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<p>Provides a QR factorization using a block-based approach.  
<a href="#details">More...</a></p>
<div class="textblock"><code>#include &lt;utility&gt;</code><br/>
<code>#include &lt;iostream&gt;</code><br/>
<code>#include &lt;fstream&gt;</code><br/>
<code>#include &lt;string&gt;</code><br/>
<code>#include &lt;algorithm&gt;</code><br/>
<code>#include &lt;vector&gt;</code><br/>
<code>#include &lt;math.h&gt;</code><br/>
<code>#include &lt;cmath&gt;</code><br/>
<code>#include &quot;boost/numeric/ublas/vector.hpp&quot;</code><br/>
<code>#include &quot;boost/numeric/ublas/matrix.hpp&quot;</code><br/>
<code>#include &quot;boost/numeric/ublas/matrix_proxy.hpp&quot;</code><br/>
<code>#include &quot;boost/numeric/ublas/vector_proxy.hpp&quot;</code><br/>
<code>#include &quot;boost/numeric/ublas/io.hpp&quot;</code><br/>
<code>#include &quot;boost/numeric/ublas/matrix_expression.hpp&quot;</code><br/>
<code>#include &quot;<a class="el" href="matrix_8hpp_source.html">viennacl/matrix.hpp</a>&quot;</code><br/>
<code>#include &quot;<a class="el" href="matrix__proxy_8hpp_source.html">viennacl/matrix_proxy.hpp</a>&quot;</code><br/>
<code>#include &quot;<a class="el" href="prod_8hpp_source.html">viennacl/linalg/prod.hpp</a>&quot;</code><br/>
<code>#include &quot;<a class="el" href="range_8hpp_source.html">viennacl/range.hpp</a>&quot;</code><br/>
</div>
<p><a href="qr_8hpp_source.html">Go to the source code of this file.</a></p>
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<tr class="memitem:a0481a094460753dd7fb519c9dda3bdc1"><td class="memTemplParams" colspan="2">template&lt;typename MatrixType , typename VectorType &gt; </td></tr>
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<tr class="memdesc:a600f0692e7550cee41cc6382337cd8c5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Implementation of inplace-QR factorization for a general Boost.uBLAS compatible matrix A.  <a href="#a600f0692e7550cee41cc6382337cd8c5">More...</a><br/></td></tr>
<tr class="separator:a600f0692e7550cee41cc6382337cd8c5"><td class="memSeparator" colspan="2">&#160;</td></tr>
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<tr class="memdesc:ad5d436e9fd57a66afe69f56d78d22eeb"><td class="mdescLeft">&#160;</td><td class="mdescRight">Implementation of a OpenCL-only QR factorization for GPUs (or multi-core CPU). DEPRECATED! Use only if you're curious and interested in playing a bit with a GPU-only implementation.  <a href="#ad5d436e9fd57a66afe69f56d78d22eeb">More...</a><br/></td></tr>
<tr class="separator:ad5d436e9fd57a66afe69f56d78d22eeb"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa3b53a769e6ce29affb7401b9118fde3"><td class="memTemplParams" colspan="2">template&lt;typename MatrixType &gt; </td></tr>
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<tr class="memdesc:aa3b53a769e6ce29affb7401b9118fde3"><td class="mdescLeft">&#160;</td><td class="mdescRight">Implementation of a hybrid QR factorization using uBLAS on the CPU and ViennaCL for GPUs (or multi-core CPU)  <a href="#aa3b53a769e6ce29affb7401b9118fde3">More...</a><br/></td></tr>
<tr class="separator:aa3b53a769e6ce29affb7401b9118fde3"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a76fc8bf8f5a20c576b7ddbad32d3e56d"><td class="memTemplParams" colspan="2">template&lt;typename MatrixType , typename VectorType &gt; </td></tr>
<tr class="memitem:a76fc8bf8f5a20c576b7ddbad32d3e56d"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespaceviennacl_1_1linalg.html#a76fc8bf8f5a20c576b7ddbad32d3e56d">viennacl::linalg::recoverQ</a> (MatrixType const &amp;A, VectorType const &amp;betas, MatrixType &amp;Q, MatrixType &amp;R)</td></tr>
<tr class="separator:a76fc8bf8f5a20c576b7ddbad32d3e56d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adf77bb0fe92ef09522d0458ee9df03db"><td class="memTemplParams" colspan="2">template&lt;typename MatrixType , typename VectorType1 , typename VectorType2 &gt; </td></tr>
<tr class="memitem:adf77bb0fe92ef09522d0458ee9df03db"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespaceviennacl_1_1linalg.html#adf77bb0fe92ef09522d0458ee9df03db">viennacl::linalg::inplace_qr_apply_trans_Q</a> (MatrixType const &amp;A, VectorType1 const &amp;betas, VectorType2 &amp;b)</td></tr>
<tr class="memdesc:adf77bb0fe92ef09522d0458ee9df03db"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes Q^T b, where Q is an implicit orthogonal matrix defined via its Householder reflectors stored in A.  <a href="#adf77bb0fe92ef09522d0458ee9df03db">More...</a><br/></td></tr>
<tr class="separator:adf77bb0fe92ef09522d0458ee9df03db"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa926ae9008c3343c337f2aa5a90e8734"><td class="memTemplParams" colspan="2">template&lt;typename T , typename F , unsigned int ALIGNMENT, typename VectorType1 , unsigned int A2&gt; </td></tr>
<tr class="memitem:aa926ae9008c3343c337f2aa5a90e8734"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespaceviennacl_1_1linalg.html#aa926ae9008c3343c337f2aa5a90e8734">viennacl::linalg::inplace_qr_apply_trans_Q</a> (<a class="el" href="classviennacl_1_1matrix.html">viennacl::matrix</a>&lt; T, F, ALIGNMENT &gt; const &amp;A, VectorType1 const &amp;betas, <a class="el" href="classviennacl_1_1vector.html">viennacl::vector</a>&lt; T, A2 &gt; &amp;b)</td></tr>
<tr class="separator:aa926ae9008c3343c337f2aa5a90e8734"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a83f573386903bae3a5379ab4cbfc5e2d"><td class="memTemplParams" colspan="2">template&lt;typename T , typename F , unsigned int ALIGNMENT&gt; </td></tr>
<tr class="memitem:a83f573386903bae3a5379ab4cbfc5e2d"><td class="memTemplItemLeft" align="right" valign="top">std::vector&lt; T &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespaceviennacl_1_1linalg.html#a83f573386903bae3a5379ab4cbfc5e2d">viennacl::linalg::inplace_qr</a> (<a class="el" href="classviennacl_1_1matrix.html">viennacl::matrix</a>&lt; T, F, ALIGNMENT &gt; &amp;A, vcl_size_t block_size=16)</td></tr>
<tr class="memdesc:a83f573386903bae3a5379ab4cbfc5e2d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Overload of inplace-QR factorization of a ViennaCL matrix A.  <a href="#a83f573386903bae3a5379ab4cbfc5e2d">More...</a><br/></td></tr>
<tr class="separator:a83f573386903bae3a5379ab4cbfc5e2d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9728d85f4f7307ed9096524de8c77cdc"><td class="memTemplParams" colspan="2">template&lt;typename MatrixType &gt; </td></tr>
<tr class="memitem:a9728d85f4f7307ed9096524de8c77cdc"><td class="memTemplItemLeft" align="right" valign="top">std::vector&lt; typename <br class="typebreak"/>
MatrixType::value_type &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespaceviennacl_1_1linalg.html#a9728d85f4f7307ed9096524de8c77cdc">viennacl::linalg::inplace_qr</a> (MatrixType &amp;A, vcl_size_t block_size=16)</td></tr>
<tr class="memdesc:a9728d85f4f7307ed9096524de8c77cdc"><td class="mdescLeft">&#160;</td><td class="mdescRight">Overload of inplace-QR factorization for a general Boost.uBLAS compatible matrix A.  <a href="#a9728d85f4f7307ed9096524de8c77cdc">More...</a><br/></td></tr>
<tr class="separator:a9728d85f4f7307ed9096524de8c77cdc"><td class="memSeparator" colspan="2">&#160;</td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Provides a QR factorization using a block-based approach. </p>

<p>Definition in file <a class="el" href="qr_8hpp_source.html">qr.hpp</a>.</p>
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