And how does your project look like? It is drone photogrammetry of large area, or ground photogrammetry of some building, or...?
It is underwater photogrammetry of a 3D object. The area is about 100m x 20m. Smaller projects that are ~20,000 images or less tend to get through that step relatively quickly.
I feel your pain.
My little uw scan of one of our dive sites took 5 days to process on my old Thinkpad.
What camera are you using?
I only had GoPro 7 cameras, but stuck 2 or 3 on a long pole (see my profile pic), to just get the scanning done 2-3 times faster.
What settings are you aligning with?
Using my gopro's uw images, it's just a fact that they're not as sharp as those from cameras on the top-side... We've got shit vis and dim light to deal with.
This meant that i don't see any benefit from using anything but Low for Aligning. I use Low, 20,000 2,000. This speeds up the run times insanely! And i don't think it matters how many points there are, more the quality of them... And uw, we just can't compete with the drone photos! I'd test Low 20,000 2,000 vs. your existing settings... To see if there's much difference. I'd guess not.
And again, as we're uw, we don't have any georeference data, no GPS data... So i think MS has to compare each photo with every other photo... This leads to exponential processing time increases as the number of photos increases...
I've got 40,000 images of my Manta Point dive site (see it in my signiture).... But to make it manageable, i landed up processing each dive individually, aligning it, then running the 'Reduce Overlap' command, set to 9. This knocked out a third of the photos. The nature of using gopros with 2 second timelapse intervals means i always have much more overlap going forward, as i can't swim fast enough! and gopros can't do 3 second intervals. damn. Then i took each of the pared down dives, using the reduced number of photos, and then aligned them all together, from scratch. 4 days, lol. And i then did another Reduce overlap. And yes, i was learning as i was doing this, so my tracks around the dive site are all over the show, not wonderfully parallel 'mowing the lawn' tracks like metashape would want. Only after that do i create the model... Which only took a day.
Aligning uw images without any georef data seems to be the hardest part for metashape. The rest is easy.
I recently tried Bzuco's tip of running multiple local nodes. This, for the alignment job, is much, much, much faster!!! When i redid my big alignment, admitedly also with an aditional eGPU, but it reduced my 4 day alignment down to 1 day.
I'd say that you should definitely do what Bzuco suggested. Start up multiple nodes on each physical machine.
On each of your 2 machines, run a subset of you data as a quicker benchmark. Run it with one node, then 2, then 3, then 4, etc... It seems to be the GPU that limits how many you can run. I had a 1660 that worked the fastest with 8 nodes, but my newer 5700 XT only liked 6. This is for the alignment job. For building the model, i can only run 2. So i just pause the ones i don't need. Building the model chews up a lot of VRAM, so you must only run as many nodes as to keep it from maxing out the VRAM, and swapping to RAM, which spanners the processing speed. When you're testing this, it takes a bit of time before it eventually gets to the VRAM dependant task, but if you see it swapping, just kill one of the extra nodes, and the server will just do that failed 'worker' at the end, completing the job just fine. So what GPUs do you have??? How much VRAM do they have?
So, maybe you'll have 8 nodes on your i9, and 12 nodes on you Threadripper... So 20 nodes showing up in the Network Monitor. And limit the i9 down to 2 after aligning, and the TR down to 3, perhaps...
Oh, and then i guess you'd want to pause the 'slower' computer's nodes when it's doing the single threaded stuff... Now it's getting complicated!
Hopefully Metashape will get some AI stuff to know which node is fastest to push this single core stuff to... and to dynamically adjust the number of local nodes to suit each workstation's hardware...
So, try Low 20,000 2,000 and try multiple nodes per computer.