PDN RLC Modeling for Power Coupling Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Power delivery networks in silicon devices, such as integrated circuits, are susceptible to voltage ripple and noise due to parasitic capacitance and inductance, causing functional issues and performance degradation, and existing simulation methods are inefficient due to large data file sizes.
Innovation Solution
A system and method for identifying power coupling effects by extracting power structure parameters, generating a reduced complexity PDN model, and testing circuit blocks to identify parasitic coupling using a resistor-inductor-capacitor (RLC) circuit model, reducing computational complexity and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full circuit simulation is performed to identify power coupling effects, then measurement precision is improved, but loss of time increases due to large data file sizes
Solution Approach 1:
The patent segments the power delivery network into multiple power domains based on power structure parameters. Each power domain is simulated separately rather than performing a single large-scale simulation of the entire circuit. This segmentation reduces the computational complexity and data file size for each simulation while maintaining the ability to identify power coupling effects across domain boundaries.
2Measurement precision
If detailed power structure parameters are extracted and simulated, then measurement precision is improved, but use of energy increases due to computational complexity
Solution Approach 1:
By dividing the circuit into multiple smaller power domains, each domain requires less computational resources to simulate. The total energy consumption is reduced because multiple small simulations consume less energy than one large simulation, while still achieving the same level of precision in identifying power coupling effects through the aggregation of domain-level results.
Data Source
AI summary
Systems for identifying power coupling effects that include a circuit, at least one processor, and a memory. The circuit may include a power delivery network (PDN) and a plurality of circuit blocks. The memory may store instructions that, when executed by the at least one processor, cause the at least one processor to perform the following operations: extract power structure parameters of the circuit; generate, based on the parameters, a PDN model, said PDN model including the PDN and the plurality of circuit blocks; test, using the PDN model, the plurality of circuit blocks; and identify, based on the testing, a power coupling effect within the PDN.