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Code Generation for quadprog Background

What Is Code Generation?

Code generation is the conversion of MATLAB® code to C/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 an example, see Generate Code for quadprog. For code generation in other optimization solvers, see Generate Code for fmincon, Generate Code for fsolve, or Generate Code for lsqcurvefit or lsqnonlin.

Code Generation Requirements

  • quadprog supports 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.

  • quadprog does not support the problem argument for code generation.

    [x,fval] = quadprog(problem) % Not supported
  • All quadprog input matrices such as A, Aeq, lb, and ub must be full, not sparse. You can convert sparse matrices to full by using the full function.

  • The lb and ub arguments must have the same number of entries as the number of columns in H or must be empty [].

  • If your target hardware does not support infinite bounds, use optim.coder.infbound.

  • For advanced code optimization involving embedded processors, you also need an Embedded Coder® license.

  • You must include options for quadprog and specify them using optimoptions. The options must include the Algorithm option, set to 'active-set'.

    options = optimoptions('quadprog','Algorithm','active-set');
    [x,fval,exitflag] = quadprog(H,f,A,b,Aeq,beq,lb,ub,x0,options);
  • Code generation supports these options:

    • Algorithm — Must be 'active-set'

    • ConstraintTolerance

    • MaxIterations

    • ObjectiveLimit

    • OptimalityTolerance

    • StepTolerance

  • Generated code has limited error checking for options. The recommended way to update an option is to use optimoptions, not dot notation.

    opts = optimoptions('quadprog','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).

See Also

| (MATLAB Coder) | |

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