Variation-Aware Custom IC Design White Paper

Improving PVT and Monte Carlo Analysis for Design Performance and Parametric Yield

Variation has become a critical concern in modern process geometries; managing it properly is key in designing custom circuits with competitive performance, power, and area. This is even becoming even more pronounced as leading-edge designs push into smaller process nodes. Given that local and global process variation, environmental variation, and proximity variation can differ among circuits, we can classify variation design problems into Process-Voltage-Temperature (PVT), Monte Carlo (MC) statistical, high-sigma statistical, or proximity-aware design.

This white paper describes how a flow using design-specific corners manages variation issues in a unified fashion. To enable corner-based design, the key ingredients are corner extraction and design verification tools. This paper describes approaches for PVT, Monte Carlo, high-sigma, and proximity design, and how appropriate technology can make these tools fast, accurate, and scalable. Finally, as an example, this paper focuses on high-sigma problems, demonstrating how Optimal Importance Sampling can provide the accuracy of an extremely large Monte Carlo run in a fraction of the runtime.

Variation-aware design is becoming a requirement for Custom IC design teams including analog RF, I/O, standard cell digital library and memory designers.

Content Overview:

• Variation problems: PVT corners, MC Statistical, High-Sigma Statistical, Proximity
• Design-Specific Corners – Enabling Technologies
• Status Quo Modeling: Plain MC: MC + Density, Manual
• Rare Event Simulation and Optimal Importance Sampling
• Case Study: High Sigma Circuits
• Return On Investment