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Right. That sounds good<br>
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<div>Heeho Park</div>
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<blockquote type="cite">On Apr 9, 2020, at 2:44 PM, Matthew Knepley <knepley@gmail.com> wrote:<br>
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<div dir="ltr">On Thu, Apr 9, 2020 at 3:41 PM Park, Heeho via petsc-users <<a href="mailto:petsc-users@mcs.anl.gov">petsc-users@mcs.anl.gov</a>> wrote:<br>
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<p>Hi PETSc developers,<br>
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<p>I am trying to formulate<br>
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<p>p^T J^T J p <br>
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<p>where p is a solution vector length n, J is Jacobian n-by-n matrix. <br>
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<p>Ref: <a href="https://en.wikipedia.org/wiki/Gauss%E2%80%93Newton_algorithm" target="_blank">https://en.wikipedia.org/wiki/Gauss%E2%80%93Newton_algorithm</a> under Large-scale optimization<br>
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<p>It is known that for parallel computations, the best way to perform this computation (with csr matrix) is<br>
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<p>J^T J p = SUM_i [ c_i ( c_i dot p) ] which results in a vector.</p>
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<div>I don't think so. Why not just do</div>
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<div> y = J p</div>
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<div> y^t y = p^T J^T J p</div>
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<div> Thanks,</div>
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<div> Matt</div>
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<p>In PFLOTRAN, we use mpibaij matrix. I could not find a PETSc command to perform this with one command.</p>
<p>Is there one I couldn't find? if not, is using MATGETROW with C for-loop a good way to do this?<br>
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<p>I currently use, MatMult(J,p,w); MatMultTranspose(J,w,w2); VecDotRealPart(p,w2);<br>
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<p>Best,<br>
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<div>Heeho Daniel Park<br>
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! ------------------------------------ !<br>
Sandia National Laboratories</div>
<div>Org: 08844, R&D</div>
<div>Work: 505-844-1319<br>
! ------------------------------------ !<br>
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-- <br>
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<div>What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead.<br>
-- Norbert Wiener</div>
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<div><a href="http://www.cse.buffalo.edu/~knepley/" target="_blank">https://www.cse.buffalo.edu/~knepley/</a><br>
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