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Old 06-25-2010, 11:22 AM   #16
saikee
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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.
 
Old 06-25-2010, 03:54 PM   #17
mostlyharmless
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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.
 
Old 06-25-2010, 04:21 PM   #18
lupusarcanus
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IMHO, this does not belong in Linux - Newbie.
 
  


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