Sparse matrix
Dear all, I have a problem with sparse matrix treatment. My matrix holds many zeroelements and real irregularity. From the memory storage limits, I want compress it. And hopefully I want to compute it in original arrangement withot uncompressing ( keep less memory). Do you have any idea? Some algorithm(liblary) exist? Please advise me.
Thanks in advance. 
Re: Sparse matrix
I use PETSc (http://www.mcs.anl.gov/petsc/)

Re: Sparse matrix
dears sorry for my bed english dear damir galeev i dont know petsc dear takuya tsuji you can use twuo rectangular matrix: the first for the coefficient ,the second for the column index.programming you can resolve the problem. hi

Re: Sparse matrix
You can use what is called a triad format. You define two integer arrays (which carry row and column numbers of nonzero entries) and one real array which carries the corresponding nonzero entries. Standard software like netlib often recognize this format. See www.netlib.org for other formats. Once you have the sparse matrix in a one standard format, I think there are standard routines to change into other formats.

Re: Sparse matrix
One can define 2 integer arrays for sparse matrix: 1st: N[row_number] = amount of all nonezero elements right up to the row number "row_number", the 2nd one gives the column for ith nonezero element in the row
column = column[N[row]+i] the only real (or double) array defines values: value = value[N[row]+i] (i  number of the nonezero element in the row) 
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