DOPP applies surrogate models to select 3D-IC partitioning candidates that optimize true PPA, matching exhaustive-search quality with substantially lower evaluation cost across eight designs.
TP-GNN: A graph neural network framework for tier partitioning in monolithic 3D ICs
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A PPA-Driven 3D-IC Partitioning Selection Framework with Surrogate Models
DOPP applies surrogate models to select 3D-IC partitioning candidates that optimize true PPA, matching exhaustive-search quality with substantially lower evaluation cost across eight designs.