PPA Prediction Methodology Using Polynomial Regression
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Solution Overview
Problem
Conventional methods for predicting the performance, power, and area (PPA) of integrated circuits under new processes or technologies are time-consuming and costly, and fail to effectively demonstrate the benefits of advanced technologies due to their reliance on outdated formats that do not account for complex relationships between speed and core area.
Innovation Solution
A design flow methodology that includes stages such as RTL coding, layout placement, synthesis, automated placement and routing, PVT corners optimization, and prediction modeling using polynomial regression to estimate PPA across different technologies, allowing for the evaluation of next-generation technologies before adoption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional prediction methods are used for PPA estimation, then manufacturing cost and time are reduced, but prediction accuracy and ability to demonstrate technology benefits deteriorate
Solution Approach 1:
The patent transforms the prediction approach by changing the parameter representation from traditional separate speed and area metrics to a unified power-speed relationship model. This parameter transformation enables more accurate technology benefit demonstration while maintaining computational efficiency through polynomial regression analysis of power versus speed data points.
Solution Approach 2:
The patent replaces conventional manual or simulation-based PPA prediction methods with an automated mathematical modeling system. By substituting complex simulation processes with polynomial regression analysis, the system achieves both high prediction accuracy and computational speed, resolving the contradiction between precision and time consumption.
2Measurement precision
If detailed simulation and analysis are performed for each technology evaluation, then prediction accuracy improves, but manufacturing cost and complexity increase
Solution Approach 1:
The patent creates a simplified mathematical model (polynomial regression) that copies the essential behavior of complex semiconductor technology processes. This model captures the relationship between power, speed, and area without requiring full-scale simulations, thereby maintaining evaluation accuracy while dramatically reducing process complexity and computational resources needed.
3Adaptability or versatility
If traditional PPA formats are used for prediction, then compatibility with existing systems is maintained, but ability to demonstrate advanced technology benefits deteriorates
Solution Approach 1:
The patent introduces a dynamic evaluation framework that adapts to different technology nodes and process conditions. The polynomial regression model can be dynamically adjusted to capture technology-specific characteristics, enabling versatile demonstration of advanced technology benefits while maintaining ease of implementation through a unified mathematical approach that works across different semiconductor processes.
Data Source
AI summary
A computer-implemented method includes: placing and routing design elements in a simulation environment; applying one or more simulation conditions to the design elements; obtaining a first set of data based on the one or more simulation conditions, and a first relationship between the first set of data; obtaining a prediction model based on the first relationship; and predicting a new set of data using the prediction model.