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실행 속도
코드 생성기는 전역 변수를 지역 변수로 대체하고, 데이터 복사본을 제거하고, memset 및 memcpy 함수를 사용하고, 데이터를 저장하는 데 필요한 메모리 양을 줄이는 등의 방법으로 생성 코드의 실행 속도를 높입니다. 컴파일러와 프로세서에 맞는 최적화를 구현하고, 버퍼 재사용을 지정하고, 필요 없는 코드를 제거하면 생성된 코드의 실행 속도를 높일 수 있습니다.
도움말 항목
- Optimize Generated Code by Combining Multiple for Constructs
The code generator uses data dependency analysis to combine
forconstructs to reduce static code size and runtime branching. - Configure Loop Unrolling Threshold
Starting at a default value of 5, the code generator begins to use a
forloop instead of separate statements to assign values to the elements of a signal or parameter array. - Eliminate Dead Code Paths in Generated Code
The code generator eliminates dead (that is, unused) code paths from the generated code.
- 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.
- Inline Numeric Values of Block Parameters
Reduce global RAM usage by inlining the literal numeric values of block parameters.
- Optimize Generated Code Using Fixed-Point Data with Simulink, Stateflow, and MATLAB
Generate fixed-point code in Simulink®, Stateflow®, and MATLAB®.
- Generate Target Optimizations Within Algorithm Code
Customize generated algorithm code with target-specific optimizations.
- 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.
- Optimize Generated Code for Complex Signals
The code generator performs various optimizations on the structures that represent signals in the generated code.
- 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.
- Control Memory Allocation for Variable-Size Arrays in a MATLAB Function Block
Disable dynamic memory allocation or specify a dynamic memory allocation threshold for MATLAB Function blocks.
- Generate SIMD Code from Simulink Blocks for Intel Platforms
Improve the execution speed of the generated code using Intel® SSE and Intel AVX technology.
- Optimize Code for Reduction Operations by Using SIMD
Generate optimized code for reduction operations using SIMD instruction sets.
