Optimize Generated C/C++ and MEX Code

By default, MATLAB^® Coder™ introduces optimizations when generating C/C++ code or MEX functions from your MATLAB code. For more information, see MATLAB Coder Optimizations in Generated Code.

To optimize your generated code further, you can:

• Adapt your MATLAB code.

• Control code generation using the configuration object from the command-line or the project settings dialog box.

Code optimization is an optional step in the Overview of Code Generation Using MATLAB Coder.

Strategies to Optimize Speed

Use this table to determine how to optimize the execution speed of the generated code.

Condition	Action
Your code has for-loops whose iterations are independent of each other.	Algorithm Acceleration Using Parallel for-Loops (parfor) Automatic Parallelization of for-Loops in the Generated Code
You have variable-size arrays in your MATLAB code.	Minimize Dynamic Memory Allocation
You have multiple variable-size arrays in your MATLAB code. You want dynamic memory allocation for larger arrays and static allocation for smaller ones.	Set Dynamic Memory Allocation Threshold
You want to pass variables in the generated code by reference.	Avoid Data Copies of Function Inputs in Generated Code
You want to maximize speed at the expense of memory usage by inlining most or all functions.	Control Inlining to Fine-Tune Performance and Readability of Generated Code
You do not want to generate code for expressions that only contain constants.	Fold Function Calls into Constants in Generated Code
You have loop operations in your MATLAB code that do not depend on the loop index.	Minimize Redundant Operations in Loops
You have integer operations in your MATLAB code and you know that integer overflow does not occur during execution of the generated code.	Disable Support for Integer Overflow
You know that the generated code does not use nonfinite numbers	Disable Support for Nonfinite Numbers
Your code has for-loops with few iterations.	Unroll for-Loops and parfor-Loops
You already have legacy C/C++ code optimized for your target environment.	Integrate External/Custom Code
You want to speed up the code generated for basic vector and matrix functions.	Speed Up Matrix Operations in Generated Standalone Code by Using BLAS Calls
You want to speed up the code generated for linear algebra functions.	Speed Up Linear Algebra in Generated Standalone Code by Using LAPACK Calls
You want to speed up the code generated for fast Fourier transform (FFT) functions.	Speed Up Fast Fourier Transforms in Generated Standalone Code by Using FFTW Library Calls

Strategies to Optimize Memory Usage

Use this table to determine how to optimize the memory usage of the generated code.

Condition	Action
Your MATLAB code uses conditional statements, but you do not require some branches of these statements in the generated code.	Prevent Code Generation for Unused Execution Paths
You want to pass variables in the generated code by reference.	Avoid Data Copies of Function Inputs in Generated Code
You have limited stack space on the code generation target.	Control Stack Space Usage
Because you have limited memory on the code generation target, you want to avoid inlining functions with many variables.	Control Inlining to Fine-Tune Performance and Readability of Generated Code
You do not want to generate code for expressions that only contain constants.	Fold Function Calls into Constants in Generated Code
You have loop operations in your MATLAB code that do not depend on the loop index.	Minimize Redundant Operations in Loops
You have integer operations in your MATLAB code and you know that integer overflow does not occur during execution of the generated code.	Disable Support for Integer Overflow
You know that the generated code does not use nonfinite numbers	Disable Support for Nonfinite Numbers
You want to optimize memory usage for variables that are large structures or arrays, even if this makes your code less readable.	Reuse Large Arrays and Structures