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<li class="toctree-l2"><a class="reference internal" href="hands-on/hands-on1.html">Exercise 1: Standard Symmetric Eigenvalue Problem</a></li>
<li class="toctree-l2"><a class="reference internal" href="hands-on/hands-on2.html">Exercise 2: Standard Non-Symmetric Eigenvalue Problem</a></li>
<li class="toctree-l2"><a class="reference internal" href="hands-on/hands-on3.html">Exercise 3: Generalized Eigenvalue Problem Stored in a File</a></li>
<li class="toctree-l2"><a class="reference internal" href="hands-on/hands-on4.html">Exercise 4: Singular Value Decomposition</a></li>
<li class="toctree-l2"><a class="reference internal" href="hands-on/hands-on5.html">Exercise 5: Problem without Explicit Matrix Storage</a></li>
<li class="toctree-l2"><a class="reference internal" href="hands-on/hands-on6.html">Exercise 6: Parallel Execution</a></li>
<li class="toctree-l2"><a class="reference internal" href="hands-on/hands-on7.html">Exercise 7: Use of Deflation Subspaces</a></li>
<li class="toctree-l2"><a class="reference internal" href="hands-on/hands-on8.html">Exercise 8: Quadratic Eigenvalue Problem</a></li>
</ul>
</details></li>
<li class="toctree-l1 current active"><a class="current reference internal" href="#">Frequently Asked Questions</a></li>
<li class="toctree-l1"><a class="reference internal" href="presentations.html">Presentations</a></li>
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  <section class="tex2jax_ignore mathjax_ignore" id="frequently-asked-questions">
<h1>Frequently Asked Questions<a class="headerlink" href="#frequently-asked-questions" title="Link to this heading">#</a></h1>
<nav class="contents local" id="table-of-contents">
<p class="topic-title">Table Of Contents</p>
<ul class="simple">
<li><p><a class="reference internal" href="#where-should-i-send-slepc-bug-reports-and-questions" id="id1">1.  Where should I send SLEPc bug reports and questions?</a></p></li>
<li><p><a class="reference internal" href="#is-there-a-slepc-users-mailing-list" id="id2">2.  Is there a SLEPc users mailing list?</a></p></li>
<li><p><a class="reference internal" href="#how-can-i-receive-announcements-of-new-slepc-versions" id="id3">3.  How can I receive announcements of new SLEPc versions?</a></p></li>
<li><p><a class="reference internal" href="#how-should-i-cite-slepc" id="id4">4.  How should I cite SLEPc?</a></p></li>
<li><p><a class="reference internal" href="#apart-from-petsc-is-it-necessary-to-install-other-software-to-use-slepc" id="id5">5.  Apart from PETSc, is it necessary to install other software to use SLEPc?</a></p></li>
<li><p><a class="reference internal" href="#i-do-not-see-any-speedup-when-using-more-than-one-process" id="id6">6.  I do not see any speedup when using more than one process</a></p></li>
<li><p><a class="reference internal" href="#which-is-the-recommended-way-of-learning-slepc" id="id7">7.  Which is the recommended way of learning SLEPc?</a></p></li>
<li><p><a class="reference internal" href="#from-3-0-0-to-3-1-the-behavior-of-shift-and-invert-has-changed" id="id8">8.  From 3.0.0 to 3.1 the behavior of shift-and-invert has changed</a></p></li>
<li><p><a class="reference internal" href="#i-get-an-error-when-retrieving-the-eigenvector" id="id9">9.  I get an error when retrieving the eigenvector</a></p></li>
<li><p><a class="reference internal" href="#i-get-an-error-when-running-shift-and-invert-in-parallel" id="id10">10. I get an error when running shift-and-invert in parallel</a></p></li>
<li><p><a class="reference internal" href="#building-an-application-with-cmake-or-pkg-config" id="id11">11. Building an application with CMake or pkg_config</a></p></li>
<li><p><a class="reference internal" href="#why-is-it-generally-a-bad-idea-to-use-eps-smallest-magnitude" id="id12">12. Why is it generally a bad idea to use EPS_SMALLEST_MAGNITUDE?</a></p></li>
<li><p><a class="reference internal" href="#creating-a-sparse-matrix-gets-terribly-slow-when-i-increase-the-matrix-size" id="id13">13. Creating a sparse matrix gets terribly slow when I increase the matrix size</a></p></li>
<li><p><a class="reference internal" href="#conda-forge-how-to-install-slepc4py-with-complex-scalars" id="id14">14. conda-forge: how to install slepc4py with complex scalars</a></p></li>
<li><p><a class="reference internal" href="#spack-how-to-install-slepc4py-with-complex-scalars" id="id15">15. spack: how to install slepc4py with complex scalars</a></p></li>
<li><p><a class="reference internal" href="#eigenvectors-have-nonzero-imaginary-part" id="id16">16. Eigenvectors have nonzero imaginary part</a></p></li>
</ul>
</nav>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<p><a class="reference external" href="https://petsc.org/release/faq/" target="_blank">PETSc FAQ</a>.</p>
</div>
<section id="where-should-i-send-slepc-bug-reports-and-questions">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">1.  Where should I send SLEPc bug reports and questions?</a><a class="headerlink" href="#where-should-i-send-slepc-bug-reports-and-questions" title="Link to this heading">#</a></h2>
<p>Send all maintenance requests to the SLEPc developers via <a class="reference external" href="mailto:slepc-maint&#37;&#52;&#48;upv&#46;es" target="_blank">slepc-maint<span>&#64;</span>upv<span>&#46;</span>es</a>.</p>
</section>
<section id="is-there-a-slepc-users-mailing-list">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">2.  Is there a SLEPc users mailing list?</a><a class="headerlink" href="#is-there-a-slepc-users-mailing-list" title="Link to this heading">#</a></h2>
<p>No, but SLEPc-related queries can be posted in the <a class="reference external" href="https://petsc.org/release/community/mailing/" target="_blank">petsc-users mailing list</a>.</p>
</section>
<section id="how-can-i-receive-announcements-of-new-slepc-versions">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">3.  How can I receive announcements of new SLEPc versions?</a><a class="headerlink" href="#how-can-i-receive-announcements-of-new-slepc-versions" title="Link to this heading">#</a></h2>
<p>You can join the slepc-announce mailing list by following the instructions in the <a class="reference internal" href="../contact/mail_list.html"><span class="doc std std-doc">Contact</span></a> section. We will update users regarding new major releases through this mailing list.</p>
<p>An alternative is to subscribe to the RSS news feed. In addition to new releases, we will also notify the publication of patches.</p>
</section>
<section id="how-should-i-cite-slepc">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">4.  How should I cite SLEPc?</a><a class="headerlink" href="#how-should-i-cite-slepc" title="Link to this heading">#</a></h2>
<p>When writing a scientific paper that makes use of SLEPc, you should cite at least reference [1] in the <a class="reference internal" href="../material/index.html"><span class="doc std std-doc">list of references</span></a>. In addition, if you use specific SLEPc features (such as computational intervals) that have papers on the list, we suggest citing them as well.</p>
</section>
<section id="apart-from-petsc-is-it-necessary-to-install-other-software-to-use-slepc">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">5.  Apart from PETSc, is it necessary to install other software to use SLEPc?</a><a class="headerlink" href="#apart-from-petsc-is-it-necessary-to-install-other-software-to-use-slepc" title="Link to this heading">#</a></h2>
<p>No, the only requirement to use SLEPc is to have PETSc installed on your system. Additionally, if you want to have access to eigensolvers not included in SLEPc, then you will have to install other libraries (e.g. ARPACK). See also the comment on linear solvers in FAQ #10 below.</p>
</section>
<section id="i-do-not-see-any-speedup-when-using-more-than-one-process">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">6.  I do not see any speedup when using more than one process</a><a class="headerlink" href="#i-do-not-see-any-speedup-when-using-more-than-one-process" title="Link to this heading">#</a></h2>
<div class="admonition important">
<p class="admonition-title">Important</p>
<p>Does not apply for version 3.6 or later, see FAQ #10 below.</p>
</div>
<span style="color:gray">
Probably you are dealing with a generalized eigenproblem (or a standard eigenproblem with shift-and-invert) and solving the linear systems with the default direct solver. By default, SLEPc uses a direct linear solver via PETSc's `redundant` mechanism, which allows the use of direct solvers in parallel executions but is not a really parallel factorization. In order to get speedup in parallel executions, you need to configure PETSc with a parallel direct linear solver such as MUMPS. For details, see the section "Solution of Linear Systems" in SLEPc's user manual.
</span>
</section>
<section id="which-is-the-recommended-way-of-learning-slepc">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">7.  Which is the recommended way of learning SLEPc?</a><a class="headerlink" href="#which-is-the-recommended-way-of-learning-slepc" title="Link to this heading">#</a></h2>
<p>Possibly, the best way of learning to use SLEPc is to follow these steps:</p>
<ul class="simple">
<li><p>First of all, get acquainted with PETSc if you are not already familiar with it (see the <a class="reference external" href="https://petsc.org/release/tutorials/" target="_blank">PETSc tutorials page</a>).</p></li>
<li><p>Read through the entire <a class="reference internal" href="manual/index.html"><span class="doc std std-doc">SLEPc Users Manual</span></a>. In a first reading, one may skip the “advanced usage” sections.</p></li>
<li><p>Follow the steps provided by the <a class="reference internal" href="hands-on/index.html"><span class="doc std std-doc">hands-on exercises</span></a>, trying the examples in an available SLEPc installation.</p></li>
<li><p>Use the example programs available in the SLEPc distribution as a basis for your own programs.</p></li>
<li><p>Use the on-line <a class="reference internal" href="../manualpages/index.html"><span class="doc std std-doc">manual pages</span></a> for reference for individual routines.</p></li>
</ul>
<p>We also provide several <a class="reference internal" href="index.html#video-tutorials"><span class="std std-ref">Video-Tutorials</span></a>.</p>
</section>
<section id="from-3-0-0-to-3-1-the-behavior-of-shift-and-invert-has-changed">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">8.  From 3.0.0 to 3.1 the behavior of shift-and-invert has changed</a><a class="headerlink" href="#from-3-0-0-to-3-1-the-behavior-of-shift-and-invert-has-changed" title="Link to this heading">#</a></h2>
<p>The shift-and-invert spectral transformation (and Cayley as well) is intended for computing the eigenvalues closest to a given value <span class="math notranslate nohighlight">\(\sigma\)</span> (the shift). Those eigenvalues closest to the shift become dominant in the transformed spectrum, so in SLEPc 3.0.0 one had to use <code class="docutils notranslate"><span class="pre"><a href="../manualpages/EPS/EPSWhich.html">EPS_LARGEST_MAGNITUDE</a></span></code> (the default) for this situation. For example (the last option can be omitted because it is the default):</p>
<div class="highlight-none notranslate"><div class="highlight"><pre><span></span>$ ./ex1 -st_type sinvert -st_shift 3.5 -eps_largest_magnitude
</pre></div>
</div>
<p>In contrast, in SLEPc 3.1 the approach is to specify the target value directly in EPS (with <code class="docutils notranslate"><span class="pre"><a href="../manualpages/EPS/EPSSetTarget.html">EPSSetTarget</a>()</span></code>) and indicate that we want to compute eigenvalues closest to the target, with <code class="docutils notranslate"><span class="pre"><a href="../manualpages/EPS/EPSWhich.html">EPS_TARGET_MAGNITUDE</a></span></code>. For example (again, the last option can be omitted):</p>
<div class="highlight-none notranslate"><div class="highlight"><pre><span></span>$ ./ex1 -st_type sinvert -eps_target 3.5 -eps_target_magnitude
</pre></div>
</div>
<p>The value of the shift need not be provided because it is taken from the target value.</p>
<p>Note that another difference is that in 3.1 eigenvalues are returned in the correct order, that is, the first one is the closest to the target, and so on.</p>
</section>
<section id="i-get-an-error-when-retrieving-the-eigenvector">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">9.  I get an error when retrieving the eigenvector</a><a class="headerlink" href="#i-get-an-error-when-retrieving-the-eigenvector" title="Link to this heading">#</a></h2>
<p>After the solver has finished, the solution can be retrieved with <code class="docutils notranslate"><span class="pre"><a href="../manualpages/EPS/EPSGetEigenpair.html">EPSGetEigenpair</a>()</span></code>.  In the <code class="docutils notranslate"><span class="pre">Vr</span></code> (and <code class="docutils notranslate"><span class="pre">Vi</span></code>) argument, one can pass <code class="docutils notranslate"><span class="pre">NULL</span></code> (if the eigenvector is not required), or a <em>valid</em> <a class="reference external" href="https://petsc.org/release/manualpages/Vec/Vec/" title="(in PETSc v3.24)"><span class="xref std std-doc">Vec</span></a> object. This means the vector must have been created, for example with <a class="reference external" href="https://petsc.org/release/manualpages/Vec/VecCreate/" title="(in PETSc v3.24)"><span class="xref std std-doc">VecCreate</span></a>(), <a class="reference external" href="https://petsc.org/release/manualpages/Vec/VecDuplicate/" title="(in PETSc v3.24)"><span class="xref std std-doc">VecDuplicate</span></a>(), or <a class="reference external" href="https://petsc.org/release/manualpages/Mat/MatCreateVecs/" title="(in PETSc v3.24)"><span class="xref std std-doc">MatCreateVecs</span></a>(), see for instance <a class="reference external" href="https://slepc.upv.es/release/src/eps/tutorials/ex7.c.html" target="_blank">ex7.c</a>. The same occurs with analog functions in <code class="docutils notranslate"><span class="pre"><a href="../manualpages/SVD/SVD.html">SVD</a></span></code>, <code class="docutils notranslate"><span class="pre"><a href="../manualpages/PEP/PEP.html">PEP</a></span></code>, and <code class="docutils notranslate"><span class="pre"><a href="../manualpages/NEP/NEP.html">NEP</a></span></code>.</p>
</section>
<section id="i-get-an-error-when-running-shift-and-invert-in-parallel">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">10. I get an error when running shift-and-invert in parallel</a><a class="headerlink" href="#i-get-an-error-when-running-shift-and-invert-in-parallel" title="Link to this heading">#</a></h2>
<p>In 3.6 and later versions, the shift-and-invert spectral transformation defaults to using <code class="docutils notranslate"><span class="pre">preonly</span></code>+<code class="docutils notranslate"><span class="pre">lu</span></code> for solving linear systems. If you run with more than one MPI process this will fail, unless you use an external package for the parallel LU factorization. This is explained in section <a class="reference internal" href="manual/st.html#sec-lin"><span class="std std-ref">Solution of Linear Systems</span></a> in the Users Manual. In previous versions of SLEPc, this would not generate an error since it was using <code class="docutils notranslate"><span class="pre">redundant</span></code> rather than plain <code class="docutils notranslate"><span class="pre">lu</span></code>.</p>
</section>
<section id="building-an-application-with-cmake-or-pkg-config">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">11. Building an application with CMake or pkg_config</a><a class="headerlink" href="#building-an-application-with-cmake-or-pkg-config" title="Link to this heading">#</a></h2>
<p>SLEPc (and PETSc) provides <code class="docutils notranslate"><span class="pre">pkg_config</span></code> files that can be used from makefiles as well as from CMake files. See the discussion at <a class="gitlab reference external" href="https://gitlab.com/slepc/slepc/-/issues/19" target="_blank">Issue #19</a>.</p>
</section>
<section id="why-is-it-generally-a-bad-idea-to-use-eps-smallest-magnitude">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">12. Why is it generally a bad idea to use EPS_SMALLEST_MAGNITUDE?</a><a class="headerlink" href="#why-is-it-generally-a-bad-idea-to-use-eps-smallest-magnitude" title="Link to this heading">#</a></h2>
<p>Krylov methods (and in particular the default SLEPc eigensolver, Krylov-Schur) are good for approximating eigenvalues in the periphery of the spectrum. Assuming an eigenproblem with real eigenvalues only, the use of <code class="docutils notranslate"><span class="pre"><a href="../manualpages/EPS/EPSWhich.html">EPS_SMALLEST_MAGNITUDE</a></span></code> will be appropriate only if all eigenvalues are either positive or negative. Otherwise, the smallest magnitude eigenvalues lie in the interior of the spectrum, and therefore the convergence will likely be very slow. The usual approach for computing interior eigenvalues is the shift- and-invert spectral transformation (see <a class="reference internal" href="manual/st.html#ch-st"><span class="std std-ref">ST: Spectral Transformation</span></a> in the Users Manual). Hence, instead of <code class="docutils notranslate"><span class="pre">-eps_smallest_magnitude</span></code> one would generally prefer <code class="docutils notranslate"><span class="pre">-st_type</span> <span class="pre">sinvert</span> <span class="pre">-eps_target</span> <span class="pre">0</span></code>.</p>
</section>
<section id="creating-a-sparse-matrix-gets-terribly-slow-when-i-increase-the-matrix-size">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">13. Creating a sparse matrix gets terribly slow when I increase the matrix size</a><a class="headerlink" href="#creating-a-sparse-matrix-gets-terribly-slow-when-i-increase-the-matrix-size" title="Link to this heading">#</a></h2>
<p>Matrix preallocation is extremely important, especially for large matrices.  See the <a class="reference external" href="https://petsc.org/release/manual/mat/#preallocation-of-memory-for-sequential-aij-sparse-matrices" target="_blank">chapter on matrices in the PETSc users manual</a>.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Since PETSc version 3.19 the <a class="reference external" href="https://petsc.org/release/manualpages/Mat/Mat/" title="(in PETSc v3.24)"><span class="xref std std-doc">Mat</span></a> data structures have been changed so that the performance is reasonably good without preallocation.</p>
</div>
</section>
<section id="conda-forge-how-to-install-slepc4py-with-complex-scalars">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">14. conda-forge: how to install slepc4py with complex scalars</a><a class="headerlink" href="#conda-forge-how-to-install-slepc4py-with-complex-scalars" title="Link to this heading">#</a></h2>
<p>The following instructions can be followed to install the conda-forge variant of slepc4py with scalar type complex.</p>
<blockquote>
<div><p>Download Miniforge</p>
<div class="highlight-console notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>wget<span class="w"> </span>https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh
</pre></div>
</div>
<p>Install miniforge in $HOME/miniforge</p>
<div class="highlight-console notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>bash<span class="w"> </span>Miniforge3-Linux-x86_64.sh<span class="w"> </span>-b<span class="w"> </span>-p<span class="w"> </span>~/miniforge
</pre></div>
</div>
<p>Activate Miniforge base environment</p>
<div class="highlight-console notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span><span class="nb">source</span><span class="w"> </span>~/miniforge/bin/activate
</pre></div>
</div>
<p>Create a new test environment with a starting package specification set. Package specification is <code class="docutils notranslate"><span class="pre">&lt;package&gt;=&lt;version&gt;==&lt;build_string&gt;</span></code>. To request the latest version, we can use <code class="docutils notranslate"><span class="pre">*</span></code></p>
<p>For {petsc|slepc}[4py], the build string starts with either ‘real’ or ‘complex’, depending on the configured scalar type. The ‘real’ variants have a build number offset by 100, so they take precedence if a specific <code class="docutils notranslate"><span class="pre">&lt;build_string&gt;</span></code> is not requested.</p>
<p>Long story short, we ask conda to create a new environment initally installing the complex variant of slepc4py latest version with the followng command</p>
<div class="highlight-console notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>conda<span class="w"> </span>create<span class="w"> </span>--name<span class="w"> </span>testenv<span class="w"> </span><span class="nv">slepc4py</span><span class="o">=</span>*<span class="o">=</span>*complex*
</pre></div>
</div>
<p>Activate the test environment</p>
<div class="highlight-console notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>conda<span class="w"> </span>activate<span class="w"> </span>testenv
</pre></div>
</div>
<p>Verify we are running the complex variant</p>
<div class="highlight-console notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>python<span class="w"> </span>-c<span class="w"> </span><span class="err">&#39;</span>
<span class="go">  from slepc4py import SLEPc</span>
<span class="go">  from petsc4py import PETSc</span>
<span class="go">  print(PETSc.ScalarType)</span>
<span class="go">&#39;</span>
</pre></div>
</div>
</div></blockquote>
</section>
<section id="spack-how-to-install-slepc4py-with-complex-scalars">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">15. spack: how to install slepc4py with complex scalars</a><a class="headerlink" href="#spack-how-to-install-slepc4py-with-complex-scalars" title="Link to this heading">#</a></h2>
<p>Make sure you select the <code class="docutils notranslate"><span class="pre">petsc+complex</span></code> variant:</p>
<div class="highlight-console notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>spack<span class="w"> </span>install<span class="w"> </span>py-slepc4py<span class="w"> </span>^petsc+complex
</pre></div>
</div>
<p>This will install PETSc with complex scalars, together with SLEPc as well as petsc4py and slepc4py. Before that, you can also do <code class="docutils notranslate"><span class="pre">spack</span> <span class="pre">spec</span> <span class="pre">py-slepc4py</span> <span class="pre">^petsc+complex</span></code> to check what it is going to install.</p>
</section>
<section id="eigenvectors-have-nonzero-imaginary-part">
<h2><a class="toc-backref" href="#table-of-contents" role="doc-backlink">16. Eigenvectors have nonzero imaginary part</a><a class="headerlink" href="#eigenvectors-have-nonzero-imaginary-part" title="Link to this heading">#</a></h2>
<p>A real symmetric matrix has real eigenvectors, but when building SLEPc with complex scalars the computed eigenvectors have nonzero imaginary part. The rationale is the following. In real scalars, if <span class="math notranslate nohighlight">\(x\)</span> is a unit-norm eigenvector then <span class="math notranslate nohighlight">\(-x\)</span> is also a valid eigenvector. In complex scalars, if <span class="math notranslate nohighlight">\(x\)</span> is a unit-norm eigenvector then <span class="math notranslate nohighlight">\(\alpha x\)</span> is also a valid eigenvector, where <span class="math notranslate nohighlight">\(\alpha\)</span> is a generalized sign, i.e., <span class="math notranslate nohighlight">\(\alpha=\exp(\theta j)\)</span> for any <span class="math notranslate nohighlight">\(\theta\)</span>. So if one wants the imaginary part to be zero, the eigenvectors returned by SLEPc must be normalized a posteriori, as is done for example in <a class="reference external" href="https://slepc.upv.es/release/src/eps/tutorials/ex20.c.html" target="_blank">ex20.c</a> (or the equivalent python example <code class="docutils notranslate"><span class="pre">ex7.py</span></code>). SLEPc does not know if the input matrix is real or complex, so it cannot normalize the vectors internally.</p>
<p>Note that the simple scaling strategy shown in those examples will not be sufficient in case of degenerate eigenvalues, i.e., eigenvalues with multiplicity larger than one.</p>
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