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 06-25-2010, 11:22 AM #16 saikee Senior Member   Registered: Sep 2005 Location: Newcastle upon Tyne UK Distribution: Any free distro. Posts: 3,398 Blog Entries: 1 Rep: johnsfine, The matrice I have been dealing with have to be assembled element by element. It is not possible to have an element with zero contribution to the system matrix. In fact in our line of computation the matrix has to have a non-zero determinant as we also solve the Eigen value problem derived from the same matrix too. Thus your argument is valid theoretically but not found in practice if the matrix is a result of some physical law and not just a pure mathemical problem. I wouldn't have thought anybody would use my code blindly non anyone serious in computing would have a problem to computer the Gaussian elimination. For your comfort my routine has been tried by various engineers in my organisation for years. My purpose of listing it out is to convince that it is a very simple procedure to solve a matrix of any size just by a few lines of loops.
 06-25-2010, 03:54 PM #17 mostlyharmless Senior Member   Registered: Jan 2008 Distribution: Arch/Slackware/Knoppix Posts: 1,766 Blog Entries: 14 Rep: Just my 2 bits: a "sparse" matrix may or may not have a specific form which makes a particular algorithm more or less rapid or stable, or both. It'd be more help to smp if we found out that his/her sparse matrix was actually, say, tridiagonal or banded, as is common for matrices arising from applications, as opposed to randomly distributed sparse. So a "general purpose" sparse matrix solver isn't really the best solution. There's also a distinction between storing the sparse matrix efficiently, which is relatively easy, and solving the system efficiently... Last edited by mostlyharmless; 06-25-2010 at 03:55 PM.
 06-25-2010, 04:21 PM #18 lupusarcanus Senior Member   Registered: Mar 2009 Location: USA Distribution: Arch Posts: 1,022 Blog Entries: 19 Rep: IMHO, this does not belong in Linux - Newbie.

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