Waveform Edge Timing Variation Under Simultaneous Switching Noise
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Solution Overview
Problem
Designers face challenges in accurately and efficiently predicting simultaneous switching noise (SSN) in integrated circuits and IC packages due to complex system-level models requiring expertise and time-consuming simulations, making it difficult to optimize I/O buffer assignments within design constraints without increasing costs.
Innovation Solution
A method and system for determining timing variations in transitioning waveforms under SSN conditions, involving calculations of amplitude values related to inductive crosstalk and power distribution network noise, with pre-calculated constants derived from physical measurements, to analyze the impact of mutual inductive relationships and provide quick, accurate predictions of timing variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If system-level SPICE-like models are used to anticipate SSN, then measurement precision is improved, but time consumption increases significantly
Solution Approach 1:
The patent segments the complex system-level SSN analysis into distinct components: mutual inductive coupling effects and PDN impedance effects. Each component is analyzed separately using simplified models, allowing accurate predictions without requiring time-consuming full-system simulations. The mutual inductance between aggressor and victim pins is calculated independently, and the PDN noise is computed separately, then combined to obtain the total SSN effect.
Solution Approach 2:
The patent extracts the essential SSN mechanisms from the complex system-level model, focusing on the two primary factors (mutual inductive coupling and PDN impedance) that contribute to SSN. By taking out only the critical elements needed for accurate SSN prediction and eliminating unnecessary system-level complexity, the method achieves both accuracy and efficiency.
2Object-affected harmful factors
If designers increase ground pins ratio to minimize mutual inductive coupling, then SSN is reduced, but I/O buffer density decreases
Solution Approach 1:
The patent changes the approach from modifying physical layout parameters (ground pin ratio) to adjusting electrical parameters (buffer assignment, switching patterns). By using computational methods to optimize buffer assignment and predict SSN under different configurations, designers can reduce mutual inductive coupling effects without sacrificing I/O buffer density through physical layout changes.
3Object-affected harmful factors
If on-die capacitance and decoupling capacitors are added to improve PDN performance, then SSN is reduced, but manufacturing cost increases
Solution Approach 1:
The patent enables designers to perform their own SSN analysis and optimization using simplified computational models, eliminating the need for expensive additional capacitance additions. By providing a self-service analysis tool that accurately predicts SSN and identifies optimization opportunities in buffer assignment and configuration, the method reduces PDN noise effects without requiring costly hardware modifications.
4Measurement precision
If comprehensive SSN analysis is performed using existing tools, then accuracy is improved, but design cycle time increases
Solution Approach 1:
The patent performs preliminary characterization of mutual inductance and PDN impedance parameters before the main SSN analysis. By pre-calculating these fundamental parameters and storing them for reuse, the method eliminates the need to recompute them during each design iteration, significantly reducing the time required for comprehensive SSN analysis while maintaining accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables comprehensive SSN analysis in a short design cycle, providing accurate timing information and voltage amplitude, overcoming inefficiencies in existing tools by breaking down the analysis into manageable blocks and correlating well with bench measurements, thus optimizing pin placement and ensuring timing margins.
Implementation Method 1
the mutual inductive coupling among switching input/output (I/O) buffers
Implementation Method 2
the impedance profile of a power distribution network (PDN)
Data Source
AI summary
A computer implemented method for determining a timing variation for an edge of a waveform under simultaneous switching noise (SSN) conditions is provided. The method includes characterizing an impact of mutual inductive relationships on a pin while the pin is at a quiet state and characterizing a signal edge applied to the pin. The signal edge can be characterized by the slew rate in one embodiment. A voltage change related to a curve characterizing the impact of mutual inductive relationships is identified and the voltage change is applied to a curve characterizing an impact of SSN on the signal edge. The method includes calculating a timing variation correlated to the voltage change applied to the curve characterizing the impact of SSN on the signal edge and presenting the calculated timing variation.