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Communication with grpc4bmi is quite slow. Often much slower than updating a locally running model. In many workflows this makes users not want to use containerized models (especially for 1D models).
We could speed up their workflows with a new grpc4bmi method update_until_and_get_variables, which:
Takes a time to update until, and the names of variables the user wants to store
The grpc server will update the model, and store the variables
Once the target time is reached, the grpc server will transfer the collected data to the user
As there is a loop running inside the container, this will greatly improve performance.
The text was updated successfully, but these errors were encountered:
Communication with grpc4bmi is quite slow. Often much slower than updating a locally running model. In many workflows this makes users not want to use containerized models (especially for 1D models).
We could speed up their workflows with a new
grpc4bmi
methodupdate_until_and_get_variables
, which:As there is a loop running inside the container, this will greatly improve performance.
The text was updated successfully, but these errors were encountered: