The Neural Processing Unit (NPU) provides integrated AI capabilities and can perform up to 11 TOPS making a total compute performance of 34 TOPS after including 5 TOPS from the CPU and 18 TOPS from the iGPU.
Seems like a strange statement. Is there any software that can leverage this NPU, let alone use the NPU/iGPU/CPU in combination? And any rate, there are definitely ML use cases where your CPU will be busy processing workloads from the ML processes.
For video games? I don’t think the NPUs can run DLSS or FSR. Not to mention the iGPU is going to be struggling.
Video content upscaling is out of the question. My 3080 (240 tensor TOPS and 30 FP32 TFLOPS) takes about 15-25 minutes to upscale ~5-7 min SD content to HD. The CPU can also get hammered a lot since you’re also encoding the output file.
To be fair, I have zero experience with real-time upscaling. I only do archival stuff often with low source quality; DVD, VHSRip, low bitrate 720p videos, older, low bitrate vertical smartphone videos.
Getting good quality upscaled video can be a big pain and even on a beefy computer (5800X, 3080, 64GB RAM) it is nowhere near real-time and more difficult source material can require multiple-trial runs (different model and/or config).
That being said 1080 to 4K does tend to be relatively easier (it helps that 1080 source material is usually of high quality). However, I usually never bother with 1080 to 4K as I find the results to somewhat unimpressive and not worth the effort (compared to say a full on film to 4K transfer like on UHD Bluray).
The article doesn’t really go into any detail, I suspect the result is more cosmetic in nature. This is in contrast to some results I’ve had where it literally looks like magic or like in the movies (the original Bladerunner with the enhance scene).
If you can run “lite real-time upscaling” on the NPU, it is a decent feature and use case (even if I wouldn’t use it).
Seems like a strange statement. Is there any software that can leverage this NPU, let alone use the NPU/iGPU/CPU in combination? And any rate, there are definitely ML use cases where your CPU will be busy processing workloads from the ML processes.
Nothing uses the NPU as of now
Idk, real time upscaling and stuff?
For video games? I don’t think the NPUs can run DLSS or FSR. Not to mention the iGPU is going to be struggling.
Video content upscaling is out of the question. My 3080 (240 tensor TOPS and 30 FP32 TFLOPS) takes about 15-25 minutes to upscale ~5-7 min SD content to HD. The CPU can also get hammered a lot since you’re also encoding the output file.
Not sd to hd. But even my Nvidia shield can do some real time ai upscaling
I’m not an expert on the matter, but I’m sure there’s plenty of usecases
https://www.talkandroid.com/guides/nvidia-shield-tv-ai-upscaling/
To be fair, I have zero experience with real-time upscaling. I only do archival stuff often with low source quality; DVD, VHSRip, low bitrate 720p videos, older, low bitrate vertical smartphone videos.
Getting good quality upscaled video can be a big pain and even on a beefy computer (5800X, 3080, 64GB RAM) it is nowhere near real-time and more difficult source material can require multiple-trial runs (different model and/or config).
That being said 1080 to 4K does tend to be relatively easier (it helps that 1080 source material is usually of high quality). However, I usually never bother with 1080 to 4K as I find the results to somewhat unimpressive and not worth the effort (compared to say a full on film to 4K transfer like on UHD Bluray).
The article doesn’t really go into any detail, I suspect the result is more cosmetic in nature. This is in contrast to some results I’ve had where it literally looks like magic or like in the movies (the original Bladerunner with the enhance scene).
If you can run “lite real-time upscaling” on the NPU, it is a decent feature and use case (even if I wouldn’t use it).