<html><head><meta http-equiv="content-type" content="text/html; charset=utf-8"></head><body dir="auto"><div dir="ltr"></div><div dir="ltr">Hi</div><div dir="ltr"><br></div><div dir="ltr">The averaging takes place on the same hardware and as part of the same job as the writing the matrix to file in the c++ code. The number of nodes is determined on the problem size and therefor for a single matrix. Allocating extra nodes for the averaging is not economical, unfortunately.</div><div dir="ltr"><br><blockquote type="cite">On 22 May 2025, at 16:52, Junchao Zhang <junchao.zhang@gmail.com> wrote:<br><br></blockquote></div><blockquote type="cite"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div>Did you run in MPI parallel? If not, using MPI and running with multiple compute nodes could solve the problem.</div><div><br></div><div>Are all these matrices already on disk? Then you have to pay the I/O cost for reading the matrices. </div><div><br></div><div>--Junchao Zhang</div><br></div><br><div class="gmail_quote gmail_quote_container"><div dir="ltr" class="gmail_attr">On Thu, May 22, 2025 at 8:21 AM Donald Duck <<a href="mailto:superdduck88@gmail.com">superdduck88@gmail.com</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr">Hello everyone<div><br></div><div>A piece of c++ code writes PETSc AIJ matrices to binary files. My task is to compute an average matrix of these AIJ matrices. Therefore I read the first matrix with petsc4py and then start to add the other matrices to it. All matrixes always have the same size, shape, nnz etc.</div><div><br></div><div>However in some cases these matrices are large and only one of it fits into memory and the reading/writing takes a significant amout of time. Is there a way to read it row by row to prevent memory overflow?</div><div><br></div><div>I'm also open for other suggestions, thanks in advance!</div><div><br></div><div>Raphael</div></div>
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