![]() Again I don’t find the editing experience under Rosetta particularly good in comparison to my Intel Macs, with small delays and micro-stutter as well those memory leak issues so I don’t recommend moving to M1 architecture for PhotoLab at all, pushing those of us without Catalina/Big Sur/Monterey Macs to upgrade to either a poor user experience or to Intel Macs which will soon be made obsolete.Īll the more reason for DxO not to have cut off Mojave before its time. This suggests that for PhotoLab export it doesn’t make much difference which M1 Mac one chooses (M1, M1 Pro, M1 Max). ![]() ![]() That is about 3x faster so the M1 35s result looks reasonable. Just dug up the previous test I ran on 61 D850/D810 images in a real set on an M1 Mac Mini with 8GB memory. When I tested on my own files, there was a huge difference with PhotoLab 5 on an M1 Mac Mini vs PhotoLab 4. I don’t have a plain M1 here any more to test against. I wonder if the M1 numbers on PhotoLab 5 (almost as good at 35s) hold up to scrutiny. In any case, the M1 Pro does get these good numbers, which I would have expected from the M1 Max but not the M1 Pro. My Radeon VII with AMD hardware acceleration enabled (Apple disables it by default, one has to add OpenCore to get it) did outperform the M1 Pro (5 or 6 sec per image with full set of adjustments including DeepPrime) but I don’t have it hooked up right now. This is half the time of the Radeon 5500XT in the charts and faster or competitive with some of the most powerful GPU’s in existence. The main reason I did these tests right now was that there was a result in for the M1 Pro from forum name 4 which I couldn’t believe, 31s while there is a conflicting result of 77s for the same M1 Pro 10/16 configuration. Spotify playback got choppy while exporting and typing slowed down (nothing like as bad as the base M1 Mac Mini with 8/8 configuration though). Memory for PhotoLab 5 is at 10.5 GB (would be about 4 GB on an Intel Mac). Great export times don’t prevent PhotoLab 5 from misbehaving on an M1 Pro Mac. These times are quite extraordinary as my MBP is now overloaded (didn’t close many apps before starting up PhotoLab 5 as I didn’t feel like restarting all my other work) with memory pressure of 63 and 9 GB of swap and I’m tabbing back into my browser to keep working during the testing (which is the other application using the most memory). With another more intensive set of corrections but no local corrections, processing jumped to 45s. With my default set of corrections for D850 files (Leica M9 colour, lens sharpening, auto-horizon, auto-crop), the process time jumped to 36s. With just DeepPrime turned on at 40, the five images processed in 32s. I’ve just run the D850 test with PhotoLab 5.1.1 on macOS 12.1 on a MBP 14 M1 Pro 10/16 16GB memory. Settings for image correction make a big difference. ![]() I imagine these settings would make more difference on larger exports. I updated the spreadsheet with my results in PL5 along with quite a variety of different settings added as notes. Now I’ve had chance to run some tests, confirm my hypothesis, and get some rough numbers. I expected something along these lines to happen in my testing, as I suspected my GPU wasn’t being used to its full potential before. If one is faster at doing its parts of the process than the other, it’s going to spend some time idle, either waiting for the other one to provide it with more data, or waiting for the other to be ready to process the next piece of data it needs to give it. The DeepPRIME export process will be like a production line, with images in progress being passed back and forth between the CPU and the GPU in the background. are all part of the export process as well, and even with OpenCL GPU assistance enabled for processing, the CPU still has some work to do. Colour and exposure adjustments, sharpening, compressing and exporting the JPEG etc. The traditionally slower parts of the DeepPRIME noise reduction process are definitely offloaded to the GPU wherever possible, but for all I know, some parts of the process may not lend themselves well to GPU processing, so may still involve some CPU work.Įven if the vast majority of the DeepPRIME noise reduction process is now GPU accelerated, exporting an image, involves more than just DeepPRIME noise reduction. In response to your question, the GPU accelerated parts of the process should take the same time to process, per image, but not all of the work done during an image export is done on the GPU. Sorry, I completely missed this post in the thread - I think I must have skipped over it, as there was a delay between my post being made (in response to the post above yours) and it being approved by moderators and appearing below yours.
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