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    <title>topic Generalized eigenvalue problem with non-definite symmetric matrix in Intel® oneAPI Math Kernel Library</title>
    <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Generalized-eigenvalue-problem-with-non-definite-symmetric/m-p/957062#M15575</link>
    <description>&lt;P&gt;I need to compute the 5 lowest real eigenvalues and corresponding eigenvectors for a generalized eigenvalue problem A*u=lambda*B*u. Both A and B are real symmetric matrices. A is positive definite but B is not positive definite.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I can use dggev but dggev computes ALL the eigenvalues and eigenvectors assuming A and B are not symmetric, which I think it is not efficient because (a) I need onl 5 eignevalues/eigenvectors and (b) my matrices ARE symmetric.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Since B is not positive definite, I cannot use sygvx.&lt;/P&gt;
&lt;P&gt;I want to use MKL! &lt;BR /&gt;What can I do?&lt;/P&gt;</description>
    <pubDate>Tue, 15 Oct 2013 22:55:31 GMT</pubDate>
    <dc:creator>Ever_B_</dc:creator>
    <dc:date>2013-10-15T22:55:31Z</dc:date>
    <item>
      <title>Generalized eigenvalue problem with non-definite symmetric matrix</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Generalized-eigenvalue-problem-with-non-definite-symmetric/m-p/957062#M15575</link>
      <description>&lt;P&gt;I need to compute the 5 lowest real eigenvalues and corresponding eigenvectors for a generalized eigenvalue problem A*u=lambda*B*u. Both A and B are real symmetric matrices. A is positive definite but B is not positive definite.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I can use dggev but dggev computes ALL the eigenvalues and eigenvectors assuming A and B are not symmetric, which I think it is not efficient because (a) I need onl 5 eignevalues/eigenvectors and (b) my matrices ARE symmetric.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Since B is not positive definite, I cannot use sygvx.&lt;/P&gt;
&lt;P&gt;I want to use MKL! &lt;BR /&gt;What can I do?&lt;/P&gt;</description>
      <pubDate>Tue, 15 Oct 2013 22:55:31 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Generalized-eigenvalue-problem-with-non-definite-symmetric/m-p/957062#M15575</guid>
      <dc:creator>Ever_B_</dc:creator>
      <dc:date>2013-10-15T22:55:31Z</dc:date>
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    <item>
      <title>Hi Ever B.,</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Generalized-eigenvalue-problem-with-non-definite-symmetric/m-p/957063#M15576</link>
      <description>&lt;P&gt;Hi Ever B.,&lt;/P&gt;
&lt;P&gt;You can solve the problem mu*A*u=B*u and then find lambda=1/mu. sygvx is applicable for this problem. Of course, you'll have to find 5 biggest eigenvalues. Of course, possibility of mu to be equal to 0 should be considred separately.&lt;/P&gt;
&lt;P&gt;Victor&lt;/P&gt;</description>
      <pubDate>Wed, 16 Oct 2013 10:56:09 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Generalized-eigenvalue-problem-with-non-definite-symmetric/m-p/957063#M15576</guid>
      <dc:creator>Victor_K_Intel1</dc:creator>
      <dc:date>2013-10-16T10:56:09Z</dc:date>
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    <item>
      <title>Solving the adjunct problem</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Generalized-eigenvalue-problem-with-non-definite-symmetric/m-p/957064#M15577</link>
      <description>&lt;P&gt;Solving the adjunct problem as Victor suggested sounds like a great idea, but I cannot get it to work. I use this call:&amp;nbsp;&lt;/P&gt;
&lt;P&gt;[fortran]call dsygvx(1, 'V', 'A', 'U', n, B, n, A, n, vl, vu, 1, n, abstol, m, Lambda, Z, n, work, lwork, iwork, ifail, info)[/fortran]&lt;/P&gt;
&lt;P&gt;Notice I reversed A and B to solve the adjunt problem. I am sure the matrix B is +definite, which is confirmed by info not giving a lack of +definiteness error. The smalles test problem I can devise has n=64 but I want to use this for N&amp;gt;10,000. I do 1/Lambda to get the eigenvalues of the original problem. &amp;nbsp;I get 63 converged, of which one is infinite, 61 give the same large unreasonable value, and only one, #63, has a resonable but not correct value. I have to say that I have solved the original problem for the 5 lowest eigenvalues with an iterative algorithm that I coded myself but it is not efficient. I want to use MKL. What can I try now? Is there any iterative algorithm in MKL?&lt;/P&gt;
&lt;P&gt;Thanks!&lt;/P&gt;
&lt;P&gt;&lt;/P&gt;</description>
      <pubDate>Sat, 19 Oct 2013 21:50:28 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Generalized-eigenvalue-problem-with-non-definite-symmetric/m-p/957064#M15577</guid>
      <dc:creator>Ever_B_</dc:creator>
      <dc:date>2013-10-19T21:50:28Z</dc:date>
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