bevy/release-content/release-notes/dlss.md

title	authors	pull_requests
Deep Learning Super Sampling (DLSS)	@JMS55	19817 19864

For users with NVIDIA RTX GPUs, Bevy now offers yet another form of anti-aliasing: DLSS.

Try it out by running Bevy's anti_aliasing example: cargo run --example anti_aliasing --features dlss --release (after performing setup from https://github.com/JMS55/dlss_wgpu).

Compared to Bevy's built-in TAA, DLSS:

• Is much higher quality
• Supports upscaling in addition to anti-aliasing, leading to much cheaper render times, particularly when used with GPU-heavy features like Bevy Solari
• Requires a NVIDIA RTX GPU
• Requires running via the Vulkan backend on Windows/Linux (no macOS, web, or mobile support)

To use DLSS in your app:

• See https://github.com/JMS55/dlss_wgpu for licensing requirements and setup instructions
• Enable Bevy's dlss feature
• Insert the DlssProjectId resource before DefaultPlugins when setting up your app
• Add the Dlss component to your camera entity, optionally setting a specific DlssPerfQualityMode (defaults to Auto)
• Optionally add sharpening via ContrastAdaptiveSharpening

Other temporal upscalers like AMD's FidelityFX™ Super Resolution (FSR), Intel's Xe Super Sampling XeSS (XeSS), and Apple's MTLFXTemporalScaler are not integrated in this release. However they all use similiar APIs, and would not be a challenge to integrate in future releases.

Support for other swapchain-related features like frame interpolation/extrapolation or latency redunction are not currently planned, but support for DLSS Ray Reconstruction for use in Bevy Solari is planned for a future release.

Special thanks to @cwfitzgerald for helping with the wgpu backend interop APIs.