existing engines to demonstrate these algorithms.

        Any DirectX11, DirectX12 or Vulkan application may embrace these algorithms.

        --
        The edge of 太玄 cannot be defined, for it is beyond every aspect of design
    • (Score: 3, Informative) by takyon on Wednesday June 23 2021, @08:49PM

      by takyon (881) <reversethis-{gro ... s} {ta} {noykat}> on Wednesday June 23 2021, @08:49PM (#1148469) Journal

      AMD FidelityFX Super Resolution Source Code Coming Next Month [phoronix.com]

      Today it's Windows-only with no Linux support being introduced. FidelityFX Super Resolution is open-source but the code drop will not be until next month.

      --
      [SIG] 10/28/2017: Soylent Upgrade v14 [soylentnews.org]
  • (Score: 1, Interesting) by Anonymous Coward on Wednesday June 23 2021, @02:08PM (1 child)

    by Anonymous Coward on Wednesday June 23 2021, @02:08PM (#1148375)

    If this works, it's like a function that receives the mean and returns the samples. Impressive!

    • (Score: 0) by Anonymous Coward on Wednesday June 23 2021, @03:11PM

      by Anonymous Coward on Wednesday June 23 2021, @03:11PM (#1148387)

      um... no. not by a long shot.

      the average of 1, 2, 3, 4, 5, 6, 7, 8, 9 is the same as the average of 1, 9, 2, 8, 3, 7, 4, 6, 5.
      in this algorithm there are certainly assumptions put in about where the different "samples" are placed, if you insist on thinking of it that way.

  • (Score: 1, Insightful) by Anonymous Coward on Wednesday June 23 2021, @04:52PM

    by Anonymous Coward on Wednesday June 23 2021, @04:52PM (#1148405)

    These new technologies are a step backwards in image fidelity -- at least 25X supersampling is needed to avoid aliasing distortion. The "super" in their names is completely false!

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