You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I am using MapdlPool and the command run_batch.
The code is launching properly and the pool is created.
Randomly, the computation fails and I receive the following error
%-------------------------------------
raise MapdlExitedError(
ansys.mapdl.core.errors.MapdlExitedError: MAPDL server connection terminated with the following error
<_MultiThreadedRendezvous of RPC that terminated with:
status = StatusCode.UNAVAILABLE
details = "Connection reset"
debug_error_string = "UNKNOWN:Error received from peer ipv4:.... {grpc_message:"Connection reset", grpc_status:14, created_time:"......"}"
%-------------------------------------
In some cases the mapdl session reboots and the computation continues (although it takes some time for the rebooting)
In other cases, I get
%-------------------------------------
PyMAPDL is taking longer than expected to connect to an MAPDL session.
Checking if there are any available licenses...
%-------------------------------------
and the computation stops completely.
Do you know how to prevent such issues?
I have tried running the pool with a lower number of instances as well. To no avail.
I am using MapdlPool and the command run_batch.
The code is launching properly and the pool is created.
Randomly, the computation fails and I receive the following error
%-------------------------------------
raise MapdlExitedError(
ansys.mapdl.core.errors.MapdlExitedError: MAPDL server connection terminated with the following error
<_MultiThreadedRendezvous of RPC that terminated with:
status = StatusCode.UNAVAILABLE
details = "Connection reset"
debug_error_string = "UNKNOWN:Error received from peer ipv4:.... {grpc_message:"Connection reset", grpc_status:14, created_time:"......"}"
%-------------------------------------
In some cases the mapdl session reboots and the computation continues (although it takes some time for the rebooting)
In other cases, I get
%-------------------------------------
PyMAPDL is taking longer than expected to connect to an MAPDL session.
Checking if there are any available licenses...
%-------------------------------------
and the computation stops completely.
Do you know how to prevent such issues?
I have tried running the pool with a lower number of instances as well. To no avail.
Community Forum: https://discuss.ansys.com/discussion/4497/mapdl-pool-run-batch-error
The text was updated successfully, but these errors were encountered: