Title
Finding placement-relevant clusters with fast modularity-based clustering.
Abstract
In advanced technology nodes, IC implementation faces increasing design complexity as well as ever-more demanding design schedule requirements. This raises the need for new decomposition approaches that can help reduce problem complexity, in conjunction with new predictive methodologies that can help avoid bottlenecks and loops in the physical implementation flow. Notably, with modern design methodologies it would be very valuable to better predict final placement of the gate-level netlist: this would enable more accurate early assessment of performance, congestion and floorplan viability in the SOC floorplanning/RTL planning stages of design. In this work, we study a new criterion for the classic challenge of VLSI netlist clustering: how well netlist clusters "stay together" through final implementation. We propose use of several evaluators of this criterion. We also explore the use of modularity-driven clustering to identify natural clusters in a given graph without the tuning of parameters and size balance constraints typically required by VLSI CAD partitioning methods. We find that the netlist hypergraph-to-graph mapping can significantly affect quality of results, and we experimentally identify an effective recipe for weighting that also comprehends topological proximity to I/Os. Further, we empirically demonstrate that modularity-based clustering achieves better correlation to actual netlist placements than traditional VLSI CAD methods (our method is also 4X faster than use of hMetis for our largest testcases). Finally, we show a potential flow with fast "blob placement" of clusters to evaluate netlist and floorplan viability in early design stages; this flow can predict gate-level placement of 370K cells in 200 seconds on a single core.
Year
DOI
Venue
2019
10.1145/3287624.3287676
ASP-DAC
Field
DocType
Citations 
Netlist,Single-core,Weighting,Computer science,Real-time computing,Physical design,Cluster analysis,Computer engineering,Very-large-scale integration,Modularity,Floorplan
Conference
0
PageRank 
References 
Authors
0.34
20
4
Name
Order
Citations
PageRank
Mateus Fogaça1204.00
Andrew B. Kahng27582859.06
Ricardo A. L. Reis321748.75
Lutong Wang4287.52