Run parameters and Decision Optimization environment
Run parameters and the Decision Optimization environment.
Run configuration parameters
When you click the Run Configuration icon next to the Run button in the Model view of the Model Builder, a window opens showing you the currently set parameter values. You can click Add parameter and then choose from the following parameters from the Select Parameters drop-down menu.
||Number||Time limits in milliseconds. You can use this parameter to set a time limit that is smaller than the default limit defined by your subscription.|
||You can use this to define the level of detail provided by engine log. The default
||Number||This parameter specifies the maximum number of cores used to process the job. The value can vary from 1 to the maximum number of cores of the processing instance. If not specified, by default, the job uses all the cores of the processing instance.|
||Number||This parameter specifies the maximum memory in megabytes used to process the job. The value can vary from 512MB to the maximum memory of the processing instance. If not specified, by default value: the job uses all of the instance's available memory.|
If you choose Custom parameter... from the Select Parameters drop-down menu you can add the following advanced parameters.
||can be viewed as Boolean (see Description)||If defined, a job dump (input and outputs) zip file is provided with this name as a job
output attachment. Name can contain placeholder
||String||If defined this generates a zip file according to specific job rules (RFC 1960-based
Filter). It must be used in conjunction with the
(duration>=1000) or (&(duration<1000)(!(solveState.solveStatus=OPTIMAL_SOLUTION))) or (|(solveState.interruptionStatus=OUT_OF_MEMORY)(solveState.failureInfo.type=INFRASTRUCTURE))
|Modeling Assistant only
|Python names for CPLEX and CPO parameters can be entered with the prefixes
ma.cplex.parameters. or ma.cpo.parameters.
Once you have set the run configuration parameters they will remain with those values for all subsequent runs for that scenario. You can set different run configurations for different scenarios.
You can remove set parameters by hovering over the parameter displayed in the Run configuration window and clicking the remove button.
The run configuration parameters are saved together with the model when you select Save as model for deployment from the Scenario panel.
Decision Optimization environment
In the run configuration window you can also see the CPU cores and memory that you have subscribed for. By default all your core and memory are used for each model you run. If you click the pencil icon to edit these, you will open an Edit environment window in your project where you can make change the values and update your environment for your project.
You might, however, want to reduce the CPU cores and memory used for a particular scenario to
enable you to run another scenario simultaneously, using the remainder core and memory. You can thus
set different run configurations for each scenario from the Run configuration window by choosing the
run configuration parameters
oaas.jobMemoryMbytes from the Select Parameters drop-down menu.