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{{short description|Image upscaling technology by Nvidia}}
{{Puffery|date=March 2024}}
'''Deep
All generations of DLSS are available on all [[Nvidia RTX|RTX]]-branded cards from Nvidia in supported titles. However, the
== History ==
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In April 2020, Nvidia advertised and shipped an improved version of DLSS named DLSS 2.0 with [[Device driver|driver]] version 445.75. DLSS 2.0 was available for a few existing games including ''Control'' and ''[[Wolfenstein: Youngblood]]'', and would later be added to many newly released games and [[game engine]]s such as [[Unreal Engine]] and [[Unity (game engine)|Unity]].<ref>{{Cite web|date=2021-02-11|title=NVIDIA DLSS Plugin and Reflex Now Available for Unreal Engine|url=https://developer.nvidia.com/blog/nvidia-dlss-and-reflex-now-available-for-unreal-engine-4-26/|access-date=2022-02-07|website=NVIDIA Developer Blog|language=en-US}}</ref><ref>{{Cite web|date=2021-04-14|title=NVIDIA DLSS Natively Supported in Unity 2021.2|url=https://developer.nvidia.com/blog/nvidia-dlss-natively-supported-in-unity-2021-2/|access-date=2022-02-07|website=NVIDIA Developer Blog|language=en-US}}</ref> This time Nvidia said that it used the Tensor Cores again, and that the AI did not need to be trained specifically on each game.<ref name="techspot" /><ref name="gamersnexus">{{cite web|url=https://www.gamersnexus.net/news-pc/3572-hw-news-crysis-remastered-ray-tracing-on-amd-nvidia|title=HW News - Crysis Remastered Ray Tracing, NVIDIA DLSS 2, Ryzen 3100 Rumors|date=2020-04-19|access-date=2020-04-19|quote=The original DLSS required training the AI network for each new game. DLSS 2.0 trains using non-game-specific content, delivering a generalized network that works across games. This means faster game integrations, and ultimately more DLSS games.|archive-date=2020-09-26|archive-url=https://web.archive.org/web/20200926224142/https://www.gamersnexus.net/news-pc/3572-hw-news-crysis-remastered-ray-tracing-on-amd-nvidia|url-status=dead}}</ref> Despite sharing the DLSS branding, the two iterations of DLSS differ significantly and are not backwards-compatible.<ref name="NVIDIA">Edward Liu, NVIDIA [https://developer.nvidia.com/gtc/2020/video/s22698-vid "DLSS 2.0 - Image Reconstruction for Real-time Rendering with Deep Learning"]</ref><ref name=":1">{{Cite web|title=Truly Next-Gen: Adding Deep Learning to Games & Graphics (Presented by NVIDIA)|url=https://www.gdcvault.com/play/1026184/Truly-Next-Gen-Adding-Deep|access-date=2022-02-07|website=GDC Vault}}</ref>
In January 2025, Nvidia stated that there are over 540 games and apps supporting DLSS, and that over 80% of [[Nvidia RTX]] users activate DLSS.<ref>{{Cite web |date=2025-01-16 |title=DLSS enabled by over 80% of GeForce RTX gaming GPU owners, claims Nvidia |url=https://www.pcgamesn.com/nvidia/dlss-80-percent |access-date=2025-01-31 |website=PCGamesN |language=en-US}}</ref>
In March 2025, there were more than 100 games that support DLSS 4, according to Nvidia.<ref>{{Cite web |last=Mujtaba |first=Hassan |date=2025-03-13 |title=NVIDIA DLSS 4 Now In Over 100 Games With More Titles Coming Soon, Neural Shading Support For DirectX Arriving Next Month |url=https://wccftech.com/nvidia-dlss-4-now-in-over-100-games-more-titles-coming-soon-neural-shading-support-directx-next-month/ |access-date=2025-05-20 |website=Wccftech |language=en-US}}</ref> By May 2025, over 125 games supported DLSS 4.<ref>{{Cite web |last=Mujtaba |first=Hassan |date=2025-05-19 |title=NVIDIA DLSS 4 Now Available In Over 125 Games & Apps, DOOM: The Dark Ages Path Tracing Update In June & Even More DLSS Titles |url=https://wccftech.com/nvidia-dlss-4-125-games-doom-the-dark-ages-path-tracing-update-june-more-dlss-titles/ |access-date=2025-05-20 |website=Wccftech |language=en-US}}</ref><ref>{{Cite web |last=Palumbo |first=Alessio |date=2025-05-19 |title=NVIDIA DLSS 4 Multi Frame Generation and Other RTX Updates Shown Off for Upcoming and Existing PC Games |url=https://wccftech.com/nvidia-dlss-4-multi-frame-generation-and-other-rtx-updates-shown-off-for-upcoming-and-existing-pc-games/ |access-date=2025-05-20 |website=Wccftech |language=en-US}}</ref>
The first [[video game console]] to use DLSS, the [[Nintendo Switch 2]], was released on June 5, 2025.<ref>{{Cite news |last=Stuart |first=Keith |date=2025-06-05 |title=The Nintendo Switch 2 is out – here's everything you need to know |url=https://www.theguardian.com/games/2025/jun/05/the-nintendo-switch-2-is-out-today-heres-everything-you-need-to-know |access-date=2025-06-09 |work=The Guardian |language=en-GB |issn=0261-3077}}</ref>
=== Release history ===
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|"1.9" (unofficial name)||August 2019||DLSS 1.0 adapted for running on the CUDA shader cores instead of tensor cores, used for ''[[Control (video game)|Control]]''<ref name="eurogamer"/><ref name="techspot"/><ref name="nividiacontrol">{{cite web |last1=Edelsten |first1=Andrew |title=NVIDIA DLSS: Control and Beyond |url=https://www.nvidia.com/en-us/geforce/news/dlss-control-and-beyond/ |publisher=Nvidia |access-date=11 August 2020 |date=30 August 2019 |quote=Leveraging this AI research, we developed a new image processing algorithm that approximated our AI research model and fit within our performance budget. This image processing approach to DLSS is integrated into Control, and it delivers up to 75% faster frame rates.}}</ref>
|-
|2.0||April 2020||An AI accelerated form of [[Temporal anti-aliasing|TAA]]U using Tensor Cores, and trained generically<ref name="control2">{{cite web|url=https://www.techquila.co.in/nvidia-dlss-2-control-review/|title=NVIDIA DLSS 2.0 Review with Control – Is This Magic?|work=TechQuila |publisher=techquila.co.in|date=2020-04-05|access-date=2020-04-06}}</ref>
|-
|3.0
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|3.5
|September 2023
|DLSS 3.5 adds
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|4.0
|January 2025
|DLSS 4.0 adds
|}
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|Ultra Quality<ref name=":5">{{cite web |title=NVIDIA preparing Ultra Quality mode for DLSS, 2.2.9.0 version spotted |url=https://videocardz.com/newz/nvidia-preparing-ultra-quality-mode-for-dlss-2-2-9-0-version-spotted |access-date=2021-07-06 |website=VideoCardz.com |language=en-US}}</ref><sub> (unused)</sub>
|1.32x
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|Quality
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=== DLSS 2.0 ===
DLSS 2.0 is a [[temporal anti-aliasing]] [[upsampling]] (TAAU) implementation, using data from previous frames extensively through sub-pixel jittering to resolve fine detail and reduce aliasing. The data DLSS 2.0 collects includes: the raw low-resolution input, [[motion vector]]s, [[Z-buffering|depth buffers]], and [[Exposure value|exposure]] / brightness information.<ref name="NVIDIA" /> It can also be used as a simpler TAA implementation where the image is rendered at 100% resolution, rather than being upsampled by DLSS, Nvidia brands this as [[DLAA]] (
TAA(U) is used in many modern video games and [[game engine]]s;<ref>[https://de45xmedrsdbp.cloudfront.net/Resources/files/TemporalAA_small-59732822.pdf Temporal AA small] Cloud Front</ref> however, all previous implementations have used some form of manually written [[heuristic]]s to prevent temporal artifacts such as [[Ghosting (television)|ghosting]] and [[Flicker (light)|flickering]]. One example of this is neighborhood clamping which forcefully prevents samples collected in previous frames from deviating too much compared to nearby pixels in newer frames. This helps to identify and fix many temporal artifacts, but deliberately removing fine details in this way is analogous to applying a [[Box blur|blur filter]], and thus the final image can appear blurry when using this method.<ref name="NVIDIA" />
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DLSS 2.0 uses a [[Convolutional neural network|convolutional]] [[Autoencoder|auto-encoder]] [[neural network]]<ref name="nvidia20" /> trained to identify and fix temporal artifacts, instead of manually programmed heuristics as mentioned above. Because of this, DLSS 2.0 can generally resolve detail better than other TAA and TAAU implementations, while also removing most temporal artifacts. This is why DLSS 2.0 can sometimes produce a sharper image than rendering at higher, or even native resolutions using traditional TAA. However, no temporal solution is perfect, and artifacts (ghosting in particular) are still visible in some scenarios when using DLSS 2.0.
Because temporal artifacts occur in most art styles and environments in broadly the same way, the neural network that powers DLSS 2.0 does not need to be retrained when being used in different games. Despite this, Nvidia does frequently ship new minor revisions of DLSS 2.0 with new titles,<ref>{{Cite web|title=NVIDIA DLSS DLL (2.3.7) Download|url=https://www.techpowerup.com/download/nvidia-dlss-dll/|access-date=2022-02-10|website=TechPowerUp|language=en}}</ref> so this could suggest some minor training optimizations may be performed as games are released, although Nvidia does not provide changelogs for these minor revisions to confirm this. The main advancements compared to DLSS 1.0 include: Significantly improved detail retention, a generalized neural network that does not need to be re-trained per-game, and ~2x less overhead (~
It should also be noted that forms of TAAU such as DLSS 2.0 are not [[Video scaler|upscalers]] in the same sense as techniques such as ESRGAN or DLSS 1.0, which attempt to create new information from a low-resolution source; instead, TAAU works to recover data from previous frames, rather than creating new data. In practice, this means low resolution [[Texture mapping|textures]] in games will still appear low-resolution when using current TAAU techniques. This is why Nvidia recommends game developers use higher resolution textures than they would normally for a given rendering resolution by applying a mip-map bias when DLSS 2.0 is enabled.<ref name="NVIDIA" />
=== DLSS 3.0 ===
Augments DLSS 2.0 by making use of [[motion interpolation]]. The DLSS
=== DLSS 3.5 ===
DLSS 3.5 adds
=== DLSS 4.0 ===
The fourth generation of
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=== Manually upgrading DLSS support ===
Users can manually replace the [[Dynamic-link library|DLLs]] in games to support a newer version of DLSS. DLSS Swapper, an [[open source]] utility, can automatically do this for all installed games.<ref>{{cite web|url=https://www.pcgamer.com/hardware/this-open-source-tool-updates-dlss-to-the-latest-version-in-all-your-games-at-once-and-no-matter-the-launcher/|title=This open source tool updates DLSS to the latest version in all your games at once and no matter the launcher|last=Edser|first=Andy|work=[[PC Gamer]]|date=2024-08-30|accessdate=2025-01-28}}</ref> Replacing DLL files can not add DLSS support or features to games that do not already implement them, though some [[Video game modding|mods]] can add frame generation support.<ref>{{cite web|url=https://www.tomshardware.com/pc-components/gpus/dlss-swapper-now-updates-fsr-xess-and-dlss-too-supports-all-major-upscaling-frame-gen-technologies|title=DLSS Swapper now updates FSR, XeSS, and DLSS, too — Supports all major upscaling/frame gen technologies|last=Nasir|first=Hassam|work=[[Tom's Hardware]]|date=2025-01-27|accessdate=2025-01-28}}</ref>
== Anti-aliasing ==
DLSS requires and applies its own [[anti-aliasing]] method. Thus, depending on the game and quality setting used, using DLSS may improve image quality even over native resolution rendering.<ref>{{Cite web |last=Smith |first=Matthew S. |date=2023-12-28 |title=What Is DLSS and Why Does it Matter for Gaming? |url=https://www.ign.com/articles/what-is-nvidia-dlss-meaning |access-date=2024-06-13 |website=IGN |language=en}}</ref> It operates on similar principles to [[Temporal anti-aliasing|TAA]]. Like TAA, it uses information from past frames to produce the current frame. Unlike TAA, DLSS does not sample every pixel in every frame. Instead, it samples different pixels in different frames and uses pixels sampled in past frames to fill in the unsampled pixels in the current frame. DLSS uses machine learning to combine samples in the current frame and past frames, and it can be thought of as an advanced and superior TAA implementation made possible by the available tensor cores.<ref name="NVIDIA" /> [[Nvidia]] also offers [[
== Architecture ==
With the exception of the shader-core version implemented in ''Control'', DLSS is only available on [[GeForce 20 series|GeForce RTX 20]], [[GeForce 30 series|GeForce RTX 30]], [[GeForce 40 series|GeForce RTX 40]], [[GeForce 50 series|GeForce RTX 50]], and [[Quadro#Quadro RTX|Quadro RTX]] series of video cards, using dedicated [[AI accelerator]]s called '''Tensor Cores'''.<ref name="nvidia20"/>{{Failed verification|date=March 2024}} Tensor Cores are available since the Nvidia [[Volta (microarchitecture)|Volta]] [[graphics processing unit|GPU]] [[microarchitecture]], which was first used on the [[Nvidia Tesla|Tesla V100]] line of products.<ref>
{{cite web|url=https://www.tomshardware.com/news/nvidia-tensor-core-tesla-v100,34384.html|title=On Tensors, Tensorflow, And Nvidia's Latest 'Tensor Cores'|publisher=tomshardware.com|date=2017-04-11|access-date=2020-04-08}}</ref> They are used for doing [[Multiply–accumulate operation|fused multiply-add]] (FMA) operations that are used extensively in neural network calculations for applying a large series of multiplications on weights, followed by the addition of a bias. Tensor cores can operate on FP16, INT8, INT4, and INT1 data types. Each core can do 1024 bits of FMA operations per clock, so 1024 INT1, 256 INT4, 128 INT8, and 64 FP16 operations per clock per tensor core, and most Turing GPUs have a few hundred tensor cores.<ref>{{Cite web|title=Tensor Core DL Performance Guide|url=https://developer.download.nvidia.com/video/gputechconf/gtc/2019/presentation/s9926-tensor-core-performance-the-ultimate-guide.pdf|url-status=live|website=Nvidia|archive-url=https://web.archive.org/web/20201111223322/https://developer.download.nvidia.com/video/gputechconf/gtc/2019/presentation/s9926-tensor-core-performance-the-ultimate-guide.pdf |archive-date=2020-11-11 }}</ref> The Tensor Cores use [[CUDA]] [[Warp (CUDA)|Warp]]-Level Primitives on 32 parallel threads to take advantage of their parallel architecture.<ref>{{cite web|url=https://devblogs.nvidia.com/using-cuda-warp-level-primitives/|title=Using CUDA Warp-Level Primitives|publisher=[[Nvidia]]|date=2018-01-15|access-date=2020-04-08|quote=NVIDIA GPUs execute groups of threads known as warps in SIMT (Single Instruction, Multiple Thread) fashion.}}</ref> A Warp is a set of 32 [[Thread (computing)|threads]] which are configured to execute the same instruction. Since [[Windows 10 version 1903]], Microsoft Windows provided [[DirectML]] as one part of [[DirectX]] to support Tensor Cores.
==
The use of DLSS
The transformer-based AI upscaling model introduced with DLSS 4 received moderate praise for its improved image quality with regard to increased stability, reduced ghosting, better anti-aliasing, and higher level of detail, as well as its backward compatability and higher training scalability regarding future improvements.<ref>{{Cite news |title=NVIDIA DLSS 4 Transformer Review - Better Image Quality for Everyone |url=https://www.techpowerup.com/review/nvidia-dlss-4-transformers-image-quality/ |archive-url=http://web.archive.org/web/20250128024629/https://www.techpowerup.com/review/nvidia-dlss-4-transformers-image-quality/ |archive-date=2025-01-28 |access-date=2025-01-31 |work=TechPowerUp |language=en}}</ref><ref>{{Cite web |last=Leadbetter |first=Richard |date=2025-01-07 |title=Hands-on with DLSS 4 on Nvidia's new GeForce RTX 5080 |url=https://www.eurogamer.net/digitalfoundry-2025-hands-on-with-dlss-4-on-nvidias-new-geforce-rtx-5080 |access-date=2025-01-31 |website=Eurogamer.net |language=en}}</ref>
▲The use of DLSS frame generation may lead to increased [[input latency]],<ref>{{Cite web |date=2023-11-21 |title=When a high frame rate can lose you the game |url=https://www.digitaltrends.com/computing/when-frames-dont-win-games/ |access-date=2024-07-09 |website=Digital Trends |language=en}}</ref> as well as [[visual artifacts]].<ref>{{Cite web |date=2023-03-08 |title=Nvidia DLSS 3 Revisit: We Try It Out in 9 Games |url=https://www.techspot.com/article/2639-dlss-3-revisit/ |access-date=2024-07-09 |website=TechSpot |language=en-US}}</ref> It has also been criticized that by implementing DLSS in their games, game developers no longer have an incentive to optimize them so that they also run smoothly in native resolution on modern PC hardware. For example, for the game ''[[Alan Wake 2]]'' in [[4K resolution]] at the highest graphics settings with [[Ray tracing (graphics)|ray tracing]] enabled, the use of DLSS in Performance mode is recommended even with graphics cards such as the [[Nvidia GeForce RTX 4080]] in order to achieve 60 fps.<ref>{{Cite web |date=2023-10-26 |title=Alan Wake 2 on PC is an embarrassment of riches |url=https://www.digitaltrends.com/computing/alan-wake-2-pc-performance/ |access-date=2024-07-09 |website=Digital Trends |language=en}}</ref>
== See also ==
* [[GPUOpen#FidelityFX Super Resolution|FidelityFX Super Resolution]] – competing technology from [[AMD]]
* [[Intel XeSS]] – competing technology from [[Intel]]
* [[PlayStation Spectral Super Resolution]] – similar technology from [[
== References ==
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[[Category:Nvidia]]
[[Category:Anti-aliasing algorithms]]
[[Category:Artificial intelligence]]
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