Code Generation in Linear Least Squares: Background
What Is Code Generation?
Code generation is the conversion of MATLAB® code to C code using MATLAB Coder™. Code generation requires a MATLAB Coder license.
Typically, you use code generation to deploy code on hardware that is not running
MATLAB. For example, you can deploy code on a robot, using
lsqlin for optimizing movement or planning.
For an example, see Generate Code for lsqlin. For code generation in other optimization solvers, see Generate Code for fmincon, Generate Code for quadprog, Generate Code for lsqcurvefit or lsqnonlin, or Generate Code for fsolve.
Requirements for Code Generation
lsqlinsupports code generation using either the
codegen(MATLAB Coder) function or the MATLAB Coder app. You must have a MATLAB Coder license to generate code.
The target hardware must support standard double-precision floating-point computations. You cannot generate code for single-precision or fixed-point computations.
Code generation targets do not use the same math kernel libraries as MATLAB solvers. Therefore, code generation solutions can vary from solver solutions, especially for poorly conditioned problems.
When solving unconstrained and underdetermined problems in MATLAB,
mldivide, which returns a basic solution. In code generation, the returned solution has minimum norm, which usually differs.
lsqlindoes not support the
problemargument for code generation.
[x,fval] = lsqlin(problem) % Not supported
lsqlininput matrices such as
ubmust be full, not sparse. You can convert sparse matrices to full by using the
ubarguments must have the same number of entries as the number of columns in
Cor must be empty
If your target hardware does not support infinite bounds, use
For advanced code optimization involving embedded processors, you also need an Embedded Coder® license.
You must include options for
lsqlinand specify them using
optimoptions. The options must include the
Algorithmoption, set to
options = optimoptions('lsqlin','Algorithm','active-set'); [x,fval,exitflag] = lsqlin(C,d,A,b,Aeq,beq,lb,ub,x0,options);
Code generation supports these options:
Algorithm— Must be
Generated code has limited error checking for options. The recommended way to update an option is to use
optimoptions, not dot notation.
opts = optimoptions('lsqlin','Algorithm','active-set'); opts = optimoptions(opts,'MaxIterations',1e4); % Recommended opts.MaxIterations = 1e4; % Not recommended
Do not load options from a file. Doing so can cause code generation to fail. Instead, create options in your code.
If you specify an option that is not supported, the option is typically ignored during code generation. For reliable results, specify only supported options.
Generated Code Not Multithreaded
By default, generated code for use outside the MATLAB environment uses linear algebra libraries that are not multithreaded. Therefore, this code can run significantly slower than code in the MATLAB environment.
If your target hardware has multiple cores, you can achieve better performance by using custom multithreaded LAPACK and BLAS libraries. To incorporate these libraries in your generated code, see Speed Up Linear Algebra in Generated Standalone Code by Using LAPACK Calls (MATLAB Coder).
codegen (MATLAB Coder) |