Parasitic extraction in EDA: what it is and why it matters

Parasitic extraction (PEX) in electronic design automation (EDA) calculates parasitic effects — such as capacitances, resistances, and inductance — within integrated circuits (ICs). Parasitics are introduced during the physical manufacturing process in semiconductor foundries, affecting both IC devices and their interconnects (Figure 1).

Figure 1. Interconnect parasitic capacitance between adjacent metal layers and within the same layer. (Image: Synopsys)

This article explores the three primary categories of parasitic effects, compares field solver and rule-based engines for accurate PEX, and discusses how systems designers use advanced EDA tools to address parasitic challenges in system-on-chip (SoC) and chiplet designs at advanced nodes.

Understanding FEOL, MEOL, and BEOL

EDA engineers rely on PEX to develop accurate analog models of ICs. These models enable detailed simulations that emulate real-world digital and analog circuit responses for timing analysis, power analysis, and signal integrity. The importance of PEX has increased with the adoption of lower process nodes, advanced integration methods, and die stacking.

Unchecked parasitic elements can significantly impact monolithic SoC and chiplet performance, causing signal delay, power loss, and signal crosstalk. By evaluating parasitics (Figure 2), designers can optimize signal speed, reduce power consumption, and identify reliability issues like electromigration, thermal hotspots, and timing violations.

Figure 2. The Cadence Quantus Extraction Solution identifies parasitics, showing resistances and capacitances between interconnects and nodes. (**Image:** Cadence)

EDA designers group parasitic elements in PEX into three categories:

Front-end of the Line (FEOL): Describes parasitic elements formed during the initial stages of IC fabrication, when components like transistors, capacitors, and resistors are patterned in the semiconductor substrate. FEOL parasitics generally manifest as gate stack breakdown, stress-induced leakage, and hot carrier stress in transistors. FEOL reliability testing focuses on bias temperature instability, which can lead to threshold voltage shifts over a circuit’s lifespan.
Middle-end of the Line (MEOL): Analyzes parasitics linked to contacts on semiconductor devices. These parasitics, particularly capacitances, occur in the interconnect regions near devices and aren’t covered by standard device models such as the Berkeley Short-channel IGFET Model (BSIM). MEOL parasitics can significantly impact device performance, particularly in advanced nodes using Fin Field-Effect Transistor (FinFET) These parasitics span gate-to-via coupling, gate-to-metal coupling, and fringing capacitances between metal layers and device structures.
Back-end of the Line (BEOL): Assesses parasitics related to interconnect layers formed during metallization. These parasitics encompass electromigration, stress migration, and time-dependent dielectric breakdown within interconnect structures. As process nodes advance, more compact interconnect architectures lead to higher resistance-capacitance (RC) delays, significantly impacting chip performance.

Field solver vs. rule-based engines

EDA engineers use field solver engines, rule-based engines, or a combination of both for accurate parasitic extraction. Field solvers calculate parasitic resistance (R), capacitance (C), inductance (L), or mutual inductance (K) by solving Maxwell’s equations. Often called 3D extraction, this method provides high accuracy by analyzing electric fields in three dimensions, making it the “gold standard” for PEX.

While field solvers efficiently analyze complex geometries without relying on pre-existing models, they require substantial processing power and are not typically used for full-chip extraction.
Field solvers use algorithms such as the finite difference method (FDM), finite element method (FEM), and method of moments, each offering trade-offs between accuracy and computation time. Notably, recent advances in graphics processing unit (GPU) acceleration, particularly GPU-based fast random walk algorithms for 3D field solving, have optimized performance. These improvements allow for a broader application of field solver accuracy in full-chip extraction while keeping runtime within practical limits.

Rule-based extraction uses lookup tables or equations derived from process specifications to calculate parasitics, typically focusing on resistance (R) and capacitance (C). Also referred to as 2D or 2.5D extraction, this method supports full-chip analysis and offers faster processing times than field solvers. While rule-based extraction is effective when interconnect delay is the primary concern, it may miss complex configurations due to its reliance on predefined models.

Some EDA tools combine field solver and rule-based methodologies, enabling field solver accuracy for critical components while maintaining the speed of rule-based extraction for broader areas of the design.

Overcoming PEX challenges in SoC and chiplet designs at advanced nodes

The growing complexity of monolithic SoCs, chiplets, and 3DIC design techniques presents significant parasitic extraction (PEX) challenges for EDA engineers. As device dimensions shrink and circuit speeds increase in deep sub-micron technologies, interconnect parasitics significantly impact circuit performance, leading to higher resistance-capacitance (RC) delays, greater interconnect resistance, and lateral line coupling that degrades signal integrity.

FinFETs amplify parasitic interactions between neighboring geometries and introduce complexity through device-width quantization (Figure 3). Similarly, 3nm gate-all-around field-effect transistors (GAAFETs) add complexity due to intricate interactions and reduced dimensions. Traditional rule-based methods can’t capture the variations in these 3D structures, so field solvers are required for accurate parasitic extraction. Advanced fabrication variations, such as multi-patterning shifts and systematic deviations, significantly affect parasitic elements like resistances and coupling capacitances.

Figure 3. FinFET parasitic capacitance interactions illustrate the coupling between the gate, source, and interconnect layers. (**Image:** Siemens)

EDA engineers use advanced PEX tools with a multi-corner approach to address these challenges. They analyze best, nominal, and worst-case scenarios to ensure designs function under varying conditions. These tools account for metal fill effects on signal nets and use automated reduction techniques to manage netlist sizes. Additionally, they incorporate electromigration and IR (voltage drop) parameters for comprehensive reliability analysis, ensuring the final design is optimized for performance and reliability.

Conclusion

Introduced during the manufacturing process in semiconductor foundries, parasitics affect both IC devices and their interconnects. Unchecked parasitic elements can significantly impact monolithic SoC and chiplet performance, causing signal delay, power loss, and signal crosstalk. To mitigate FEOL, MEOL, and BEOL parasitics, system designers use advanced PEX tools that integrate field solver and rule-based engines. These tools calculate and reduce parasitic effects within ICs, including capacitance, resistance, and inductance.

References

What is Parasitic Extraction?, Synopsys
What is Parasitic Extraction?, Cadence
Virtuosity: Custom IC Design Flow/Methodology – Circuit Physical Verification & Parasitic Extraction, Cadence
Mastering Parasitic Extraction at the 3 nm Process Node, Siemens
Knowledge Center: Backend-of-the-line (BEOL), Semiconductor Engineering
Do You Really Understand The Importance Of Parasitic Extraction In Chip Designs?, Semiconductor Engineering
When Front-End-of-Line and Back-End-of-Line Reliability Meet, Semiconductor Digest
Parasitic Extraction Must Solve Advanced Node Issues, EDN