Neural Super Sampling is here!
Neural Super Sampling (NSS), a next-generation AI-powered upscaling solution from Arm is released for graphics and gaming developers to start experimenting today!
Elevated by machine learning
NSS is designed for real-time performance on future mobile devices with Arm Neural Technology. However, latency depends on implementation factors such as GPU configuration, resolution, and use case. In our Enchanted Castle demo video below, NSS reduced GPU workload by 50 percent. The model rendered at 540p and upscaled to 1080p in just 4ms in sustained performance setup.
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Learn about our NSS Model
Get started with our NSS model today.
If you want to go deeper check out the following resources:
💻 Technical Blog: How Neural Super Sampling works
📃 White Paper: Building for Tomorrow: Try Neural Super Sampling Today with the Unreal Plugin & ML extensions for Vulkan
📲 Technical Blog: Experiment with NSS
How we trained the model
Check out the Neural Graphics Dataset: A collection of reference images and image sequences along with the corresponding motion, depth and other data required to train, validate and test neural super sampling algorithms.
The current version of the dataset includes a limited set of data for Neural Super Sampling to demonstrate how the NSS model development flow works. While this flow does not yet provide a comprehensive dataset for complete model (re)training, stay tuned for future releases of the Neural Graphics Model Gym where Arm will provide tools to capture and convert content for use in model training and retraining.
Get started experimenting with NSS today!
NSS has been integrated into Unreal Engine via two plugins, the NSS Plugin for Unreal® Engine and Unreal® NNE Plugin for ML extensions for Vulkan.
For step-by-step instructions on how to use NSS in Unreal® Engine.See our learning paths:
Quickstart with ML extensions for Vulkan®: ML extensions for Vulkan® Quickstart Guide
Quickstart with Unreal: Neural Super Sampling Quickstart Guide for NSS integration into Unreal Engine
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