<?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: MKL 7.0 Beta PARADISO: Cholesky factors in Intel® oneAPI Math Kernel Library</title>
    <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965414#M16176</link>
    <description>&lt;DIV&gt;diagonal elements of "C" are needed for computing the determinant of the A matrix (along with some other things). &lt;/DIV&gt;</description>
    <pubDate>Sun, 11 Apr 2004 05:42:03 GMT</pubDate>
    <dc:creator>Intel_C_Intel</dc:creator>
    <dc:date>2004-04-11T05:42:03Z</dc:date>
    <item>
      <title>MKL 7.0 Beta PARADISO: Cholesky factors</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965412#M16174</link>
      <description>&lt;DIV&gt;&lt;/DIV&gt;
&lt;DIV&gt;Is it possible to access cholesky factors of A (= C*C')?&lt;/DIV&gt;</description>
      <pubDate>Sat, 27 Mar 2004 23:33:03 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965412#M16174</guid>
      <dc:creator>Intel_C_Intel</dc:creator>
      <dc:date>2004-03-27T23:33:03Z</dc:date>
    </item>
    <item>
      <title>Re: MKL 7.0 Beta PARADISO: Cholesky factors</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965413#M16175</link>
      <description>&lt;P&gt;I have gone back to the developers of sparse solver and they would like to understand why you want this particular quantity. Clearly it would be possible to add such functionality, but if they can understand the unlying motivation for this they may be able to address that.&lt;/P&gt;
&lt;P&gt;Bruce&lt;/P&gt;</description>
      <pubDate>Thu, 08 Apr 2004 06:13:19 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965413#M16175</guid>
      <dc:creator>Intel_C_Intel</dc:creator>
      <dc:date>2004-04-08T06:13:19Z</dc:date>
    </item>
    <item>
      <title>Re: MKL 7.0 Beta PARADISO: Cholesky factors</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965414#M16176</link>
      <description>&lt;DIV&gt;diagonal elements of "C" are needed for computing the determinant of the A matrix (along with some other things). &lt;/DIV&gt;</description>
      <pubDate>Sun, 11 Apr 2004 05:42:03 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965414#M16176</guid>
      <dc:creator>Intel_C_Intel</dc:creator>
      <dc:date>2004-04-11T05:42:03Z</dc:date>
    </item>
    <item>
      <title>Re: MKL 7.0 Beta PARADISO: Cholesky factors</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965415#M16177</link>
      <description>&lt;P&gt;There are many situations where the factors of the Cholesky decompositon are needed. One of them, very important for many number smashers, regards the solution of the generalized eigenvalue problem:&lt;/P&gt;
&lt;P&gt;find (L, X) (L real and X vector) such that&lt;/P&gt;
&lt;P&gt;K X = L M X&lt;/P&gt;
&lt;P&gt;where K,M are symmetric positive definite matrices.&lt;/P&gt;
&lt;P&gt;The generalized problem could be transformed into a classical eigenvalue problem, retaining the symmetry and posiveness of the matrix operator A:&lt;/P&gt;
&lt;P&gt;A X = 1/L X&lt;/P&gt;
&lt;P&gt;where A depends on K,M. Using A Lanczos or a subspace iteration method for this problem (when coming from the generalized one) requires access to the factors of K (or M).&lt;/P&gt;
&lt;P&gt;Please note that generalized eigenvalue analysis is a very common task in many engineering sciences.&lt;/P&gt;
&lt;P&gt;&lt;/P&gt;
&lt;DIV&gt;&lt;/DIV&gt;</description>
      <pubDate>Tue, 13 Apr 2004 20:28:30 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965415#M16177</guid>
      <dc:creator>igino-pitacco</dc:creator>
      <dc:date>2004-04-13T20:28:30Z</dc:date>
    </item>
    <item>
      <title>Re: MKL 7.0 Beta PARADISO: Cholesky factors</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965416#M16178</link>
      <description>&lt;P&gt;This is exactly the information I need. I can't say for certain when I will have more information on this butI will forward this to the developers.&lt;/P&gt;
&lt;P&gt;Bruce&lt;/P&gt;
&lt;DIV&gt;&lt;/DIV&gt;</description>
      <pubDate>Tue, 13 Apr 2004 22:10:00 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965416#M16178</guid>
      <dc:creator>Intel_C_Intel</dc:creator>
      <dc:date>2004-04-13T22:10:00Z</dc:date>
    </item>
    <item>
      <title>Re: MKL 7.0 Beta PARADISO: Cholesky factors</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965417#M16179</link>
      <description>&lt;P&gt;has there been any development re. sparse cholesky ? &lt;/P&gt;
&lt;P&gt;Thank you. &lt;/P&gt;
&lt;P&gt;mepa&lt;/P&gt;</description>
      <pubDate>Sat, 19 Jan 2008 23:38:44 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/MKL-7-0-Beta-PARADISO-Cholesky-factors/m-p/965417#M16179</guid>
      <dc:creator>mepad_si</dc:creator>
      <dc:date>2008-01-19T23:38:44Z</dc:date>
    </item>
  </channel>
</rss>

