<html><head><meta http-equiv="content-type" content="text/html; charset=utf-8"></head><body style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">Hi Mathew,<div><br></div><div><div style="orphans: 2; widows: 2;">Thanks for the response. It actually seems like the matrix is very sparse (<font color="#363636"><span style="white-space: pre;">0.99% sparsity from what I’m measuring). It’s an FEA solver so it would make sense.</span></font></div><div style="orphans: 2; widows: 2;"><font color="#363636"><span style="white-space: pre;">My current guess is the optimization flags are making a large difference for the M1 Mac, but I am also surprised it makes such a huge difference.</span></font></div><div style="orphans: 2; widows: 2;"><font color="#363636"><span style="white-space: pre;"><br></span></font></div><div style="orphans: 2; widows: 2;"><font color="#363636"><span style="white-space: pre;">It’s why I was asking if there was a resource or another to use my own version of PETSc with Conda.</span></font></div><div style="orphans: 2; widows: 2;"><font color="#363636"><span style="white-space: pre;"><br></span></font></div><div style="orphans: 2; widows: 2;"><font color="#363636"><span style="caret-color: rgb(54, 54, 54); white-space: pre;">I believe a 2-3 x speed up is worth the hassle. </span></font></div><div style="orphans: 2; widows: 2;"><font color="#363636"><span style="caret-color: rgb(54, 54, 54); white-space: pre;"><br></span></font></div><div style="orphans: 2; widows: 2;"><font color="#363636"><span style="caret-color: rgb(54, 54, 54); white-space: pre;"><br></span></font></div><div style="orphans: 2; widows: 2;"><font color="#363636"><span style="white-space: pre;">Best,</span></font></div><div style="orphans: 2; widows: 2;"><font color="#363636"><span style="white-space: pre;">Jorge</span></font></div><div style="orphans: 2; widows: 2;"><font color="#363636" face="Menlo, Monaco, Courier New, monospace"><span style="white-space: pre;"><br></span></font></div><div style="orphans: 2; widows: 2;"><font color="#363636" face="Menlo, Monaco, Courier New, monospace"><span style="white-space: pre;"><br></span></font></div><div style="orphans: 2; widows: 2;"><font color="#363636" face="Menlo, Monaco, Courier New, monospace"><span style="white-space: pre;"><br></span></font></div><div><blockquote type="cite"><div>On Oct 19, 2023, at 4:00 PM, Matthew Knepley <knepley@gmail.com> wrote:</div><br class="Apple-interchange-newline"><div><meta http-equiv="Content-Type" content="text/html; charset=utf-8"><div dir="ltr"><div dir="ltr">On Thu, Oct 19, 2023 at 3:54 PM Jorge Nin <<a href="mailto:jorgenin@mit.edu">jorgenin@mit.edu</a>> wrote:<br></div><div class="gmail_quote"><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">Hi,<br>
I was playing around with a self compiled version and, and a the Conda binary of Petsc on the same problem, on my M1 Mac.<br>
Interestingly I found that the Conda binary solves the problem 2-3 times slower vs the self compiled version. (For context I’m using the petsc4py python interface) <br>
<br>
I’ve attached two log views to show the comparison.<br>
<br>
I was mostly curious about the possible cause for this.<br></blockquote><div><br></div><div>All the time is in the LU numeric factorization. I don't know if your matrix is sparse or dense. I am guessing it is dense and different LAPACK implementations are linked. If it is sparse, then the compiler options are different between builds, but I would be surprised if it made this much difference.</div><div><br></div><div> Thanks,</div><div><br></div><div> Matt</div><div> </div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">
I was also curious how I could use my own compiled version of PETSc in my Conda install? <br>
<br>
<br>
Best,<br>
Jorge<br>
<br>
</blockquote></div><br clear="all"><div><br></div><span class="gmail_signature_prefix">-- </span><br><div dir="ltr" class="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><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><div><br></div><div><a href="http://www.cse.buffalo.edu/~knepley/" target="_blank">https://www.cse.buffalo.edu/~knepley/</a><br></div></div></div></div></div></div></div></div>
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