If you're dealing with limited memory resources in embedded systems and the total size of global variables is a concern during code generation from Simulink, there are several strategies you can use to reduce the memory footprint. Here are some tips to help you minimize the size of global variables:
- Reduce Data Types Size: Use smaller data types (e.g., uint8, int16) instead of larger ones (e.g., double) when appropriate. Choose the smallest data type that can represent your data accurately.
- Use Local Variables: Minimize the use of global variables. Whenever possible, use local variables within functions or blocks. Local variables have a smaller memory footprint because they only exist within the scope of the function or block.
- Optimize Memory Usage in Simulink Blocks:
- Use fixed-point data types when suitable, as they can reduce the memory required compared to floating-point types.
- Configure block data types to match the smallest required data type.
- Use signal ranges to constrain data, allowing more aggressive data type optimization.
- Use Memory Block: Consider using Memory blocks to allocate memory in a controlled manner. This allows you to manage memory explicitly and can help prevent overallocation.
- Data Decomposition: If you have large arrays, consider decomposing them into smaller chunks or optimizing the data layout to reduce memory fragmentation.
- Check Library Block Parameters: If you're using custom library blocks, check their parameters. Some blocks may have configuration options that impact memory usage.
- Analyze Code Generation Reports: Enable and review the code generation reports in Simulink. These reports can provide insights into memory usage and suggest optimizations.
- Limit Sample Rates: Reducing the sample rates of your signals can help reduce memory usage in embedded systems.
By applying these strategies and being mindful of data types and memory usage throughout your Simulink model, you can work towards reducing the total size of global variables and better fit your embedded hardware constraints.
