This sort of thing would definitely compute the inverse. And it is definitely to be avoided.
How about you give some specifics so I can say what should be done? On Sun, Oct 4, 2015 at 7:31 PM, go canal <goca...@yahoo.com.invalid> wrote: > Thank you all, the solver is something like this, am I correct: > Matrix m = .... > Matrix inverse = new QRDecomposition(m).solve(new DiagonalMatrix(1, > m.rowSize())); > > The problem I have is that the matrix is too big, I need distributed, or > out-of-core solution. > > thanks, canal > > > On Monday, October 5, 2015 6:25 AM, Peter Jaumann < > peter.jauma...@gmail.com> wrote: > > > This should be done with a matrix solver indeed!!! > > > > On Oct 4, 2015 11:53 AM, "Ted Dunning" <ted.dunn...@gmail.com> wrote: > > > > > > It is almost certain that starting with an inversion is a serious error. > > > > Are you sure you don't want a matrix solver instead? > > > > Sent from my iPhone > > > > > On Oct 3, 2015, at 20:09, go canal <goca...@yahoo.com.INVALID> wrote: > > > > > > oh, it is so unfortunate that the first step of my project requires the > inversion of a very large matrix. will have to revert back to scalapack or > MR based solutions I guess. > > > thanks, canal > > > > > > > > > On Saturday, October 3, 2015 11:31 PM, Ted Dunning < > ted.dunn...@gmail.com> wrote: > > > > > > > > > I doubt seriously that Samsara will support matrix inversion per se. > The > > > problem is > > > > > > a) it densifies sparse matrices > > > > > > b) it is much more costly than solving a linear system > > > > > > Samsara is roughly memory based, but different back-ends will try to > spill > > > to disk if necessary. It is likely that the resulting degradation in > > > performance would be dramatic and thus unacceptable to most users. > > > > > > > > > > > >> On Fri, Oct 2, 2015 at 8:47 PM, go canal <goca...@yahoo.com.invalid> > wrote: > > >> > > >> HiI saw some distributed matrix functions included in Samsara now. > > >> Wondering if we have a plan to support matrix inversion ?BTW, am I > correct > > >> that it is distributed memory based, not out-of-core ? thanks, canal > > > > > > > > > >
