Microsoft Eying DirectML as DLSS alternative on Xbox
Much like AMD is eying DirectML as a substitute for DLSS, Microsoft is doing the same thing. And yeah they're actively developing it as part of DirectX. However interesting to learn is that technology is going to make a move to the XBOX as well.
An while writing it I just realized, it's not odd at all, as the new XBOX is powered by RDNA2 AMD Radeon hardware. DLSS has proven to be slowly becoming a success. Especially DLSS v2.0 offers significant performance improvements. NVIDIA however is utilized dedicated hardware or DLSS through the Tensor cores, whereas AMD would need to run it over the compute engine.
DirectML
It seems development is well underway. DirectML is built on top of Direct3D. Microsoft showed the following image as an example of DirectML-based “super-resolution” AI scaling technique with Forza Horizon 3. The comparison shows a frame from the game with DirectML super-resolution (left) and upscaled normal through the bilinear filter (right).
ML Super Sampling (left) and bilinear upsampling (right)
Microsoft apparently plans to bring something similar to Xbox Series X and Series S, which would be especially interesting. And yeah, AMD on their end are looking into using ML for the new Radeon series desktop graphics cards. It will be interesting to see what the performance hit will be and if it outweighs the usage of that compute engine as NVIDIA RTX has hardware dedicated to machine deep learning, while the hardware implementation of RDNA2 does not.
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To be clear, DirectML is a substitute for NGX, not DLSS. DLSS is an application built on top of Nvidia's NGX. Just like whatever AI based upscaler AMD/Microsoft will build will be an application on top of Win/DirectML.
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Thank frack that M$ is stepping up where AMD hasn't yet.
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So better quality at the cost of latency and performance.
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At the cost of performance? Not quite the DLSS alternative.
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Yees please. Looks great.
But we already knew that AI image reconstruction is capable of great quality. Minimizing performance hit is the key issue.
https://creativecoding.soe.ucsc.edu/QW-Net/
" Recently, a combined real-time image reconstruction technique called Deep Learning Super Sampling (DLSS) was introduced, but the details of the underlying network are unknown.
Concurrent to our work, Xiao introduced a reconstruction technique based on U-Net. Using an optimized inference implementation they reconstruct a 1080p image in 18 to 20 ms on a high-end GPU. In comparison, DLSS reconstructs a 4K image in under 2 ms. Both these approaches can reconstruct images at a higher resolution than the input render. "