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<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Times New Roman",serif">Hello Pierre,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Times New Roman",serif"> PDIPM works in parallel so you can have distributed Hessian, Jacobians, constraints, variables, gradients in any layout you want. If you are using a DM then you can
have it generate the Hessian. <o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Times New Roman",serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Times New Roman",serif">Ideally, you want to have the layout below to minimize movement of matrix/vector elements across ranks.
<o:p></o:p></span></p>
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<li class="MsoListParagraph" style="margin-left:0in;mso-list:l0 level1 lfo1"><span style="font-size:12.0pt;font-family:"Times New Roman",serif">The layout of vectors x, bounds on x, and gradient is same.<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l0 level1 lfo1"><span style="font-size:12.0pt;font-family:"Times New Roman",serif">The row layout of the equality/inequality Jacobian is same as the equality/inequality constraint vector layout.<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l0 level1 lfo1"><span style="font-size:12.0pt;font-family:"Times New Roman",serif">The column layout of the equality/inequality Jacobian is same as that for x.<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l0 level1 lfo1"><span style="font-size:12.0pt;font-family:"Times New Roman",serif">The row and column layout for the Hessian is same as x.<o:p></o:p></span></li></ul>
<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Times New Roman",serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Times New Roman",serif">The tutorial example ex1 is extremely small (only 2 variables) so its implementation is very simplistic. I think, in parallel, it ships off constraints etc. to rank 0. It’s
not an ideal example w.r.t demonstrating a parallel implementation. We aim to add more examples as we develop PDIPM. If you have an example to contribute then we would most welcome it and provide help on adding it.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Times New Roman",serif"><o:p> </o:p></span></p>
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<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Times New Roman",serif">Thanks,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Times New Roman",serif">Shri<o:p></o:p></span></p>
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<p class="MsoNormal" style="margin-left:.5in"><b><span style="font-size:12.0pt;color:black">From:
</span></b><span style="font-size:12.0pt;color:black">petsc-dev <petsc-dev-bounces@mcs.anl.gov> on behalf of Pierre Jolivet <pierre.jolivet@enseeiht.fr><br>
<b>Date: </b>Monday, September 14, 2020 at 1:52 PM<br>
<b>To: </b>PETSc Development <petsc-dev@mcs.anl.gov><br>
<b>Subject: </b>[petsc-dev] PDIPDM questions<o:p></o:p></span></p>
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<p class="MsoNormal" style="margin-left:.5in"><o:p> </o:p></p>
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<p class="MsoNormal" style="margin-left:.5in">Hello,<o:p></o:p></p>
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<p class="MsoNormal" style="margin-left:.5in">In my quest to help users migrate from Ipopt to Tao, I’ve a new question.<o:p></o:p></p>
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<p class="MsoNormal" style="margin-left:.5in">When looking at src/tao/constrained/tutorials/ex1.c, it seems that almost everything is centralized on rank 0 (local sizes are 0 but on rank 0).<o:p></o:p></p>
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<p class="MsoNormal" style="margin-left:.5in">I’d like to have my Hessian distributed more naturally, as in (almost?) all other SNES/TS examples, but still keep the Jacobian of my equality constraint, which is of dimension 1 x N (N >> 1), centralized on rank
0.<o:p></o:p></p>
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<p class="MsoNormal" style="margin-left:.5in">Is this possible?<o:p></o:p></p>
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<p class="MsoNormal" style="margin-left:.5in">If not, is it possible to supply the transpose of the Jacobian, of dimension N x 1, which could then be distributed row-wise like the Hessian?<o:p></o:p></p>
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<p class="MsoNormal" style="margin-left:.5in">Or maybe use some trick to distribute a MatAIJ/MatDense of dimension 1 x N column-wise? Use a MatNest with as many blocks as processes?<o:p></o:p></p>
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<p class="MsoNormal" style="margin-left:.5in"><o:p> </o:p></p>
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<p class="MsoNormal" style="margin-left:.5in">So, just to sum up, how can I have a distributed Hessian with a Jacobian with a single row?<o:p></o:p></p>
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<p class="MsoNormal" style="margin-left:.5in"><o:p> </o:p></p>
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<p class="MsoNormal" style="margin-left:.5in">Thanks in advance for your help,<o:p></o:p></p>
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<p class="MsoNormal" style="margin-left:.5in">Pierre<o:p></o:p></p>
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