echo on n = 100; A = randn(2*n,n); b = randn(2*n,1); cvx_begin variable x(n) minimize( norm( A*x-b ) ) cvx_end echo off
n = 100; A = randn(2*n,n); b = randn(2*n,1); cvx_begin variable x(n) minimize( norm( A*x-b ) ) cvx_end Calling sedumi: 201 variables, 101 equality constraints For improved efficiency, sedumi is solving the dual problem. ------------------------------------------------------------ SeDuMi 1.21 by AdvOL, 2005-2008 and Jos F. Sturm, 1998-2003. Alg = 2: xz-corrector, Adaptive Step-Differentiation, theta = 0.250, beta = 0.500 eqs m = 101, order n = 3, dim = 202, blocks = 2 nnz(A) = 20001 + 0, nnz(ADA) = 10201, nnz(L) = 5151 it : b*y gap delta rate t/tP* t/tD* feas cg cg prec 0 : 6.88E+00 0.000 1 : -8.51E+00 1.66E+00 0.000 0.2408 0.9000 0.9000 -0.52 1 1 2.1E+00 2 : -1.10E+01 1.62E-01 0.000 0.0977 0.9900 0.9900 0.97 1 1 2.4E-01 3 : -1.08E+01 9.64E-05 0.387 0.0006 0.9999 0.9999 1.04 1 1 1.4E-04 4 : -1.08E+01 5.79E-07 0.000 0.0060 0.9990 0.9990 1.62 1 1 6.7E-07 5 : -1.08E+01 7.28E-14 0.000 0.0000 1.0000 1.0000 1.00 1 1 8.9E-14 iter seconds digits c*x b*y 5 0.0 Inf -1.0766202444e+01 -1.0766202444e+01 |Ax-b| = 4.3e-14, [Ay-c]_+ = 1.7E-13, |x|= 1.4e+00, |y|= 1.1e+01 Detailed timing (sec) Pre IPM Post 1.000E-02 4.000E-02 0.000E+00 Max-norms: ||b||=1, ||c|| = 3.449504e+00, Cholesky |add|=0, |skip| = 0, ||L.L|| = 1. ------------------------------------------------------------ Status: Solved Optimal value (cvx_optval): +10.7662 echo off