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    <title>topic Matrix Orthogonalization Routine in Intel® oneAPI Math Kernel Library</title>
    <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Matrix-Orthogonalization-Routine/m-p/852496#M6658</link>
    <description>Hey guys,
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;The lab I work with is trying to port some of their old code that uses the NAG libraries over to a new supercomputer cluster that does not have NAG but has Intel MKL. Most of the general LAPACK and BLAS routines have a simple counterpart, but there is one NAG routine that I was wondering if MKL had something similar to.&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;The routine in NAG is called: F05AAF. It takes in a set of vectors and orthogonalizes them. We use it to orthogonalize a matrix in our code. The MKL libraries have orthogonal factorization routines, but I do not believe that it is the same thing as matrix orthogonalization (NAG uses the Gram-Schmidt process).&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;Here is the NAG description of F05AAF:http://www.nag.co.uk/numeric/Fl/manual/pdf/F05/f05aaf.pdf&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;Could anybody shine some light on whether MKL has this capability?&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;Thanks.&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;</description>
    <pubDate>Fri, 17 Jul 2009 23:25:12 GMT</pubDate>
    <dc:creator>yelu1220</dc:creator>
    <dc:date>2009-07-17T23:25:12Z</dc:date>
    <item>
      <title>Matrix Orthogonalization Routine</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Matrix-Orthogonalization-Routine/m-p/852496#M6658</link>
      <description>Hey guys,
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;The lab I work with is trying to port some of their old code that uses the NAG libraries over to a new supercomputer cluster that does not have NAG but has Intel MKL. Most of the general LAPACK and BLAS routines have a simple counterpart, but there is one NAG routine that I was wondering if MKL had something similar to.&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;The routine in NAG is called: F05AAF. It takes in a set of vectors and orthogonalizes them. We use it to orthogonalize a matrix in our code. The MKL libraries have orthogonal factorization routines, but I do not believe that it is the same thing as matrix orthogonalization (NAG uses the Gram-Schmidt process).&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;Here is the NAG description of F05AAF:http://www.nag.co.uk/numeric/Fl/manual/pdf/F05/f05aaf.pdf&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;Could anybody shine some light on whether MKL has this capability?&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;Thanks.&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;</description>
      <pubDate>Fri, 17 Jul 2009 23:25:12 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Matrix-Orthogonalization-Routine/m-p/852496#M6658</guid>
      <dc:creator>yelu1220</dc:creator>
      <dc:date>2009-07-17T23:25:12Z</dc:date>
    </item>
    <item>
      <title>Re: Matrix Orthogonalization Routine</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Matrix-Orthogonalization-Routine/m-p/852497#M6659</link>
      <description>&lt;DIV style="margin:0px;"&gt;&lt;/DIV&gt;
&lt;BR /&gt;Hello,&lt;BR /&gt;&lt;BR /&gt;I'm an MKL LAPACK engineer. MKL doesn't have matrix orthogonalization routine. Generally, MKL supports LAPACK standard, which is described at &lt;A href="http://www.netlib.org/lapack"&gt;www.netlib.org/lapack&lt;/A&gt;,but this routine isn't standard. Anyway, we can introduce functionality in MKL if it's useful for our customers.&lt;BR /&gt;&lt;BR /&gt;Michael.</description>
      <pubDate>Mon, 20 Jul 2009 10:38:33 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Matrix-Orthogonalization-Routine/m-p/852497#M6659</guid>
      <dc:creator>Michael_C_Intel4</dc:creator>
      <dc:date>2009-07-20T10:38:33Z</dc:date>
    </item>
    <item>
      <title>Re: Matrix Orthogonalization Routine</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Matrix-Orthogonalization-Routine/m-p/852498#M6660</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/436059"&gt;yelu1220&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;Hey guys,
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;The lab I work with is trying to port some of their old code that uses the NAG libraries over to a new supercomputer cluster that does not have NAG but has Intel MKL. Most of the general LAPACK and BLAS routines have a simple counterpart, but there is one NAG routine that I was wondering if MKL had something similar to.&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;The routine in NAG is called: F05AAF. It takes in a set of vectors and orthogonalizes them. We use it to orthogonalize a matrix in our code. The MKL libraries have orthogonal factorization routines, but I do not believe that it is the same thing as matrix orthogonalization (NAG uses the Gram-Schmidt process).&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;Here is the NAG description of F05AAF:http://www.nag.co.uk/numeric/Fl/manual/pdf/F05/f05aaf.pdf&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;Could anybody shine some light on whether MKL has this capability?&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;DIV&gt;Thanks.&lt;/DIV&gt;
&lt;DIV&gt;&lt;BR /&gt;&lt;/DIV&gt;
&lt;/EM&gt;&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;
&lt;BR /&gt;&lt;BR /&gt;&lt;!--[if gte mso 9]&gt;&lt;xml&gt; &lt;w:WordDocument&gt; &lt;w:View&gt;Normal&lt;/w:View&gt; &lt;w:Zoom&gt;0&lt;/w:Zoom&gt; &lt;w:PunctuationKerning /&gt; &lt;w:ValidateAgainstSchemas /&gt; &lt;w:SaveIfXMLInvalid&gt;false&lt;/w:SaveIfXMLInvalid&gt; &lt;w:IgnoreMixedContent&gt;false&lt;/w:IgnoreMixedContent&gt; &lt;w:AlwaysShowPlaceholderText&gt;false&lt;/w:AlwaysShowPlaceholderText&gt; &lt;w:Compatibility&gt; &lt;w:BreakWrappedTables /&gt; &lt;w:SnapToGridInCell /&gt; &lt;w:WrapTextWithPunct /&gt; &lt;w:UseAsianBreakRules /&gt; &lt;w:DontGrowAutofit /&gt; &lt;/w:Compatibility&gt; &lt;w:BrowserLevel&gt;MicrosoftInternetExplorer4&lt;/w:BrowserLevel&gt; &lt;/w:WordDocument&gt; &lt;/xml&gt;&lt;![endif]--&gt;&lt;!--[if gte mso 9]&gt;&lt;xml&gt; &lt;w:LatentStyles DefLockedState="false" LatentStyleCount="156"&gt; &lt;/w:LatentStyles&gt; &lt;/xml&gt;&lt;![endif]--&gt; &lt;!--[if gte mso 10]&gt; &lt;mce:style&gt;&lt;!   /* Style Definitions */  table.MsoNormalTable 	{mso-style-name:"Table Normal"; 	mso-tstyle-rowband-size:0; 	mso-tstyle-colband-size:0; 	mso-style-noshow:yes; 	mso-style-parent:""; 	mso-padding-alt:0in 5.4pt 0in 5.4pt; 	mso-para-margin:0in; 	mso-para-margin-bottom:.0001pt; 	mso-pagination:widow-orphan; 	font-size:10.0pt; 	font-family:"Times New Roman"; 	mso-ansi-language:#0400; 	mso-fareast-language:#0400; 	mso-bidi-language:#0400;} --&gt; &lt;!--[endif]--&gt;
&lt;P class="MsoNormal"&gt;&lt;SPAN style="font-size: 10pt; font-family: Verdana; color: maroon;"&gt;Yelu1220,&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="MsoNormal"&gt;&lt;SPAN style="font-size: 10pt; font-family: Verdana; color: maroon;"&gt;We &lt;/SPAN&gt;&lt;SPAN style="font-size: 10pt; font-family: Verdana; color: #333399;" lang="RU"&gt;would recommend you submit the issue against MKL to Premier support( &lt;/SPAN&gt;&lt;SPAN style="font-size: 10pt; font-family: Verdana;" lang="RU"&gt;&lt;A href="https://premier.intel.com/"&gt;https://premier.intel.com/&lt;/A&gt;&lt;SPAN style="color: #333399;"&gt; )&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="MsoNormal"&gt;--Gennady&lt;SPAN style="font-size: 10pt; font-family: Verdana;" lang="RU"&gt;&lt;/SPAN&gt;&lt;/P&gt;
&lt;BR /&gt;</description>
      <pubDate>Mon, 03 Aug 2009 13:47:43 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Matrix-Orthogonalization-Routine/m-p/852498#M6660</guid>
      <dc:creator>Gennady_F_Intel</dc:creator>
      <dc:date>2009-08-03T13:47:43Z</dc:date>
    </item>
    <item>
      <title>Re: Matrix Orthogonalization Routine</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Matrix-Orthogonalization-Routine/m-p/852499#M6661</link>
      <description>&lt;P&gt;&lt;BR /&gt;Hi, &lt;/P&gt;&lt;P&gt;For such request, MKL LAPACK functionality can be used:&lt;/P&gt;&lt;P&gt;If we consider QR factorization of the M-by-N (M&amp;gt;N) matrx A=Q*R in the form where Q is square M-by-M matrix and R is an upper triangular M-by-N matrix. The equality A=Q*R can be re-written also as a product Q1*R1 where Q1 is a rectangular M-by-N submatrix of the matrix Q and R1 is M-by-M submatrix of the R. Let us note that columns of Q1 are orthonormal (they are orthogonal to each other and have norms equal to 1). The equality A=Q1*R1 can be treated as every column of A is a linear combination of Q1 columns, i.e. they span the same linear space. In other words, columns of Q1 is nothing else but a result of ortogonalization of columns A. &lt;/P&gt;&lt;P&gt;Of course, cases where R degenerates should be cosnsidered with some care and R must be trapezoidal if rank(A) is less than N.&lt;/P&gt;&lt;P&gt;QR functionality of MKL does not give Q directly- after calling DGEQRF a function DORGQR must be called.&lt;/P&gt;&lt;P&gt;DGEQPF might be useful for degenerate cases.&lt;/P&gt;&lt;P&gt;how does this works for you? &lt;/P&gt;&lt;P&gt;Thanks,&lt;BR /&gt;Chao &lt;/P&gt;</description>
      <pubDate>Tue, 29 Mar 2011 01:28:30 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Matrix-Orthogonalization-Routine/m-p/852499#M6661</guid>
      <dc:creator>Chao_Y_Intel</dc:creator>
      <dc:date>2011-03-29T01:28:30Z</dc:date>
    </item>
    <item>
      <title>Re: Matrix Orthogonalization Routine</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Matrix-Orthogonalization-Routine/m-p/852500#M6662</link>
      <description>&lt;P&gt;Hi, &lt;/P&gt;&lt;P&gt;For such request, MKL LAPACK functionality can be used:&lt;/P&gt;&lt;P&gt;If we consider QR factorization of the M-by-N (M&amp;gt;N) matrx A=Q*R in the form where Q is square M-by-M matrix and R is an upper triangular M-by-N matrix. The equality A=Q*R can be re-written also as a product Q1*R1 where Q1 is a rectangular M-by-N submatrix of the matrix Q and R1 is M-by-M submatrix of the R. Let us note that columns of Q1 are orthonormal (they are orthogonal to each other and have norms equal to 1). The equality A=Q1*R1 can be treated as every column of A is a linear combination of Q1 columns, i.e. they span the same linear space. In other words, columns of Q1 is nothing else but a result of ortogonalization of columns A. &lt;/P&gt;&lt;P&gt;Of course, cases where R degenerates should be cosnsidered with some care and R must be trapezoidal if rank(A) is less than N.&lt;/P&gt;&lt;P&gt;QR functionality of MKL does not give Q directly- after calling DGEQRF a function DORGQR must be called.&lt;/P&gt;&lt;P&gt;DGEQPF might be useful for degenerate cases.&lt;/P&gt;&lt;P&gt;how does this works for you? &lt;/P&gt;&lt;P&gt;Thanks,&lt;BR /&gt;Chao &lt;/P&gt;</description>
      <pubDate>Tue, 29 Mar 2011 01:32:58 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Matrix-Orthogonalization-Routine/m-p/852500#M6662</guid>
      <dc:creator>Chao_Y_Intel</dc:creator>
      <dc:date>2011-03-29T01:32:58Z</dc:date>
    </item>
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