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    <title>topic Cholesky Decomposition using ScaLAPACK and Intel's Fortran Compiler in Intel® oneAPI Math Kernel Library</title>
    <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Cholesky-Decomposition-using-ScaLAPACK-and-Intel-s-Fortran/m-p/994404#M18210</link>
    <description>&lt;DIV&gt;Hi, I am trying to implement an parallel Cholesky decomposition in a fortran code that I am writing. I have seen that the Intel fortran compiler has ScaLAPACK in its libraries and was wondering if anyone out there has used this, and if they have any examples of doing the Cholesky factorization for a positive definite matrix in parallel using Fortran. Any help would be great, as I am just starting out with even learning parallel programming. Thanks.&lt;/DIV&gt;</description>
    <pubDate>Wed, 09 Mar 2005 07:24:10 GMT</pubDate>
    <dc:creator>philipdc78</dc:creator>
    <dc:date>2005-03-09T07:24:10Z</dc:date>
    <item>
      <title>Cholesky Decomposition using ScaLAPACK and Intel's Fortran Compiler</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Cholesky-Decomposition-using-ScaLAPACK-and-Intel-s-Fortran/m-p/994404#M18210</link>
      <description>&lt;DIV&gt;Hi, I am trying to implement an parallel Cholesky decomposition in a fortran code that I am writing. I have seen that the Intel fortran compiler has ScaLAPACK in its libraries and was wondering if anyone out there has used this, and if they have any examples of doing the Cholesky factorization for a positive definite matrix in parallel using Fortran. Any help would be great, as I am just starting out with even learning parallel programming. Thanks.&lt;/DIV&gt;</description>
      <pubDate>Wed, 09 Mar 2005 07:24:10 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Cholesky-Decomposition-using-ScaLAPACK-and-Intel-s-Fortran/m-p/994404#M18210</guid>
      <dc:creator>philipdc78</dc:creator>
      <dc:date>2005-03-09T07:24:10Z</dc:date>
    </item>
    <item>
      <title>Re: Cholesky Decomposition using ScaLAPACK and Intel's Fortran</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Cholesky-Decomposition-using-ScaLAPACK-and-Intel-s-Fortran/m-p/994405#M18211</link>
      <description>&lt;DIV&gt;ScaLAPACK is actually part of the Intel Math Kernel Library, not the Intel Fortran Compiler. I am moving your thread over to the MKL forum for response.&lt;/DIV&gt;</description>
      <pubDate>Thu, 10 Mar 2005 00:01:35 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Cholesky-Decomposition-using-ScaLAPACK-and-Intel-s-Fortran/m-p/994405#M18211</guid>
      <dc:creator>Steven_L_Intel1</dc:creator>
      <dc:date>2005-03-10T00:01:35Z</dc:date>
    </item>
    <item>
      <title>Re: Cholesky Decomposition using ScaLAPACK and Intel's Fortran</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Cholesky-Decomposition-using-ScaLAPACK-and-Intel-s-Fortran/m-p/994406#M18212</link>
      <description>Well, it depends on what you are trying to do here. If you need a parallel implementation of Cholesky decomposition, you can simply call the LAPACK function in MKL, DPOTRF. If, on the other hand you want to understand writing the code for Cholesky decomposition and try to parallelize that, I would recommend either Numerical Recipes or going to &lt;A href="https://community.intel.com/www.netlib.org" target="_blank"&gt;www.netlib.org&lt;/A&gt; and get the LAPACK source code and understand it.

As I am writing this I realize you may be interested in the parallelization of this code for a cluster. The ScaLAPACK code, at the same netlib site, might be of help there.

Bruce</description>
      <pubDate>Fri, 11 Mar 2005 03:27:13 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Cholesky-Decomposition-using-ScaLAPACK-and-Intel-s-Fortran/m-p/994406#M18212</guid>
      <dc:creator>Intel_C_Intel</dc:creator>
      <dc:date>2005-03-11T03:27:13Z</dc:date>
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