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    <title>topic Re: Iterative methods for sparse least square problem in Intel® oneAPI Math Kernel Library</title>
    <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Iterative-methods-for-sparse-least-square-problem/m-p/896508#M10909</link>
    <description>&lt;BR /&gt;MKL doesn't have any plan to include iterative methods for the sparse least square problems. PARDISO doesn't have such functioanality as well.&lt;BR /&gt;&lt;BR /&gt;But you could try the following way. It can work if your matrix has full rank.It is known thatthe least square problem for A*x = fis equivalent to finding the solution of the system(A^T * A) x = A^T *f. MKL Sparse BLAS provides routines for computing product of two sparse matrices stored in the compressed sparse row format. The result matrix can be stored as a dense matrix orcompressed sparse row matrix. The vector A^T*f can be computed with the help of MKL sparse BLAS as well. After that PARDISO or LAPACK solver can be used for finding the solution(A^T * A) x = A^T *f.&lt;BR /&gt;&lt;BR /&gt;All the best&lt;BR /&gt;Sergey&lt;BR /&gt;</description>
    <pubDate>Thu, 26 Feb 2009 09:51:49 GMT</pubDate>
    <dc:creator>Sergey_K_Intel1</dc:creator>
    <dc:date>2009-02-26T09:51:49Z</dc:date>
    <item>
      <title>Iterative methods for sparse least square problem</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Iterative-methods-for-sparse-least-square-problem/m-p/896507#M10908</link>
      <description>Does Intel have any plan to include iterative methods for the sparse least square problem such as LSQR, SYMMLQ, and MINRES into MKL? (or PARADISO has already included these functions?)</description>
      <pubDate>Mon, 23 Feb 2009 22:03:12 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Iterative-methods-for-sparse-least-square-problem/m-p/896507#M10908</guid>
      <dc:creator>heiga</dc:creator>
      <dc:date>2009-02-23T22:03:12Z</dc:date>
    </item>
    <item>
      <title>Re: Iterative methods for sparse least square problem</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Iterative-methods-for-sparse-least-square-problem/m-p/896508#M10909</link>
      <description>&lt;BR /&gt;MKL doesn't have any plan to include iterative methods for the sparse least square problems. PARDISO doesn't have such functioanality as well.&lt;BR /&gt;&lt;BR /&gt;But you could try the following way. It can work if your matrix has full rank.It is known thatthe least square problem for A*x = fis equivalent to finding the solution of the system(A^T * A) x = A^T *f. MKL Sparse BLAS provides routines for computing product of two sparse matrices stored in the compressed sparse row format. The result matrix can be stored as a dense matrix orcompressed sparse row matrix. The vector A^T*f can be computed with the help of MKL sparse BLAS as well. After that PARDISO or LAPACK solver can be used for finding the solution(A^T * A) x = A^T *f.&lt;BR /&gt;&lt;BR /&gt;All the best&lt;BR /&gt;Sergey&lt;BR /&gt;</description>
      <pubDate>Thu, 26 Feb 2009 09:51:49 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Iterative-methods-for-sparse-least-square-problem/m-p/896508#M10909</guid>
      <dc:creator>Sergey_K_Intel1</dc:creator>
      <dc:date>2009-02-26T09:51:49Z</dc:date>
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    <item>
      <title>Re: Iterative methods for sparse least square problem</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Iterative-methods-for-sparse-least-square-problem/m-p/896509#M10910</link>
      <description>&lt;DIV style="margin:0px;"&gt;
&lt;DIV id="quote_reply" style="width: 100%; margin-top: 5px;"&gt;
&lt;DIV style="margin-left:2px;margin-right:2px;"&gt;Quoting - &lt;A href="https://community.intel.com/en-us/profile/93645"&gt;Sergey Kuznetsov (Intel)&lt;/A&gt;&lt;/DIV&gt;
&lt;DIV style="background-color:#E5E5E5; padding:5px;border: 1px; border-style: inset;margin-left:2px;margin-right:2px;"&gt;&lt;EM&gt;But you could try the following way. It can work if your matrix has full rank.It is known thatthe least square problem for A*x = fis equivalent to finding the solution of the system(A^T * A) x = A^T *f. MKL Sparse BLAS provides routines for computing product of two sparse matrices stored in the compressed sparse row format. The result matrix can be stored as a dense matrix orcompressed sparse row matrix. The vector A^T*f can be computed with the help of MKL sparse BLAS as well. After that PARDISO or LAPACK solver can be used for finding the solution(A^T * A) x = A^T *f. &lt;BR /&gt;&lt;/EM&gt;&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;BR /&gt;Thank you very much for your reply. Unfortunately, my problem doesn't have full rank. So I'm currently using open-source version of MINRES.&lt;BR /&gt;</description>
      <pubDate>Thu, 26 Feb 2009 10:53:20 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Iterative-methods-for-sparse-least-square-problem/m-p/896509#M10910</guid>
      <dc:creator>heiga</dc:creator>
      <dc:date>2009-02-26T10:53:20Z</dc:date>
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