I’ve read some posts here which compare Raw conversion performance across different computer platforms.
What I seem to have missed is a summary: a few bullet-points which describe the underlying factors that anyone should consider when upgrading to a better-performing system.
What are the most important features for a system doing RAW conversion and general stills editing ?
Which features can we ignore, because they are actually targeted to video professionals ?
Many thanks
This is a user forum, so nobody will list and summarise things.
Common understanding is that you should get a decent video card, specially if you plan to use DeepPrime and DeepPrime XD. One of the threads opened a Google spreadsheet where real world measurements were added by users. Try to find the respective post.
Thank you, I have seen the spreadsheet.
What constitutes a decent video card for this purpose: memory ? cores ? speed ? cost ?
The same questions can be asked of CPU.
Some applications do not take advantage of the latest features, so it might not be prudent to merely “throw money at the problem” and buy the most expensive configuration we can afford… or is it ?
To put it another way, is there a way to prioritize the requirements ? For example, back in the day with Photoshop, the more RAM we had, the better. With insufficient RAM and scratch-disk space, whatever CPU we had was I/O bound. What are the analogous factors here ?
To ask the question a different way: what are the bottlenecks or constraints to efficiency, where spending money will be most effective ?
what is your budget ?
@noname has asked the key question. I would add, that while you can get away with GPUs that are below the minimum specified by DxO, it’s not a good idea. In other words your minimum budget for a GPU has to be the cost of the minimum as specified by DxO. Beyond that, the higher the spec the faster PL will export images using DeepPRIME or DeepPRIME XD noise reduction.
Also bear in mind that the amount you go over the minimum spec should be driven by how important outright speed is to you.
For example, if you edit 10 photos and export them in a batch when done, then speed may be unimportant, as you can go off and do something else while they export.
If, on the other hand, you edit 500 photos in one sitting and want to export them for a client before moving onto the next job, then you’ll want to invest in a lot of power to churn through the exports.
Check measured times and see what system was used.
I recently bought a new computer. Since then I have been trialling new software, such as Topaz and DxO.
Now I realise that I need a decent gpu. Not cheap, I’m looking at GeForce RTX 3050 8gb, which is around £220.
DxO is slow on PureRaw, on 5DS size files it takes around 6 minutes each image, even a 20mp image takes over 3 minutes. Topaz is even slower on Sharpen AI. Nik Efex only takes a few seconds to complete.
But this new software uses a lot of memory.
No doubt this will get worse.
I do wonder if it is all worth it sometimes.
Could you put a link to that spreadsheet, on here, please?
Thanks for the link. Actually I looked on google and did not find it. I have seen that before on a DXO post but did not know that was the one that was being referred to.
Just done a test of 64mp image on DxO PureRaw3 with DeepPrime XD. Not a noisy image.
With selection on Auto, it took 380 secs, changed preference to GPU card only, took 136 seconds.
So the auto selection is not always the best.
So check the preferences and see which is best on your computer.
Strangely estimated time at the start was both 6 minutes.
Careful with interpreting export times when using the same image(s)…as DPL’s cache can make a difference. Exporting one image with the sequence of auto/manual/auto selecting GPU got me times of 10/7/7 seconds respectively - with edits set to NoCorrection + DeepPRIME at its default values.
ETA is wrong in the beginning. After a while, estimated times more closely match what you’ll get.
Well I tried it on different but similar images, times were exactly the same.
So gpu was 3x faster than the the auto default setting which used cpu only.
This has been the same on other images, I did a batch of 14 images and they took around 84 mins. The times are consistent 6 mins on cpu (auto), 2 mins on gpu. Why is auto going to the cpu only setting? Results look identical to me.
Times near the end can wrong as well jumping from 2 mins to only around 10 second’s sometimes. Or saying 10 seconds when it takes over 60 seconds.
In reply to the OP, new AI software uses a lot of GPU vRam, so really you need a decent gpu with at least 8gb of Ram.
I’m now looking a Nvidvia RTX4060 gpu, instead of the RTX3050, it is newer, it is about 60% faster but costs about £50 more, in the system I’m considering.
You probably need a CPU, such as Intel 5i or AMD 5 5600, with 16gb or 32gb
Ram, 1TD SSD.
Thank you !!
I recently really pushed the boat out and changed my 2012 i7-960 (12GB) with unsupported GPU for a Core i9 13900KF + 32GB and RTX 4070 + 12GB. What a difference on using Deep Prime AI, 30 minutes down to under 3 seconds for a Nikon D810 RAW file.
I have a NUC with embedded graphics and Core i9 9th generation mobile (power limited) and that took 4 minutes for the same image. I also tried it on a gaming laptop (i7 + 8GB) with supported graphics card (4GB), vintage 2017 and that took around 65s.
Wow 30 mins, I thought 6 mins was bad. My 5DS files are probably similar to yours.
I can’t go as far as you computer wise. Intel Core i5 12400F with RTX 4060 8 gb is the most I can go to. Actually DxO is not so bad as can batch process. Topaz is worse, some things don’t even work.
My results back up your statement about graphics card and associated memory. The CPU doesn’t count for that much. I started off looking at the RTX 30XX series but thought if I’m not in the market for another PC for 10 years or so what the heck. I did place a limit on spend though so juggled parameters within that limit.
For the record, I purchased a Mac Studio M2 Max with 64GB RAM and 32-core GPU.
The time required to convert a 42MB Sony raw file went from 5 minutes+ on my 2017 iMac to 16 seconds on the Mac Studio. The new machine is around 20X faster. 
Thanks for your helpful discussion.
