The Complexity Report shows the Rent Exponent, Average Fanout, and distribution per type of leaf cells for the top-level design and/or for hierarchical cells. The Rent exponent is the relationship between the number of ports and the number of cells of a netlist partition when recursively partitioning the design with a min-cut algorithm. It is computed with similar algorithms as the ones used by the placer during global placement. Therefore, it can provide a good indication of the challenges seen by the placer, especially when the hierarchy of the design matches well the physical partitions found during global placement.
A design with higher Rent exponent corresponds to a design where the groups of highly connected logic also have strong connectivity with other groups. This usually translates into a higher utilization of global routing resources and an increased routing complexity. The Rent exponent provided in this report is computed on the unplaced and unrouted netlist. After placement, the Rent exponent of the same design can differ as it is based on physical partitions instead of logical partitions.
Report Design Analysis runs in Complexity Mode when you do either of the following:
- Check the Complexity option in the Report Design Analysis dialog box Options tab.
- Execute the
report_design_analysisTcl command with the
The following figure shows the Complexity Report.
The following table shows the typical ranges for the Rent Exponent.
|0.0 to 0.65||This range is low to normal.|
|0.65 to 0.85||This range is high, especially when the total number of instances is above 15,000.|
|Above 0.85||This range is very high, indicating that the design might fail during implementation if the number of instances is also high.|
The following table shows the typical ranges for the Average Fanout.
|Below 4||This range is normal.|
|4 to 5||
This range is high, indicating that placing the design without congestion might be difficult.
|Above 5||This range is very high, indicating that the design might fail during implementation.|
You must treat high Rent exponents and high Average Fanouts for larger modules with higher importance. Smaller modules, especially under 15,000 total instances, can have high Rent exponent and high Average Fanout and still be easy to place and route successfully. Therefore, you must review the Total Instances column along with the Rent exponent and Average Fanout.
-hierarchical_depthoption to refine the analysis to include the lower-level modules.