Design Support Apparatus for Simulation Parameter Optimization
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Solution Overview
Problem
Conventional design support techniques for manufacturing, such as in SRAM design, face challenges with combinational explosion when dealing with numerous design parameter combinations, leading to inefficient numerical calculations and difficulty in determining the accuracy of the Pareto frontier within real-time constraints.
Innovation Solution
A design support apparatus that employs logical expression input, quantifier elimination, sampling point generation, and possible range computation to efficiently determine the relation between design variables, allowing for the visualization of objective functions and design parameters without the need for extensive simulator calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If thorough sampling of design parameter combinations is performed to ensure accuracy of Pareto frontier, then measurement precision is improved, but loss of time increases due to combinational explosion
Solution Approach 1:
The patent segments the design parameter space into multiple regions and performs sampling in a staged manner. First, initial sampling is performed to identify promising regions, then subsequent sampling is concentrated in those regions. This segmentation avoids the need to thoroughly sample the entire parameter space, reducing calculation time while maintaining accuracy in identifying the Pareto frontier.
Solution Approach 2:
The patent performs preliminary sampling and analysis to identify regions of interest before conducting detailed sampling. By performing this preliminary action, the system can focus subsequent computational resources on areas most likely to contain the Pareto frontier, thereby reducing the overall time required while ensuring accurate identification of optimal solutions.
2Measurement precision
If extensive simulator calculations are performed to determine relations between design variables, then measurement precision is improved, but productivity decreases due to large computational requirements
Solution Approach 1:
The patent creates a simplified mathematical model (copy) of the complex simulator calculations. Instead of performing extensive actual simulator calculations, the system uses a pre-established mathematical model that reproduces the essential relationships between design variables and objective functions. This copying approach maintains measurement precision while dramatically improving productivity by avoiding repeated full simulator executions.
Solution Approach 2:
The patent transforms the problem from requiring extensive simulator calculations to using a mathematical model with simplified parameters. By changing the representation from complex simulator-based calculations to a parameterized mathematical model, the system achieves the same measurement precision with significantly reduced computational requirements, thereby improving productivity.
3Measurement precision
If comprehensive sampling is performed to visualize multiple objective functions, then measurement precision is improved, but device complexity increases due to repeated calculations
Solution Approach 1:
The patent replaces complex repeated simulator calculations with a single mathematical model that can be evaluated multiple times without requiring repeated full simulator executions. This copying approach allows comprehensive sampling and visualization of multiple objective functions while reducing the actual computational complexity of the system.
Data Source
AI summary
A design support apparatus includes: a logical expression substitution unit to substitute a part of the logical expression, which includes a function expression of the design variables and a quantifier attached to the design variable, with a substitution variable; a quantifier elimination unit to generate a relational expression including the substitution variable and design variables without the quantifier by eliminating the design variable to which the quantifier is attached from the logical expression; a sampling point generation unit to generate a plurality of sampling points corresponding to the design variables and the substitution variable included in the relational expression; a possible range computation unit to compute, for each of the sampling points, a possible range that the relational expression may take, by calculating values of remaining design variables included in the relational expression based on the relational expression; and a possible range display unit to display the possible range.