Matrix: Schenk_IBMNA/c-56

Description: IBM TJ Watson, non-linear optimization

Schenk_IBMNA/c-56 graph
(undirected graph drawing)


Schenk_IBMNA/c-56 dmperm of Schenk_IBMNA/c-56

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  • Matrix group: Schenk_IBMNA
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  • download as a MATLAB mat-file, file size: 2 MB. Use UFget(1574) or UFget('Schenk_IBMNA/c-56') in MATLAB.
  • download in Matrix Market format, file size: 2 MB.
  • download in Rutherford/Boeing format, file size: 1 MB.

    Matrix properties
    number of rows35,910
    number of columns35,910
    nonzeros380,240
    structural full rank?yes
    structural rank35,910
    # of blocks from dmperm5
    # strongly connected comp.5
    explicit zero entries660
    nonzero pattern symmetrysymmetric
    numeric value symmetrysymmetric
    typereal
    structuresymmetric
    Cholesky candidate?no
    positive definite?no

    authorIBM
    editorO. Schenk
    date2006
    kindoptimization problem
    2D/3D problem?no

    Additional fieldssize and type
    bfull 35910-by-1

    Ordering statistics:result
    nnz(chol(P*(A+A'+s*I)*P')) with AMD629,137
    Cholesky flop count7.3e+07
    nnz(L+U), no partial pivoting, with AMD1,222,364
    nnz(V) for QR, upper bound nnz(L) for LU, with COLAMD11,617,211
    nnz(R) for QR, upper bound nnz(U) for LU, with COLAMD19,148,275

    Note that all matrix statistics (except nonzero pattern symmetry) exclude the 660 explicit zero entries.

    SVD-based statistics:
    norm(A)120695
    min(svd(A))1e-08
    cond(A)1.20695e+13
    rank(A)35,904
    sprank(A)-rank(A)6
    null space dimension6
    full numerical rank?no
    singular value gap829.534

    singular values (MAT file):click here
    SVD method used:s = svd (full (A))
    status:ok

    Schenk_IBMNA/c-56 svd

    For a description of the statistics displayed above, click here.

    Maintained by Tim Davis, last updated 12-Mar-2014.
    Matrix pictures by cspy, a MATLAB function in the CSparse package.
    Matrix graphs by Yifan Hu, AT&T Labs Visualization Group.