<div class="gmail_quote">2012/3/22 Gao Bin <span dir="ltr"><<a href="mailto:bin.gao@uit.no">bin.gao@uit.no</a>></span><br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<font>"The parallel dense matrices are partitioned by rows across the processors, so that each local rectangular submatrix is stored in the dense format described above."</font>
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Does it mean each processor will have several continuous rows and all columns of the matrix? If yes, why do we need to specify "n" -- the number of local columns when calling MatCreateMPIDense?<br></font></blockquote>
<div><br></div><div>Interpret the local column size n as the local size of the Vec that the Mat will be applied to.</div><div><br></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
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I am sorry to raise this simple question, since I have read the manual and tutorials, but I have not found a clear answer. Moreover, the reason I am asking this question is that I would like to use PETSc for matrix operations, but the elements of matrices need
to be calculate via my own code. If I know the distribution of the matrix, I could let each processor only calculate and set local values (the rows and columns possessed on the processor itself) for efficiency.<br>
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My second question is if PETSc provides symmetric and anti-symmetric matrices. I have read the manual, the answer seems to be no. Am I right?</font></blockquote></div><br><div>See the SBAIJ format (it is sparse).</div><div>
<br></div><div>With a parallel dense matrix, there isn't any point using a symmetric format unless you use a different distribution of the entries.</div>