Dear Mahdi,
You can also check if the -Xmx variable is set and lets SNAP use an ideal amount of RAM:
Some users reported (for large processing clusters) that using 60% of the available RAM (instead of 75%) resulted in faster processing actually (at least reported here).
Generally, I believe this is related to the memory management of larger graphs which makes long processing chains slow, at least this is what is reported here Problems obtaining an interferogram from two product sets and here Coregistrating more than two Sentinel-1 SLC IW products - #19 by mengdahl
Of course, this is makes them quite ineffective, because they don’t save a lot of time.
If you are working on linux you could as well create a shell script which uses gpt and writes intermediate products (memory is then released), such as here: S1_preprocessing.sh (1.0 KB) This is for the preprocessing of a Sentinel-1 product to terrain-corrected Gamma0, but creating an inteferogram should work as well and you can delete intermediate products within the same graph.
Not very elegant and just a work-around.