Data Type Optimization in Simulink
Data type optimization automatically iterates through various fixed-point configurations to choose the optimal heterogeneous data types while meeting tolerance constraints on the numerical behavior of your system. The optimization seeks to minimize an objective function, such as total bit width or total operator counts, using fixed-point data types for an efficient design.
You can optimize data types using the
fxpopt function at the command line, or by using the
Optimized Fixed-Point Conversion workflow
in the Fixed-Point Tool.
|Fixed-Point Tool||Convert a floating-point model to a fixed-point model|
|Optimize data types of a system|
- Data Type Conversion Overview
Convert data types in your model to fixed point in one of three ways.
- Specify Behavioral Constraints
Use signal tolerances and model verification blocks to verify behavior of fixed-point implementation.
- Optimize Fixed-Point Data Types for a System
Optimize data types in a system based on specified tolerances.
- Optimize the Fixed-Point Data Types of a System Using the Fixed-Point Tool
Use the Fixed-Point Tool to optimize the data types of a system using multiple simulation scenarios.
- Optimize Data Types Using Multiple Simulation Scenarios
Define multiple simulation scenarios for range collection and verification.
- Perform Data Type Optimization with Custom Behavioral Constraints
Use Model Verification blocks to specify custom behavioral constraints for data type optimization with
- Model Configuration Changes Made During Data Type Optimization
Changes made to model configuration parameters during data type optimization with
- Use Design Evolution Manager with the Fixed-Point Tool
Example showing how to manage different design versions while converting a model from floating point to fixed point.
Troubleshoot blocks that are not supported for fixed-point conversion.
Troubleshoot errors thrown during data type optimization using the
Follow best practices and avoid unsupported MATLAB® Function block features.