PPA Evaluation
Cross-source consensus on PPA Evaluation from 1 sources and 5 claims.
1 sources · 5 claims
Uses
How it works
Benefits
Risks & contraindications
Highlighted claims
- The reported PPA metrics are congestion, routed wirelength, worst negative slack, total negative slack, and power. — A PPA-Driven 3D-IC Partitioning Selection Framework with Surrogate Models
- Final PPA metrics are expensive because they require full 3D backend implementation. — A PPA-Driven 3D-IC Partitioning Selection Framework with Surrogate Models
- DOPP summarizes PPA quality with an L2 norm over min-max-normalized PPA metrics, where smaller scores are better. — A PPA-Driven 3D-IC Partitioning Selection Framework with Surrogate Models
- DOPP's average relative improvements over Open3DBench covered congestion, routed wirelength, WNS, TNS, and power. — A PPA-Driven 3D-IC Partitioning Selection Framework with Surrogate Models
- Backend PPA evaluation can act as a budget-aware optimization signal rather than only an end-of-flow validation step. — A PPA-Driven 3D-IC Partitioning Selection Framework with Surrogate Models