执行速度
提高生成的代码的执行速度
代码生成器通过以下途径尽可能提高生成的代码的执行速度：用局部变量替换全局变量，删除数据副本，使用 memset 和 memcpy 函数，以及减少用于存储数据的内存量。您可以实施特定于编译器和处理器的优化，指定缓冲区重用以及删除可能不需要的代码，以此提高生成的代码的执行速度。
模型设置
主题
执行速度优化基础知识
- Design Techniques to Optimize Models for Efficient Code Generation
Apply design tools and techniques to optimize a model for code generation. - Optimize Generated Code Using Code Efficiency Tools and Techniques
When generating production code from your model to deploy into a real-time embedded system, code efficiency is an important consideration. - Configure Model for Code Generation Objectives by Using Code Generation Advisor
Use the Code Generation Advisor to check your model against code generation objectives. - Generate Efficient Code by Setting Model Configuration Parameters
Choose the efficiency level and priorities for your generated code.
特定于处理器的优化
- Control Data and Function Placement in Memory by Inserting Pragmas
Increase code efficiency on your hardware by inserting pragmas in the generated code. Pragmas specify locations in memory to store data and functions. - Replace boolean with Specific Integer Data Type
Improve the execution speed of the generated code by replacing thebooleanbuilt-in data type with a specific integer data type. - Subnormal Number Execution Speed
Minimize the possibility of execution slowdowns or overruns due to subnormal number calculation latency. - Floating-Point Multiplication to Handle a Net Slope Correction
For processors that support efficient multiplication, improve code efficiency by using floating-point multiplication to handle a net slope correction. - Generate Target Optimizations Within Algorithm Code
Customize generated algorithm code with target-specific optimizations. - Generate SIMD Code from Simulink Blocks for Intel Platforms
Improve the execution speed of the generated code using Intel® SSE and Intel AVX technology. - Generate SIMD Code from Simulink Blocks for Apple silicon Platforms
Improve the execution speed of the generated code for Apple silicon platforms using ARM® Neon technology. - Optimize SIMD Code by Performing Fused Multiply Add Operations
For processors that support FMA instructions, improve execution efficiency by performing fused multiply-add operations.
用于提高执行效率的优化
- 优化全局变量使用
选择全局变量引用优化来满足您的内存使用量和执行速度要求。 - Improve Execution Efficiency by Reordering Block Operations in the Generated Code
The code generator can change the block execution order to improve execution efficiency. - Configure Loop Unrolling Threshold
Starting at a default value of 5, the code generator begins to use aforloop instead of separate statements to assign values to the elements of a signal or parameter array. - Use memcpy Function to Optimize Generated Code for Vector Assignments
The code generator optimizes the generated code for vector assignments by replacingforloops withmemcpyfunction calls. - Use Conditional Input Branch Execution
For Switch and Multiport Switch blocks, Simulink® executes only blocks that compute the control input and the data input that the control input selects. - 控制 MATLAB Function 模块中可变大小数组的内存分配
禁用动态内存分配或为 MATLAB Function 模块指定动态内存分配阈值。 - Speed Up Linear Algebra in Code Generated from a MATLAB Function Block
Generate LAPACK calls for certain linear algebra functions in a MATLAB function block. Specify LAPACK library to use. - Speed Up Matrix Operations in Code Generated from a MATLAB Function Block
Generate BLAS calls for certain low-level matrix operations. Specify BLAS library to use. - Speed Up Fast Fourier Transforms in Code Generated from a MATLAB Function Block
Generate FFTW library calls for fast Fourier transforms in a MATLAB Function block. Specify the FFTW library. - Synchronize Multithreaded FFTW Planning in Code Generated from a MATLAB Function Block
Implement FFT library callback class methods and provide supporting C code to prevent concurrent access to FFTW planning. - Optimize Performance of Memory Access by Using Data Alignment
Optimize the alignment of data in memory for your hardware.
使用 Halide 代码生成的优化
- Speed Up Generated Code Execution with Halide Code
Generate Halide code from Simulink models for faster array computation. - When to Use Halide Code for Efficiency
Determine when to use Halide code to provide greater execution speed. - Enhance Generated Code Performance Using Halide from a MATLAB Function Block
Generate Halide code from MATLAB Function blocks in a Simulink model for faster array computation.
相关信息
精选示例
通过开发和使用代码替换库来优化生成的代码 - Simulink
使用代码替换库优化生成的代码。
