
Partitioning the grid for parallel processing has three major goals:
Balancing the partitions (equalizing the number of cells) ensures that each processor has an equal load and that the partitions will be ready to communicate at about the same time. Since communication between partitions can be a relatively timeconsuming process, minimizing the number of interfaces can reduce the time associated with this data interchange. Minimizing the number of partition neighbors reduces the chances for network and routing contentions. In addition, minimizing partition neighbors is important on machines where the cost of initiating message passing is expensive compared to the cost of sending longer messages. This is especially true for workstations connected in a network.
The partitioning schemes in FLUENT use bisection algorithms to create the partitions, but unlike other schemes which require the number of partitions to be a factor of two, these schemes have no limitations on the number of partitions. For each available processor, you will create the same number of partitions (i.e., the total number of partitions will be an integral multiple of the number of processors).
Bisection Methods
The grid is partitioned using a bisection algorithm. The selected algorithm is applied to the parent domain, and then recursively applied to the child subdomains. For example, to divide the grid into four partitions, the solver will bisect the entire (parent) domain into two child domains, and then repeat the bisection for each of the child domains, yielding four partitions in total. To divide the grid into three partitions, the solver will "bisect'' the parent domain to create two partitionsone approximately twice as large as the otherand then bisect the larger child domain again to create three partitions in total.
The grid can be partitioned using one of the algorithms listed below. The most efficient choice is problemdependent, so you can try different methods until you find the one that is best for your problem. See Section 31.5.4 for recommended partitioning strategies.

Note that when using the socket version (
pnet), the METIS partitioner is not available. In this case, METIS partitioning can be obtained using the partition filter, as described below.


If you create nonconformal interfaces, and generate virtual polygonal faces, your METIS partition can cross nonconformal interfaces by using the connectivity of the virtual polygonal faces. This improves load balancing for the parallel solver and minimizes communication by decreasing the number of partition interface cells.

This is the default bisection method in FLUENT.
Optimizations
Additional optimizations can be applied to improve the quality of the grid partitions. The heuristic of bisecting perpendicular to the direction of longest domain extent is not always the best choice for creating the smallest interface boundary. A "pretesting'' operation (see Section 31.5.5) can be applied to automatically choose the best direction before partitioning. In addition, the following iterative optimization schemes exist:
In general, the Smooth and Merge schemes are relatively inexpensive optimization tools.
Pretesting
If you choose the Principal Axes or Cartesian Axes method, you can improve the bisection by testing different directions before performing the actual bisection. If you choose not to use pretesting (the default), FLUENT will perform the bisection perpendicular to the direction of longest domain extent.
If pretesting is enabled, it will occur automatically when you click the Partition button in the Partition Grid panel, or when you read in the grid if you are using automatic partitioning. The bisection algorithm will test all coordinate directions and choose the one which yields the fewest partition interfaces for the final bisection.
Note that using pretesting will increase the time required for partitioning. For 2D problems partitioning will take 3 times as long as without pretesting, and for 3D problems it will take 4 times as long.
Using the Partition Filter
As noted above, you can use the METIS partitioning method through a filter in addition to within the Auto Partition Grid and Partition Grid panels. To perform METIS partitioning on an unpartitioned grid, use the File/Import/Partition/Metis... menu item.
File Import Partition Metis...
FLUENT will use the METIS partitioner to partition the grid, and then read the partitioned grid into the solver. The number of partitions will be equal to the number of processes. You can then proceed with the model definition and solution.

Direct import to the parallel solver through the partition filter requires that the host machine has enough memory to run the filter for the specified grid. If not, you will need to run the filter on a machine that does have enough memory. You can either start the parallel solver on the machine with enough memory and repeat the process described above, or run the filter manually on the new machine and then read the partitioned grid into the parallel solver on the host machine.

To manually partition a grid using the partition filter, enter the following command:
where input_filename is the filename for the grid to be partitioned, partition_count is the number of partitions desired, and output_filename is the filename for the partitioned grid. You can then read the partitioned grid into the solver (using the standard File/Read/Case... menu item) and proceed with the model definition and solution.
When the File/Import/Partition/Metis... menu item is used to import an unpartitioned grid into the parallel solver, the METIS partitioner partitions the entire grid. You may also partition each cell zone individually, using the File/Import/Partition/Metis Zone... menu item.
File Import Partition Metis Zone...
This method can be useful for balancing the work load. For example, if a case has a fluid zone and a solid zone, the computation in the fluid zone is more expensive than in the solid zone, so partitioning each zone individually will result in a more balanced work load.