Thank you all for replying, there were some good ideas!
So the last two days I spent testing this two systems, to understand how they deal with the load. Turned out classical testing, of starting two machines simultaneously on the same task and see which one finishes first, don't really do justice this days. Especially when you get into equation dual CPU systems.
Digging for hidden potential in both systems I decided to run 2 and 3 parallel Photoscan windows, working at the same time on 6 photos set. Which started to show some very interesting results. You can see from bottom table, time performance on each test.
This graph shows how each system deals with the load during parallel Photoscan tasking. Obviously exponential peaking is a bad thing
While working on the same one task, during conventional testing, systems didn't show much difference in speed and only in cost
. However when you multitasking, you're starting to reach the true Xeon station potential. As it deals with load more efficiently judging from that graph.
Here's some results of Xeon working on 90 photos set where each one is 18mp!
Having that data, its pretty clear that sequential chunk processing is not the most efficient way to work, for those of us who need to process multiple sets of photos. Hereof I would like to request for Parallel chunk processing feature in Photoscan. As from this, all will benefit.
Here's an example.
Sequential processing of 5 sets, 90 photos each:
107 + 107 +107 +107 +107 = 535 min
Parallel processing of 5 sets, 90 photos each:
128 + 128 + 107 = 363 min
And this is 172 hours of saved time, we can spend processing two more sets and walk a dog
Also depending on system potential, it would be cool to be able to set the number of parallel processes Photoscan will do. If sets are not heavy, like 20-35 photos, it can be set to 4 may be even 5. If its heavy, 100 photos and more, could be set to 2.
Would like to hear what you all think, may be you have something to add or see where I'm wrong.
Some screen shots of nice smooth synchronized parallel processing here: