Good morning.
My tests on my laptop with windows 11.
I do not know if the dimensions play so much role. I observe that 2019, 2023 give stable results using big heap while is the opposite for 2024, small heap usage and skyrocketed time.
Enjoy!
2019
1 dim:[835,394] time:1100 heap:80468L
2 dim:[835,394] time:1098 heap:80488L
3 dim:[835,394] time:812 heap:80480L
1 dim:[835,394] time:655 heap:80468L
2 dim:[835,394] time:1022 heap:80472L
3 dim:[835,394] time:1009 heap:80468L
1 dim:[835,394] time:899 heap:-682736L
2 dim:[835,394] time:1024 heap:80468L
3 dim:[835,394] time:863 heap:80468L
1 dim:[835,394] time:623 heap:80488L
2 dim:[835,394] time:1059 heap:80480L
3 dim:[835,394] time:801 heap:80468L
1 dim:[835,394] time:729 heap:80472L
2 dim:[835,394] time:1228 heap:80468L
3 dim:[835,394] time:946 heap:-578588L
2023
1 dim:[798,371] time:884 heap:82068L
2 dim:[798,371] time:1474 heap:82068L
3 dim:[798,371] time:1387 heap:82068L
1 dim:[798,371] time:889 heap:82068L
2 dim:[798,371] time:1619 heap:82068L
3 dim:[798,371] time:1443 heap:82068L
1 dim:[798,371] time:834 heap:82068L
2 dim:[798,371] time:1524 heap:82068L
3 dim:[798,371] time:1325 heap:82068L
1 dim:[798,371] time:875 heap:82068L
2 dim:[798,371] time:1642 heap:82068L
3 dim:[798,371] time:1439 heap:82068L
1 dim:[798,371] time:918 heap:82068L
2 dim:[798,371] time:1556 heap:82068L
3 dim:[798,371] time:1477 heap:82068L
2024
1 dim:[1089,388] time:2534 heap:38480L
2 dim:[1089,388] time:6106 heap:38068L
3 dim:[1089,388] time:7502 heap:38068L
1 dim:[1089,388] time:5505 heap:38068L
2 dim:[1089,388] time:14941 heap:38068L
3 dim:[1089,388] time:18172 heap:38096L
1 dim:[1089,388] time:10772 heap:38068L
2 dim:[1089,388] time:24687 heap:38068L
3 dim:[1089,388] time:28194 heap:38096L
1 dim:[1089,388] time:20997 heap:38092L
2 dim:[1089,388] time:34444 heap:38096L
3 dim:[1089,388] time:35325 heap:38068L
1 dim:[1089,388] time:24050 heap:38068L
2 dim:[1089,388] time:41893 heap:38068L
3 dim:[1089,388] time:43437 heap:38068L