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    <title>topic Solution to the system of linear equations (Ax=b) with a tridiagonal matrix A  in Intel® oneAPI Math Kernel Library</title>
    <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Solution-to-the-system-of-linear-equations-Ax-b-with-a/m-p/1163816#M28078</link>
    <description>&lt;P&gt;&lt;SPAN style="font-size: 1em;"&gt;Dear all,&lt;/SPAN&gt;&lt;/P&gt;

&lt;P&gt;I'm using&amp;nbsp;ZGTSV routine in order to solve a system of linear equations (Ax=b), where A is a tridiagonal matrix which may not be diagonally dominant (depends on initial values). For a while now I have detected some errors regarding the method used in the ?GTSV routines. Specially I have found that Gauss elimination loses precision due to accumulated round-off errors. I believe that this is my case since the amplitude of the errors increases from x(N) to x(1) (maybe due to backsubstitution?). To test this I actually placed in the x array the data backwards x(N:1) and made the necessary changes to the A matrix and vector b.&amp;nbsp;&lt;BR /&gt;
	&lt;BR /&gt;
	Now I was thinking of using iterative methods (Jacobi or Gauss-Seidel) instead of direct method (Gauss elimination) but I couldn't find any routine that would do this for me. Is there one?&lt;BR /&gt;
	&lt;BR /&gt;
	BTW: does anyone know any better method to solve my problem?&lt;BR /&gt;
	&lt;BR /&gt;
	Thank you in advance for your help&lt;/P&gt;

&lt;P&gt;Best regards&lt;BR /&gt;
	Josué Lopes&lt;/P&gt;

&lt;P&gt;&amp;nbsp;&lt;/P&gt;

&lt;P&gt;&amp;nbsp;&lt;/P&gt;

&lt;P&gt;&amp;nbsp;&lt;/P&gt;

&lt;P&gt;&amp;nbsp;&lt;/P&gt;

&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Mon, 27 Nov 2017 20:11:19 GMT</pubDate>
    <dc:creator>Josue_L_</dc:creator>
    <dc:date>2017-11-27T20:11:19Z</dc:date>
    <item>
      <title>Solution to the system of linear equations (Ax=b) with a tridiagonal matrix A</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Solution-to-the-system-of-linear-equations-Ax-b-with-a/m-p/1163816#M28078</link>
      <description>&lt;P&gt;&lt;SPAN style="font-size: 1em;"&gt;Dear all,&lt;/SPAN&gt;&lt;/P&gt;

&lt;P&gt;I'm using&amp;nbsp;ZGTSV routine in order to solve a system of linear equations (Ax=b), where A is a tridiagonal matrix which may not be diagonally dominant (depends on initial values). For a while now I have detected some errors regarding the method used in the ?GTSV routines. Specially I have found that Gauss elimination loses precision due to accumulated round-off errors. I believe that this is my case since the amplitude of the errors increases from x(N) to x(1) (maybe due to backsubstitution?). To test this I actually placed in the x array the data backwards x(N:1) and made the necessary changes to the A matrix and vector b.&amp;nbsp;&lt;BR /&gt;
	&lt;BR /&gt;
	Now I was thinking of using iterative methods (Jacobi or Gauss-Seidel) instead of direct method (Gauss elimination) but I couldn't find any routine that would do this for me. Is there one?&lt;BR /&gt;
	&lt;BR /&gt;
	BTW: does anyone know any better method to solve my problem?&lt;BR /&gt;
	&lt;BR /&gt;
	Thank you in advance for your help&lt;/P&gt;

&lt;P&gt;Best regards&lt;BR /&gt;
	Josué Lopes&lt;/P&gt;

&lt;P&gt;&amp;nbsp;&lt;/P&gt;

&lt;P&gt;&amp;nbsp;&lt;/P&gt;

&lt;P&gt;&amp;nbsp;&lt;/P&gt;

&lt;P&gt;&amp;nbsp;&lt;/P&gt;

&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 27 Nov 2017 20:11:19 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Solution-to-the-system-of-linear-equations-Ax-b-with-a/m-p/1163816#M28078</guid>
      <dc:creator>Josue_L_</dc:creator>
      <dc:date>2017-11-27T20:11:19Z</dc:date>
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