• SJSU Singular Matrix Database
  • Matrix group: Sandia
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  • Matrix: Sandia/fpga_dcop_04
  • Description: Sandia/fpga_dcop_04 circuit simulation matrix. Sandia National Lab.
  • download as a MATLAB mat-file, file size: 52 KB. Use SJget(126) or SJget('Sandia/fpga_dcop_04') in MATLAB.
  • download in Matrix Market format, file size: 61 KB.
  • download in Rutherford/Boeing format, file size: 61 KB.


    Routine svd from Matlab (R2008a) used to calculate the singular values.


    dmperm of Sandia/fpga_dcop_04

    scc of Sandia/fpga_dcop_04

    Matrix properties (click for a legend)  
    number of rows1,220
    number of columns1,220
    structural full rank?yes
    structural rank1,220
    numerical rank 1,209
    dimension of the numerical null space11
    numerical rank / min(size(A))0.99098
    Euclidean norm of A 9.3357
    calculated singular value # 12091.0606e-011
    numerical rank defined using a tolerance
    max(size(A))*eps(norm(A)) =
    calculated singular value # 12106.6737e-013
    gap in the singular values at the numerical rank:
    singular value # 1209 / singular value # 1210
    calculated condition number8.1419e+013
    # of blocks from dmperm189
    # strongly connected comp.34
    entries not in dmperm blocks2,318
    explicit zero entries0
    nonzero pattern symmetry 82%
    numeric value symmetry 35%
    Cholesky candidate?no
    positive definite?no

    authorR. Hoekstra
    editorT. Davis
    kindsubsequent circuit simulation problem
    2D/3D problem?no

    Additional fieldssize and type
    bfull 1220-by-1


    next: Sandia/fpga_dcop_05 first: Sandia/fpga_dcop_01

    Ordering statistics:AMD METIS DMPERM+
    nnz(chol(P*(A+A'+s*I)*P'))5,524 5,462 2,972
    Cholesky flop count2.8e+004 2.7e+004 7.9e+003
    nnz(L+U), no partial pivoting9,828 9,704 7,042
    nnz(V) for QR, upper bound nnz(L) for LU10,629 13,241 2,520
    nnz(R) for QR, upper bound nnz(U) for LU26,882 27,775 6,661

    Maintained by Leslie Foster, last updated 24-Apr-2009.

    Entries 5 through 14 in the table of matrix properties and the singular
    value plot were created using SJsingular code. The other plots
    and statistics are produced using utilities from the SuiteSparse package.
    Matrix color plot pictures by cspy, a MATLAB function in the CSparse package.