<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re:issue in running multiple pardiso concurrently. in Intel® oneAPI Math Kernel Library</title>
    <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/issue-in-running-multiple-pardiso-concurrently/m-p/1568151#M35765</link>
    <description>&lt;P&gt;Hello miaodi,&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;&lt;/P&gt;&lt;P&gt;Thank you for posting here.&lt;/P&gt;&lt;P&gt;Could you tell us your oneMKL version, OS version and hardware platform? As well as providing us a simple reproducer for the issue.&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;&lt;/P&gt;&lt;P&gt;Regards,&lt;/P&gt;&lt;P&gt;Ruqiu&lt;/P&gt;&lt;BR /&gt;</description>
    <pubDate>Thu, 01 Feb 2024 02:43:53 GMT</pubDate>
    <dc:creator>Ruqiu_C_Intel</dc:creator>
    <dc:date>2024-02-01T02:43:53Z</dc:date>
    <item>
      <title>issue in running multiple pardiso concurrently.</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/issue-in-running-multiple-pardiso-concurrently/m-p/1566153#M35749</link>
      <description>&lt;P&gt;Hi,&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;For a project, we woule like to solve multiple independent linear system concurrently. The structure of the code is like this:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;LI-CODE lang="markup"&gt;    omp_set_max_active_levels( 2 );
#pragma omp parallel num_threads( 2 )
{
   mkl_set_num_threads_local( 10 );
   op A = assemble();
   auto pardiso_solver = createSolver(A);
   pardiso_solver-&amp;gt;solve(rhs, x);
}&lt;/LI-CODE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;When the outer num_threads is set to 1, everything works ok. However, when I increase it to 2. I got error code -2 in solve stage. In my test, the operator A is nothing but a 3x3 matrix:&lt;/P&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;SPAN&gt;/*&lt;/SPAN&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;SPAN&gt;A = 1 2 3&lt;/SPAN&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;SPAN&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;0 4 5&lt;/SPAN&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;SPAN&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;0 0 6&lt;/SPAN&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;SPAN&gt;*/&lt;/SPAN&gt;&lt;/DIV&gt;&lt;DIV&gt;&amp;nbsp;&lt;/DIV&gt;&lt;DIV&gt;&lt;SPAN&gt;my solver parameters are set as:&lt;/SPAN&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;LI-CODE lang="markup"&gt; _iparm[1] = 3;
 _iparm[7] = 1; 
 _iparm[34] = 0; &lt;/LI-CODE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;DIV&gt;&amp;nbsp;Could I know what could be the cause of the problem?&lt;/DIV&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Thu, 25 Jan 2024 18:37:02 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/issue-in-running-multiple-pardiso-concurrently/m-p/1566153#M35749</guid>
      <dc:creator>miaodi1987</dc:creator>
      <dc:date>2024-01-25T18:37:02Z</dc:date>
    </item>
    <item>
      <title>Re:issue in running multiple pardiso concurrently.</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/issue-in-running-multiple-pardiso-concurrently/m-p/1568151#M35765</link>
      <description>&lt;P&gt;Hello miaodi,&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;&lt;/P&gt;&lt;P&gt;Thank you for posting here.&lt;/P&gt;&lt;P&gt;Could you tell us your oneMKL version, OS version and hardware platform? As well as providing us a simple reproducer for the issue.&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;&lt;/P&gt;&lt;P&gt;Regards,&lt;/P&gt;&lt;P&gt;Ruqiu&lt;/P&gt;&lt;BR /&gt;</description>
      <pubDate>Thu, 01 Feb 2024 02:43:53 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/issue-in-running-multiple-pardiso-concurrently/m-p/1568151#M35765</guid>
      <dc:creator>Ruqiu_C_Intel</dc:creator>
      <dc:date>2024-02-01T02:43:53Z</dc:date>
    </item>
  </channel>
</rss>

