Presentation
Automated Validation of Liberty Models
DescriptionSignoff-quality standard cell libraries are critical for successful SoC tape-outs. Even minor inaccuracies in Liberty (.lib) models can lead to late-stage failures in timing, power, IR drop, and noise analysis. Manual QA of Liberty files are error-prone due to their complexity, especially with statistical LVF and CCS waveform data for advanced nodes.
Traditional validation methods are slow, resource-intensive, and often miss subtle inconsistencies. The need for a scalable, automated, and SPICE-accurate validation framework was driven by:
• Increasing complexity of Liberty views
• Growing number of PVT corners and cells
• Demand for early detection of outliers to reduce debug cycles
We present an automated validation framework methodology covering
• Moments-based LVF validation: Reduces false positives from traditional sigma checks.
• STA-like LVF comparison: Uses effective delay/transition metrics for realistic analysis.
• Automated SPICE setup: Supports all arcs, slew/load conditions, and parasitic.
• Insight-driven debug: Visual trend plots accelerate root cause analysis.
Applied to over 1000 cells across 30+ PVT corners, the methodology enables early outlier detection, improves SPICE level correlation, and delivers up to 2× productivity gains in validation and revision analysis. The results demonstrate a scalable approach to achieving consistent, signoff ready Liberty libraries with reduced silicon risk.
Traditional validation methods are slow, resource-intensive, and often miss subtle inconsistencies. The need for a scalable, automated, and SPICE-accurate validation framework was driven by:
• Increasing complexity of Liberty views
• Growing number of PVT corners and cells
• Demand for early detection of outliers to reduce debug cycles
We present an automated validation framework methodology covering
• Moments-based LVF validation: Reduces false positives from traditional sigma checks.
• STA-like LVF comparison: Uses effective delay/transition metrics for realistic analysis.
• Automated SPICE setup: Supports all arcs, slew/load conditions, and parasitic.
• Insight-driven debug: Visual trend plots accelerate root cause analysis.
Applied to over 1000 cells across 30+ PVT corners, the methodology enables early outlier detection, improves SPICE level correlation, and delivers up to 2× productivity gains in validation and revision analysis. The results demonstrate a scalable approach to achieving consistent, signoff ready Liberty libraries with reduced silicon risk.
Event Type
Engineering Presentation
TimeMonday, July 272:45pm - 3:00pm PDT
LocationSeaside Ballroom B