Search
Close this search box.

Home

What Is Nvidia DLSS For Graphics Card?

Nvidia DLSS?

Nvidia DLSS (Deep Learning Super Sampling) is a technology developed by Nvidia, a leading manufacturer of graphics processing units (GPUs), to improve video game performance and image quality using artificial intelligence and deep learning algorithms.

DLSS works by rendering graphics at a lower resolution and then using AI to upscale the image to a higher resolution in real-time, resulting in smoother, faster gameplay with less demand on the graphics card.

1. DLSS 1

DLSS 1 (Deep Learning Super Sampling version 1) is the initial version of Nvidia’s DLSS technology, first introduced in 2018. DLSS 1 uses deep learning algorithms to upscale lower-resolution images to higher resolutions, resulting in improved image quality and smoother, faster frame rates in video games.

However, DLSS 1 was criticized for sometimes producing blurry or inaccurate images, and its adoption by game developers was limited. In subsequent versions of DLSS, Nvidia has made significant improvements to address these issues and make the technology more widely used and effective.

2. DLSS 2

DLSS 2 (Deep Learning Super Sampling version 2) is the second and current version of Nvidia’s DLSS technology, released in 2020 as an improvement over the initial DLSS 1. DLSS 2 uses advanced AI algorithms and deep learning techniques to upscale lower-resolution images to higher resolutions with even greater accuracy, resulting in sharper and more detailed graphics in video games.

DLSS 2 also allows for more flexible integration with game engines and is less resource-intensive, making it easier to implement and more widely adopted by game developers. Overall, DLSS 2 significantly boosts gaming performance and image quality while minimizing the impact on the hardware required to run games.

3. DLSS 3

As per the latest news, there is no such thing as DLSS 3. The most recent and current version of Nvidia’s DLSS technology is DLSS 2, which was released in 2020 and has since been implemented in a growing number of video games to enhance their graphics and performance. It’s possible that Nvidia may release future versions of DLSS, but as of now, DLSS 2 is the most recent and advanced version available.

What is the Function of DLSS?

The function of DLSS (Deep Learning Super Sampling) is to improve video games’ performance and image quality. DLSS uses artificial intelligence and deep learning algorithms to upscale lower-resolution images to higher resolutions, resulting in smoother, faster gameplay and more detailed and realistic graphics.

This allows players to enjoy high-quality gaming experiences even on less powerful hardware. DLSS achieves this by rendering graphics at a lower resolution and then using AI to upscale the image to a higher resolution in real-time, reducing the demand on the graphics card while maintaining or even enhancing image quality.

The result is an immersive and visually stunning gaming experience accessible to a wider range of gamers.

Functioning of DLSS

DLSS (Deep Learning Super Sampling) uses artificial intelligence and deep learning algorithms to upscale lower-resolution images to higher resolutions in real-time. Here’s how it works:

  • The game engine renders the graphics at a lower resolution than the output resolution, resulting in faster frame rates and improved performance.
  • The lower-resolution image is then fed into a deep neural network, which uses machine learning to learn how to upscale the image to a higher resolution.
  • The neural network then applies this upscaling algorithm to the lower-resolution image, producing a higher-quality image at the output resolution in real-time.
  • Finally, the higher-quality image is displayed on the screen, resulting in smoother, faster gameplay and more detailed and realistic graphics.

DLSS achieves this by using a combination of temporal feedback and spatial feedback. Temporal feedback uses information from previous frames to enhance the quality of the current frame, while spatial feedback uses information from neighboring pixels to improve image quality.

DLSS 2.0 vs. DLSS 2.1

  1. Quality: DLSS 2.1 features several improvements to image quality over DLSS 2.0, including reduced blurring and improved edge sharpness.
  2. Performance: DLSS 2.1 also features improved performance over DLSS 2.0, with faster frame rates and better stability.
  3. VR Support: DLSS 2.1 supports virtual reality (VR) games, which was not available in DLSS 2.0.
  4. Modest Hardware Requirements: DLSS 2.1 also has lower hardware requirements than DLSS 2.0, meaning it can be used in a broader range of hardware.
  5. Support for Higher Resolutions: DLSS 2.1 introduces support for 8K resolution, whereas DLSS 2.0 supports up to 4K resolution.
  6. Improved Motion Vector Support: DLSS 2.1 includes improved support for motion vectors, which allows for better handling of motion blur and other fast-moving objects.

What are DLSS 2.0 Selectable Modes?

DLSS 2.0 Selectable Modes are different options for implementing Nvidia’s Deep Learning Super Sampling technology in video games, offering varying degrees of performance and image quality. Here are the selectable modes available in DLSS 2.0:

  • Quality Mode: This mode provides the highest image quality with the most significant upscaling. It’s ideal for playing at 4K resolution or higher and requires higher-end hardware.
  • Balanced Mode: This mode balances performance and image quality and is ideal for playing at 1440p or 1080p resolution.
  • Performance Mode: This mode provides the highest performance boost but with less upscaling and image quality than the Quality or Balanced mode. It’s ideal for playing at 1080p resolution or lower and for systems with lower-end hardware.
  • Ultra Performance Mode: This mode was added in DLSS 2.2 and is the lowest-quality mode that provides the most significant performance boost. It’s suitable for playing at 1080p resolution or lower on low-end hardware, but image quality may suffer.

What Graphics Cards Support DLSS?

DLSS requires Tensor Cores, specialized hardware in Nvidia’s RTX series graphics cards, to perform the deep learning algorithms needed to upscale lower-resolution images to higher resolutions. Therefore, only Nvidia RTX series graphics cards, including the RTX 20-series and RTX 30-series, support DLSS.

Here is a list of some of the Nvidia graphics cards that support DLSS:

  • GeForce RTX 3090
  • GeForce RTX 3080
  • GeForce RTX 3070
  • GeForce RTX 3060 Ti
  • GeForce RTX 3060
  • GeForce RTX 2080 Ti
  • GeForce RTX 2080 Super
  • GeForce RTX 2080
  • GeForce RTX 2070 Super
  • GeForce RTX 2070
  • GeForce RTX 2060 Super
  • GeForce RTX 2060

Which Games Support DLSS?

Many game developers have implemented DLSS in their titles, and the list of supported games is continually growing. Here are some of the games that support DLSS:

  • Control
  • Cyberpunk 2077
  • Death Stranding
  • Deliver Us The Moon
  • F1 2020
  • Fortnite
  • Marvel’s Avengers
  • Metro Exodus
  • Monster Hunter World
  • Outriders
  • Watch Dogs Legion
  • Wolfenstein: Youngblood

This is not an exhaustive list; new games are always being added to the list of supported DLSS titles. Players can check if their favorite games support DLSS in the game’s graphics settings or by looking at the game’s official website or documentation

List of Games That Support DLSS

Here is an updated list of games that support DLSS:

  • 7 Days to Die
  • Amid Evil
  • Anno 1800
  • Atomic Heart
  • Battlefield V
  • Bright Memory
  • Call of Duty: Black Ops Cold War
  • Call of Duty: Warzone
  • Chernobylite
  • Control
  • Cyberpunk 2077
  • Deliver Us The Moon
  • Enlisted
  • F1 2020
  • Final Fantasy XV
  • Fortnite
  • Ghost runner
  • Into The Radius
  • Justice
  • Marvel’s Avengers

Nvidia DLSS FAQs

1. What Does DLSS Stand For?

Ans: DLSS stands for Deep Learning Super Sampling.

2. What does Nvidia DLSS do?

Ans: This technology allows players to run games at higher resolutions with better performance, which is particularly useful for graphically demanding games. DLSS is exclusive to Nvidia RTX series graphics cards, which have specialized Tensor Cores for performing the deep learning algorithms needed for the upscaling process.

3. What are the Disadvantages of DLSS?

Ans: Here are some of the main disadvantages of DLSS:
* Quality
* Compatibility
* Training
* Limited resolution scaling

4. Should I opt for ray tracing or DLSS?

Ans: A rendering method called ray tracing can produce more realistic lighting and shadows in video games by simulating the behavior of light in real-world situations. Unfortunately, ray tracing requires a lot of processing and can significantly influence speed. You might want to turn on ray tracing in your games if you have a strong GPU and prefer visual integrity over performance.
On the other hand, by upscaling lower-resolution photos to higher resolutions, DLSS can enhance performance while preserving or improving image quality. This technology is beneficial for maintaining high framerates or running graphically demanding games at higher resolutions. Consider adopting DLSS if you value performance over visual fidelity or have a low-end GPU.

Conclusion

In conclusion, Nvidia DLSS (Deep Learning Super Sampling) is a technology that upscales low-resolution photos to higher resolutions while maintaining or improving image quality. While DLSS can offer several advantages, like better performance and image quality, there are also potential drawbacks, including compatibility concerns and quality restrictions.

Ultimately, the choice between DLSS and ray tracing comes down to your priorities and the capabilities of your machine. Ray tracing can provide more realistic lighting and shadows but is computationally expensive. By upscaling low-resolution photos, DLSS can increase efficiency while maintaining image quality. Try both settings and see which works best for you and your game.

Leave a Reply

Your email address will not be published. Required fields are marked *