I don't dispute that some applications are hard to parallelize. However, in my day to day work, I've found that parallel operations are often not that complicated to introduce.
The bigger issue is that CPUs are now so fast I find myself blocked by IO far more often than I'm blocked by actual processing.
> From production rendering to playing hundreds of virtual instruments to simulating an iOS app on multiple devices at once, it’s exceedingly capable.
> Increased speed for Logic Pro X, MATLAB, Adobe Photoshop 2020, Autodesk Maya, Wolfram Mathematica Build Time, Final Cut Pro X
> Tasks like animating 3D film assets, compositing 8K scenes and building lifelike gaming environments.
This is the target market - and pretty much everything listed here tends to be multi-threaded. Making multi threaded applications aren't easy, but for high performance tasks all these use-cases have to be multi-threaded where possible or they are just too slow.
I think that people grossly underestimate the amount of processing that can be done on video. Reasonably sized filters, something like deinterlacing, high quality transforms. Swamping a modern CPU in terms of memory access or processing isn't too hard.
Yes, if you just use AOM directly you'll have a hard time saturating the core with work.
However, if you split your video up into scenes and start an AOM instance per scene, it becomes trivial to outperform the 12 core ryzen with a 128 core machine. The main bottleneck becomes memory bandwidth.
This is what the av1an project is doing https://github.com/master-of-zen/Av1an
All that said, you need videos long enough for there to be a benefit here. The Ryzen will still win if you are talking about making 10 second av1 gifs.