Partitioning algorithm used when participants are running in parallel. This setting is hidden when only FMU participants are defined.
System Coupling's partitioning algorithms allow for both shared and distributed execution and for the allocation of machines or cores. The default algorithm is generally the best choice, as it allows for each participant to take advantage of all the allocated resources. The other "allocate" algorithms are provided to handle situations where not enough resources are available to run the same machines. The custom algorithm allows you to partition participants in a specialized way not offered by the other algorithms.
Possible values:
SharedAllocateMachines(default value)Participants share both machines and cores.
SharedAllocateCoresParticipants share machines but not cores.
DistributedAllocateMachinesParticipants minimally share cores and machines. (Linux only)
DistributedAllocateCoresParticipants never share cores or machines. (Linux only)
CustomParticipants are assigned machines and cores as specified in the custom partitioning information you provide via the ParticipantPartitioning() command. For details, see Applying Custom Participant Partitioningin the System Coupling User's Guide.
Note:
Parallel processing is not supported for Windows, so selection of a "Distributed Allocate" algorithm for a Windows run will generate an error.
When simultaneous execution of participant solutions is enabled, the explicit application of partitioning is changed as described in Execution of Simultaneous Participant Solutions in the System Coupling User's Guide.
Tip: Shown in the GUI as the Analysis Control | Partitioning Algorithm setting.