On one of the 2 tested Win10 computers manage_numcalc_script.py is dead-slow - unusable.
I traced the issue to the _numcalc_instances() function in manage_numcalc.py.
Specifically on that Windows computer the for p in psutil.process_iter(['name', 'memory_info']): takes about 2,5 minutes to execute and fully loads one CPU core. As this command is called after each NumCalc Instance, it looks like the script is dead.
The issue could be caused by antivirus or some corporate software, but the
workaround in manage_numcalc.py is to change line:
running_instances = _numcalc_instances()
to
running_instances = 7.777 # workaround _numcalc_instances()
This will skip the extremely slow _numcalc_instances() function and fix the performance. What is lost is the possibility to limit CPU core limit (max_instances), but the max_cpu_load is still available (even if it is not very effective).
If more people are affected, please report it here and then the issue may get a permanent fix.
On one of the 2 tested Win10 computers
manage_numcalc_script.pyis dead-slow - unusable.I traced the issue to the
_numcalc_instances()function inmanage_numcalc.py.Specifically on that Windows computer the
for p in psutil.process_iter(['name', 'memory_info']):takes about 2,5 minutes to execute and fully loads one CPU core. As this command is called after each NumCalc Instance, it looks like the script is dead.The issue could be caused by antivirus or some corporate software, but the
workaround in
manage_numcalc.pyis to change line:running_instances = _numcalc_instances()to
running_instances = 7.777 # workaround _numcalc_instances()This will skip the extremely slow _numcalc_instances() function and fix the performance. What is lost is the possibility to limit CPU core limit (max_instances), but the max_cpu_load is still available (even if it is not very effective).
If more people are affected, please report it here and then the issue may get a permanent fix.