PL9 on older computers

@Allan I have been testing 9.02 this morning and got some good and some bad results with
image

My 5900X is happy to be put to sleep and has a large illuminated power switch which flashes when asleep and which immediately powers the machine up when pressed and, more to the point, when woken after sleep the GPU memory has reverted to a low starting point.

So here is the results of runs with 40 copies ([M]aster and 39 VCs) of the second image you supplied.

After various simple adjustments have been made (changing DP3 to XD2s for example)
The memory used is not the highest I have seen while testing with the 5060TI(16GB) but is typical at 8859MB

Straight after a “Sleep”:-

Please note that any changes to the image options, no direct edits but just selecting all images or changing XD2s to DP3 or vice versa etc. were done before PL902 went to “Sleep” (along with the rest of the machine, i.e. 4899MB

@Required My tests with both the GPU benchmark Nikon images with AI selections crudely applied by me and tested as physical images and as one physical image and 39V Cs and Alan’s second image have varied wildly!

Using my 5060TI with 16GB the tests have reached as high as 12778 GB and in none of my tests today have I made a single edit change except to select all images or change the NR. Whatever DxO are doing in PL9 the GPU memory management is all over the place, there are other non-technical terms I could use but I want to be able to go on posting.

My recommendation for those with limited GPU memory is to try using “Sleep” to purge the GPU before an export providing

  1. Set up PL5 ready for export so that all that is needed is the actual export command.
  2. Your machine can reliably be put to sleep and restored
  3. Your machine can be quickly put to sleep and then restored from sleep, I am lucky with the 5900X that the keyboard has a dedicated sleep key and it is conspicuously obvious that the machine is asleep.

PS:- This isn’t going to help with editing issues but the occasional purge of GPU memory might not be a bad thing, unless it takes forever or is not reliable!

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