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<div class="title">iterative_operations.hpp</div> </div>
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<a href="host__based_2iterative__operations_8hpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="preprocessor">#ifndef VIENNACL_LINALG_HOST_BASED_ITERATIVE_OPERATIONS_HPP_</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="preprocessor">#define VIENNACL_LINALG_HOST_BASED_ITERATIVE_OPERATIONS_HPP_</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> </div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">/* =========================================================================</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> Copyright (c) 2010-2016, Institute for Microelectronics,</span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> Institute for Analysis and Scientific Computing,</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> TU Wien.</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> Portions of this software are copyright by UChicago Argonne, LLC.</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"></span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> -----------------</span></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> ViennaCL - The Vienna Computing Library</span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> -----------------</span></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"></span></div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> Project Head: Karl Rupp rupp@iue.tuwien.ac.at</span></div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"></span></div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> (A list of authors and contributors can be found in the manual)</span></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"></span></div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> License: MIT (X11), see file LICENSE in the base directory</span></div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment">============================================================================= */</span></div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include <cmath></span></div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include <algorithm></span> <span class="comment">//for std::max and std::min</span></div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="forwards_8h.html">viennacl/forwards.h</a>"</span></div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="scalar_8hpp.html">viennacl/scalar.hpp</a>"</span></div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="tools_8hpp.html">viennacl/tools/tools.hpp</a>"</span></div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include "<a class="code" href="predicate_8hpp.html">viennacl/meta/predicate.hpp</a>"</span></div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include "<a class="code" href="enable__if_8hpp.html">viennacl/meta/enable_if.hpp</a>"</span></div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include "<a class="code" href="size_8hpp.html">viennacl/traits/size.hpp</a>"</span></div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#include "<a class="code" href="start_8hpp.html">viennacl/traits/start.hpp</a>"</span></div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="preprocessor">#include "<a class="code" href="linalg_2host__based_2common_8hpp.html">viennacl/linalg/host_based/common.hpp</a>"</span></div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include "<a class="code" href="op__applier_8hpp.html">viennacl/linalg/detail/op_applier.hpp</a>"</span></div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="preprocessor">#include "<a class="code" href="stride_8hpp.html">viennacl/traits/stride.hpp</a>"</span></div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="comment">// Minimum vector size for using OpenMP on vector operations:</span></div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="preprocessor">#ifndef VIENNACL_OPENMP_VECTOR_MIN_SIZE</span></div>
<div class="line"><a name="l00042"></a><span class="lineno"><a class="line" href="host__based_2iterative__operations_8hpp.html#aa1b0719a06924fc82f8d8ed6c739a04d"> 42</a></span> <span class="preprocessor"> #define VIENNACL_OPENMP_VECTOR_MIN_SIZE 5000</span></div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="keyword">namespace </span>viennacl</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span> {</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="keyword">namespace </span>linalg</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span> {</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="keyword">namespace </span>host_based</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span> {</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span> </div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="keyword">namespace </span>detail</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span> {</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00061"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884"> 61</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">pipelined_prod_impl</a>(<a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * r0star,</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size,</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_offset)</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  {</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> value_type;</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  value_type * Ap_buf = detail::extract_raw_pointer<value_type>(Ap.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>()) + <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(Ap);</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  value_type <span class="keyword">const</span> * p_buf = detail::extract_raw_pointer<value_type>(p.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>()) + <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(p);</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  value_type <span class="keyword">const</span> * elements = detail::extract_raw_pointer<value_type>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a87a0ad5f26983b1c2d24ee302d886562">handle</a>());</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <span class="keyword">const</span> * row_buffer = detail::extract_raw_pointer<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#af71dec61a70e8df4f78a527aa989a106">handle1</a>());</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <span class="keyword">const</span> * col_buffer = detail::extract_raw_pointer<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a91f5145351151a66f916bdc3901206f2">handle2</a>());</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  value_type * data_buffer = detail::extract_raw_pointer<value_type>(inner_prod_buffer);</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  value_type inner_prod_ApAp = 0;</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  value_type inner_prod_pAp = 0;</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  value_type inner_prod_Ap_r0star = 0;</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordflow">for</span> (<span class="keywordtype">long</span> <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> = 0; row < static_cast<long>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>()); ++<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>)</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  {</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  value_type <a class="code" href="namespaceviennacl_1_1linalg_1_1detail_1_1spai.html#a7eeb3f2f51183bed7e6d0a1aeefc87bc">dot_prod</a> = 0;</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  value_type val_p_diag = p_buf[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>)]; <span class="comment">//likely to be loaded from cache if required again in this row</span></div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> row_end = row_buffer[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>+1];</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = row_buffer[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>]; i < row_end; ++i)</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  dot_prod += elements[i] * p_buf[col_buffer[i]];</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="comment">// update contributions for the inner products (Ap, Ap) and (p, Ap)</span></div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  Ap_buf[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>)] = dot_prod;</div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  inner_prod_ApAp += dot_prod * <a class="code" href="namespaceviennacl_1_1linalg_1_1detail_1_1spai.html#a7eeb3f2f51183bed7e6d0a1aeefc87bc">dot_prod</a>;</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  inner_prod_pAp += val_p_diag * <a class="code" href="namespaceviennacl_1_1linalg_1_1detail_1_1spai.html#a7eeb3f2f51183bed7e6d0a1aeefc87bc">dot_prod</a>;</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  inner_prod_Ap_r0star += r0star ? dot_prod * r0star[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>)] : value_type(0);</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  }</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  data_buffer[ buffer_chunk_size] = inner_prod_ApAp;</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  data_buffer[2 * buffer_chunk_size] = inner_prod_pAp;</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordflow">if</span> (r0star)</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  data_buffer[buffer_chunk_offset] = inner_prod_Ap_r0star;</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  }</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span> </div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span> </div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00112"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a60401098f6a2dea052342d94f14f1bb4"> 112</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">pipelined_prod_impl</a>(<a class="code" href="classviennacl_1_1coordinate__matrix.html">coordinate_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * r0star,</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size,</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_offset)</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  {</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> value_type;</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  value_type * Ap_buf = detail::extract_raw_pointer<value_type>(Ap.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>()) + <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(Ap);;</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  value_type <span class="keyword">const</span> * p_buf = detail::extract_raw_pointer<value_type>(p.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>()) + <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(p);;</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  value_type <span class="keyword">const</span> * elements = detail::extract_raw_pointer<value_type>(A.<a class="code" href="classviennacl_1_1coordinate__matrix.html#aeb74dd2ab673d7912a17f60777e9bf6c">handle</a>());</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <span class="keyword">const</span> * coord_buffer = detail::extract_raw_pointer<unsigned int>(A.<a class="code" href="classviennacl_1_1coordinate__matrix.html#a875b6ccacbf0df8ef48ab7f7c46244f1">handle12</a>());</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  value_type * data_buffer = detail::extract_raw_pointer<value_type>(inner_prod_buffer);</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="comment">// flush result buffer (cannot be expected to be zero)</span></div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 0; i< Ap.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>(); ++i)</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  Ap_buf[i] = 0;</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="comment">// matrix-vector product with a general COO format</span></div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 0; i < A.<a class="code" href="classviennacl_1_1coordinate__matrix.html#a04c51b826e4bae9c97a3749ee2161b87">nnz</a>(); ++i)</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  Ap_buf[coord_buffer[2*i]] += elements[i] * p_buf[coord_buffer[2*i+1]];</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span> </div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="comment">// computing the inner products (Ap, Ap) and (p, Ap):</span></div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="comment">// Note: The COO format does not allow to inject the subsequent operations into the matrix-vector product, because row and column ordering assumptions are too weak</span></div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  value_type inner_prod_ApAp = 0;</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  value_type inner_prod_pAp = 0;</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  value_type inner_prod_Ap_r0star = 0;</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 0; i<Ap.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>(); ++i)</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  {</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> value_Ap = Ap_buf[i];</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> value_p = p_buf[i];</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span> </div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  inner_prod_ApAp += value_Ap * value_Ap;</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  inner_prod_pAp += value_Ap * value_p;</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  inner_prod_Ap_r0star += r0star ? value_Ap * r0star[i] : value_type(0);</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  }</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  data_buffer[ buffer_chunk_size] = inner_prod_ApAp;</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  data_buffer[2 * buffer_chunk_size] = inner_prod_pAp;</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="keywordflow">if</span> (r0star)</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  data_buffer[buffer_chunk_offset] = inner_prod_Ap_r0star;</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  }</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00165"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a4c47c67ddce12fd93fe84c15f351b389"> 165</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">pipelined_prod_impl</a>(<a class="code" href="classviennacl_1_1ell__matrix.html">ell_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * r0star,</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size,</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_offset)</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  {</div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> value_type;</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span> </div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  value_type * Ap_buf = detail::extract_raw_pointer<value_type>(Ap.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>()) + <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(Ap);;</div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  value_type <span class="keyword">const</span> * p_buf = detail::extract_raw_pointer<value_type>(p.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>()) + <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(p);;</div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  value_type <span class="keyword">const</span> * elements = detail::extract_raw_pointer<value_type>(A.<a class="code" href="classviennacl_1_1ell__matrix.html#a7fe5450dbe53bb797938aa920d4bbb68">handle</a>());</div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <span class="keyword">const</span> * coords = detail::extract_raw_pointer<unsigned int>(A.<a class="code" href="classviennacl_1_1ell__matrix.html#a1260f11302263435b8f6de4a4c0ef4b6">handle2</a>());</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  value_type * data_buffer = detail::extract_raw_pointer<value_type>(inner_prod_buffer);</div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span> </div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  value_type inner_prod_ApAp = 0;</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  value_type inner_prod_pAp = 0;</div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  value_type inner_prod_Ap_r0star = 0;</div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> = 0; <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> < A.<a class="code" href="classviennacl_1_1ell__matrix.html#a7a37f6e784757bd80c71f800efcefc3f">size1</a>(); ++<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>)</div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  {</div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  value_type <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a> = 0;</div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  value_type val_p_diag = p_buf[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>)]; <span class="comment">//likely to be loaded from cache if required again in this row</span></div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span> </div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> item_id = 0; item_id < A.<a class="code" href="classviennacl_1_1ell__matrix.html#ae3280590756e720a8d8dacdeed4b702a">internal_maxnnz</a>(); ++item_id)</div>
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  {</div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> offset = <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> + item_id * A.<a class="code" href="classviennacl_1_1ell__matrix.html#af2e571bfc69f9f0acf3e9b19ce2b9b9f">internal_size1</a>();</div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  value_type val = elements[offset];</div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span> </div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="keywordflow">if</span> (val)</div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  sum += (p_buf[coords[offset]] * val);</div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  }</div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span> </div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  Ap_buf[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>] = <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a>;</div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  inner_prod_ApAp += sum * <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a>;</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  inner_prod_pAp += val_p_diag * <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a>;</div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  inner_prod_Ap_r0star += r0star ? sum * r0star[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>] : value_type(0);</div>
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  }</div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span> </div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  data_buffer[ buffer_chunk_size] = inner_prod_ApAp;</div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  data_buffer[2 * buffer_chunk_size] = inner_prod_pAp;</div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keywordflow">if</span> (r0star)</div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  data_buffer[buffer_chunk_offset] = inner_prod_Ap_r0star;</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  }</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span> </div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span> </div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> IndexT></div>
<div class="line"><a name="l00218"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a407ff4933c3fcf3fd01a2a3a34857ebe"> 218</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">pipelined_prod_impl</a>(<a class="code" href="classviennacl_1_1sliced__ell__matrix.html">sliced_ell_matrix<NumericT, IndexT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * r0star,</div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size,</div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_offset)</div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  {</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> value_type;</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span> </div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  value_type * Ap_buf = detail::extract_raw_pointer<value_type>(Ap.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>()) + <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(Ap);;</div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  value_type <span class="keyword">const</span> * p_buf = detail::extract_raw_pointer<value_type>(p.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>()) + <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(p);;</div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  value_type <span class="keyword">const</span> * elements = detail::extract_raw_pointer<value_type>(A.<a class="code" href="classviennacl_1_1sliced__ell__matrix.html#abbc671358c44037b7c2b22a01f17c3a7">handle</a>());</div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  IndexT <span class="keyword">const</span> * columns_per_block = detail::extract_raw_pointer<IndexT>(A.<a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a94043424c01974b2db8062f74f625825">handle1</a>());</div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  IndexT <span class="keyword">const</span> * column_indices = detail::extract_raw_pointer<IndexT>(A.<a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a31d5fa9ec25dcfeb260f7e11c4db6571">handle2</a>());</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  IndexT <span class="keyword">const</span> * block_start = detail::extract_raw_pointer<IndexT>(A.<a class="code" href="classviennacl_1_1sliced__ell__matrix.html#aa59ae796d592a679a4c6036ba84f61b0">handle3</a>());</div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  value_type * data_buffer = detail::extract_raw_pointer<value_type>(inner_prod_buffer);</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span> </div>
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> num_blocks = A.<a class="code" href="classviennacl_1_1sliced__ell__matrix.html#a16cd8194ca5b263de32f131362498d77">size1</a>() / A.<a class="code" href="classviennacl_1_1sliced__ell__matrix.html#aa9a7f4003687cae9a2af97f9fa328db5">rows_per_block</a>() + 1;</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  std::vector<value_type> result_values(A.<a class="code" href="classviennacl_1_1sliced__ell__matrix.html#aa9a7f4003687cae9a2af97f9fa328db5">rows_per_block</a>());</div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span> </div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  value_type inner_prod_ApAp = 0;</div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  value_type inner_prod_pAp = 0;</div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  value_type inner_prod_Ap_r0star = 0;</div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> block_idx = 0; block_idx < num_blocks; ++block_idx)</div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  {</div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> current_columns_per_block = columns_per_block[block_idx];</div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span> </div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i=0; i<result_values.size(); ++i)</div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  result_values[i] = 0;</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span> </div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="keywordflow">for</span> (IndexT column_entry_index = 0;</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  column_entry_index < current_columns_per_block;</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  ++column_entry_index)</div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  {</div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> stride_start = block_start[block_idx] + column_entry_index * A.<a class="code" href="classviennacl_1_1sliced__ell__matrix.html#aa9a7f4003687cae9a2af97f9fa328db5">rows_per_block</a>();</div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="comment">// Note: This for-loop may be unrolled by hand for exploiting vectorization</span></div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="comment">// Careful benchmarking recommended first, memory channels may be saturated already!</span></div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <span class="keywordflow">for</span> (IndexT row_in_block = 0; row_in_block < A.<a class="code" href="classviennacl_1_1sliced__ell__matrix.html#aa9a7f4003687cae9a2af97f9fa328db5">rows_per_block</a>(); ++row_in_block)</div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  {</div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  value_type val = elements[stride_start + row_in_block];</div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span> </div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  result_values[row_in_block] += val ? p_buf[column_indices[stride_start + row_in_block]] * val : 0;</div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  }</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  }</div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span> </div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> first_row_in_matrix = block_idx * A.<a class="code" href="classviennacl_1_1sliced__ell__matrix.html#aa9a7f4003687cae9a2af97f9fa328db5">rows_per_block</a>();</div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="keywordflow">for</span> (IndexT row_in_block = 0; row_in_block < A.<a class="code" href="classviennacl_1_1sliced__ell__matrix.html#aa9a7f4003687cae9a2af97f9fa328db5">rows_per_block</a>(); ++row_in_block)</div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  {</div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> = first_row_in_matrix + row_in_block;</div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <span class="keywordflow">if</span> (row < Ap.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>())</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  {</div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  value_type row_result = result_values[row_in_block];</div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span> </div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  Ap_buf[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>] = row_result;</div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  inner_prod_ApAp += row_result * row_result;</div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  inner_prod_pAp += p_buf[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>] * row_result;</div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  inner_prod_Ap_r0star += r0star ? row_result * r0star[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>] : value_type(0);</div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  }</div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  }</div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  }</div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span> </div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  data_buffer[ buffer_chunk_size] = inner_prod_ApAp;</div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  data_buffer[2 * buffer_chunk_size] = inner_prod_pAp;</div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <span class="keywordflow">if</span> (r0star)</div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  data_buffer[buffer_chunk_offset] = inner_prod_Ap_r0star;</div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  }</div>
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span> </div>
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00294"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#ac9d1c21f37de06e65be9d2002fb3b45e"> 294</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">pipelined_prod_impl</a>(<a class="code" href="classviennacl_1_1hyb__matrix.html">hyb_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * r0star,</div>
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size,</div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_offset)</div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  {</div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> value_type;</div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keyword">typedef</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index_type;</div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span> </div>
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  value_type * Ap_buf = detail::extract_raw_pointer<value_type>(Ap.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>()) + <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(Ap);;</div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  value_type <span class="keyword">const</span> * p_buf = detail::extract_raw_pointer<value_type>(p.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>()) + <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(p);;</div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  value_type <span class="keyword">const</span> * elements = detail::extract_raw_pointer<value_type>(A.<a class="code" href="classviennacl_1_1hyb__matrix.html#a4b3f5963def504d05e7ab97b972067f0">handle</a>());</div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  index_type <span class="keyword">const</span> * coords = detail::extract_raw_pointer<index_type>(A.<a class="code" href="classviennacl_1_1hyb__matrix.html#a83cb07a6aa15fcf960b40b4a82fdc574">handle2</a>());</div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  value_type <span class="keyword">const</span> * csr_elements = detail::extract_raw_pointer<value_type>(A.<a class="code" href="classviennacl_1_1hyb__matrix.html#aed5ff60ddfef1cd59108064a5d4cdd7f">handle5</a>());</div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  index_type <span class="keyword">const</span> * csr_row_buffer = detail::extract_raw_pointer<index_type>(A.<a class="code" href="classviennacl_1_1hyb__matrix.html#a85c8cfa2f303c11c2e8ebea46e4ea400">handle3</a>());</div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  index_type <span class="keyword">const</span> * csr_col_buffer = detail::extract_raw_pointer<index_type>(A.<a class="code" href="classviennacl_1_1hyb__matrix.html#acd8b0197ad9c5a92ed26cf6ec3ce6137">handle4</a>());</div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  value_type * data_buffer = detail::extract_raw_pointer<value_type>(inner_prod_buffer);</div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span> </div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  value_type inner_prod_ApAp = 0;</div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  value_type inner_prod_pAp = 0;</div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  value_type inner_prod_Ap_r0star = 0;</div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> = 0; <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> < A.<a class="code" href="classviennacl_1_1hyb__matrix.html#ab5f077832dd0efade9f5037327a1786d">size1</a>(); ++<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>)</div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  {</div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  value_type val_p_diag = p_buf[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>)]; <span class="comment">//likely to be loaded from cache if required again in this row</span></div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  value_type <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a> = 0;</div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span> </div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="comment">// Part 1: Process ELL part</span></div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="keywordflow">for</span> (index_type item_id = 0; item_id < A.<a class="code" href="classviennacl_1_1hyb__matrix.html#ac80cf4d3ab3ab38f398405ecf88419cd">internal_ellnnz</a>(); ++item_id)</div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  {</div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> offset = <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> + item_id * A.<a class="code" href="classviennacl_1_1hyb__matrix.html#a71a65b6963fe30384f160f4cf6c189c8">internal_size1</a>();</div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  value_type val = elements[offset];</div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span> </div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="keywordflow">if</span> (val)</div>
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  sum += p_buf[coords[offset]] * val;</div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  }</div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span> </div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="comment">// Part 2: Process HYB part</span></div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> col_begin = csr_row_buffer[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>];</div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> col_end = csr_row_buffer[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> + 1];</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span> </div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> item_id = col_begin; item_id < col_end; item_id++)</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  sum += p_buf[csr_col_buffer[item_id]] * csr_elements[item_id];</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span> </div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  Ap_buf[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>] = <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a>;</div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  inner_prod_ApAp += sum * <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a>;</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  inner_prod_pAp += val_p_diag * <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a>;</div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  inner_prod_Ap_r0star += r0star ? sum * r0star[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>] : value_type(0);</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  }</div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span> </div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  data_buffer[ buffer_chunk_size] = inner_prod_ApAp;</div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  data_buffer[2 * buffer_chunk_size] = inner_prod_pAp;</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <span class="keywordflow">if</span> (r0star)</div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  data_buffer[buffer_chunk_offset] = inner_prod_Ap_r0star;</div>
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  }</div>
<div class="line"><a name="l00354"></a><span class="lineno"> 354</span> </div>
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span> } <span class="comment">// namespace detail</span></div>
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span> </div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span> </div>
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00367"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#aa1f80e9f52a434ea819a0a38c91223a4"> 367</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#aa1f80e9f52a434ea819a0a38c91223a4">pipelined_cg_vector_update</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & result,</div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> alpha,</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & p,</div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & r,</div>
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & Ap,</div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> beta,</div>
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer)</div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span> {</div>
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> value_type;</div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span> </div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  value_type * data_result = detail::extract_raw_pointer<value_type>(result);</div>
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  value_type * data_p = detail::extract_raw_pointer<value_type>(p);</div>
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  value_type * data_r = detail::extract_raw_pointer<value_type>(r);</div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  value_type <span class="keyword">const</span> * data_Ap = detail::extract_raw_pointer<value_type>(Ap);</div>
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  value_type * data_buffer = detail::extract_raw_pointer<value_type>(inner_prod_buffer);</div>
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span> </div>
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="comment">// Note: Due to the special setting in CG, there is no need to check for sizes and strides</span></div>
<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(result);</div>
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span> </div>
<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  value_type inner_prod_r = 0;</div>
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keywordflow">for</span> (<span class="keywordtype">long</span> i = 0; i < static_cast<long>(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>); ++i)</div>
<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  {</div>
<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  value_type value_p = data_p[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)];</div>
<div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  value_type value_r = data_r[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)];</div>
<div class="line"><a name="l00391"></a><span class="lineno"> 391</span> </div>
<div class="line"><a name="l00392"></a><span class="lineno"> 392</span> </div>
<div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  data_result[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)] += alpha * value_p;</div>
<div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  value_r -= alpha * data_Ap[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)];</div>
<div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  value_p = value_r + beta * value_p;</div>
<div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  inner_prod_r += value_r * value_r;</div>
<div class="line"><a name="l00397"></a><span class="lineno"> 397</span> </div>
<div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  data_p[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)] = value_p;</div>
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  data_r[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)] = value_r;</div>
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  }</div>
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span> </div>
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  data_buffer[0] = inner_prod_r;</div>
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span> }</div>
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span> </div>
<div class="line"><a name="l00405"></a><span class="lineno"> 405</span> </div>
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00413"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a9cca5888f4345b3b4f3339c74dbf9042"> 413</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a9cca5888f4345b3b4f3339c74dbf9042">pipelined_cg_prod</a>(<a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer)</div>
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span> {</div>
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * PtrType;</div>
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">viennacl::linalg::host_based::detail::pipelined_prod_impl</a>(A, p, Ap, PtrType(NULL), inner_prod_buffer, inner_prod_buffer.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>() / 3, 0);</div>
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span> }</div>
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span> </div>
<div class="line"><a name="l00422"></a><span class="lineno"> 422</span> </div>
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span> </div>
<div class="line"><a name="l00430"></a><span class="lineno"> 430</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00431"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#ab3c4e15706647da60ecf0d9bf375bd20"> 431</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a9cca5888f4345b3b4f3339c74dbf9042">pipelined_cg_prod</a>(<a class="code" href="classviennacl_1_1coordinate__matrix.html">coordinate_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer)</div>
<div class="line"><a name="l00435"></a><span class="lineno"> 435</span> {</div>
<div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * PtrType;</div>
<div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">viennacl::linalg::host_based::detail::pipelined_prod_impl</a>(A, p, Ap, PtrType(NULL), inner_prod_buffer, inner_prod_buffer.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>() / 3, 0);</div>
<div class="line"><a name="l00438"></a><span class="lineno"> 438</span> }</div>
<div class="line"><a name="l00439"></a><span class="lineno"> 439</span> </div>
<div class="line"><a name="l00440"></a><span class="lineno"> 440</span> </div>
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00448"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#aecdb028789f4419f1404533749109529"> 448</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a9cca5888f4345b3b4f3339c74dbf9042">pipelined_cg_prod</a>(<a class="code" href="classviennacl_1_1ell__matrix.html">ell_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer)</div>
<div class="line"><a name="l00452"></a><span class="lineno"> 452</span> {</div>
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * PtrType;</div>
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">viennacl::linalg::host_based::detail::pipelined_prod_impl</a>(A, p, Ap, PtrType(NULL), inner_prod_buffer, inner_prod_buffer.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>() / 3, 0);</div>
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span> }</div>
<div class="line"><a name="l00456"></a><span class="lineno"> 456</span> </div>
<div class="line"><a name="l00457"></a><span class="lineno"> 457</span> </div>
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> IndexT></div>
<div class="line"><a name="l00465"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a6824118f240d2035a829f3ad6f7a0550"> 465</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a9cca5888f4345b3b4f3339c74dbf9042">pipelined_cg_prod</a>(<a class="code" href="classviennacl_1_1sliced__ell__matrix.html">sliced_ell_matrix<NumericT, IndexT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer)</div>
<div class="line"><a name="l00469"></a><span class="lineno"> 469</span> {</div>
<div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * PtrType;</div>
<div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">viennacl::linalg::host_based::detail::pipelined_prod_impl</a>(A, p, Ap, PtrType(NULL), inner_prod_buffer, inner_prod_buffer.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>() / 3, 0);</div>
<div class="line"><a name="l00472"></a><span class="lineno"> 472</span> }</div>
<div class="line"><a name="l00473"></a><span class="lineno"> 473</span> </div>
<div class="line"><a name="l00474"></a><span class="lineno"> 474</span> </div>
<div class="line"><a name="l00475"></a><span class="lineno"> 475</span> </div>
<div class="line"><a name="l00476"></a><span class="lineno"> 476</span> </div>
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00484"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a007721c3f2ab15ac50194467853ab87e"> 484</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a9cca5888f4345b3b4f3339c74dbf9042">pipelined_cg_prod</a>(<a class="code" href="classviennacl_1_1hyb__matrix.html">hyb_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer)</div>
<div class="line"><a name="l00488"></a><span class="lineno"> 488</span> {</div>
<div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * PtrType;</div>
<div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">viennacl::linalg::host_based::detail::pipelined_prod_impl</a>(A, p, Ap, PtrType(NULL), inner_prod_buffer, inner_prod_buffer.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>() / 3, 0);</div>
<div class="line"><a name="l00491"></a><span class="lineno"> 491</span> }</div>
<div class="line"><a name="l00492"></a><span class="lineno"> 492</span> </div>
<div class="line"><a name="l00494"></a><span class="lineno"> 494</span> </div>
<div class="line"><a name="l00495"></a><span class="lineno"> 495</span> </div>
<div class="line"><a name="l00503"></a><span class="lineno"> 503</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00504"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#ac1b61075d4b2a3d605fb08dc0dca95ea"> 504</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ac1b61075d4b2a3d605fb08dc0dca95ea">pipelined_bicgstab_update_s</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & s,</div>
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & r,</div>
<div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & Ap,</div>
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size,</div>
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_offset)</div>
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span> {</div>
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> value_type;</div>
<div class="line"><a name="l00512"></a><span class="lineno"> 512</span> </div>
<div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  value_type * data_s = detail::extract_raw_pointer<value_type>(s);</div>
<div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  value_type * data_r = detail::extract_raw_pointer<value_type>(r);</div>
<div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  value_type <span class="keyword">const</span> * data_Ap = detail::extract_raw_pointer<value_type>(Ap);</div>
<div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  value_type * data_buffer = detail::extract_raw_pointer<value_type>(inner_prod_buffer);</div>
<div class="line"><a name="l00517"></a><span class="lineno"> 517</span> </div>
<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <span class="comment">// Note: Due to the special setting in CG, there is no need to check for sizes and strides</span></div>
<div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(s);</div>
<div class="line"><a name="l00520"></a><span class="lineno"> 520</span> </div>
<div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <span class="comment">// part 1: compute alpha:</span></div>
<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  value_type r_in_r0 = 0;</div>
<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  value_type Ap_in_r0 = 0;</div>
<div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i=0; i<buffer_chunk_size; ++i)</div>
<div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  {</div>
<div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  r_in_r0 += data_buffer[i];</div>
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  Ap_in_r0 += data_buffer[i + 3 * buffer_chunk_size];</div>
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  }</div>
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  value_type alpha = r_in_r0 / Ap_in_r0;</div>
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span> </div>
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  <span class="comment">// part 2: s = r - alpha * Ap and first step in reduction for s:</span></div>
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  value_type inner_prod_s = 0;</div>
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="keywordflow">for</span> (<span class="keywordtype">long</span> i = 0; i < static_cast<long>(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>); ++i)</div>
<div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  {</div>
<div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  value_type value_s = data_s[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)];</div>
<div class="line"><a name="l00536"></a><span class="lineno"> 536</span> </div>
<div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  value_s = data_r[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)] - alpha * data_Ap[static_cast<vcl_size_t>(i)];</div>
<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  inner_prod_s += value_s * value_s;</div>
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span> </div>
<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  data_s[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)] = value_s;</div>
<div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  }</div>
<div class="line"><a name="l00542"></a><span class="lineno"> 542</span> </div>
<div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  data_buffer[buffer_chunk_offset] = inner_prod_s;</div>
<div class="line"><a name="l00544"></a><span class="lineno"> 544</span> }</div>
<div class="line"><a name="l00545"></a><span class="lineno"> 545</span> </div>
<div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00554"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#ae379e200baf8decb11531e9284252bd8"> 554</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ae379e200baf8decb11531e9284252bd8">pipelined_bicgstab_vector_update</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & result, <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> alpha, <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & p, <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> omega, <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & s,</div>
<div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & residual, <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & As,</div>
<div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> beta, <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & Ap,</div>
<div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & r0star,</div>
<div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size)</div>
<div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  {</div>
<div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  <span class="keyword">typedef</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> value_type;</div>
<div class="line"><a name="l00562"></a><span class="lineno"> 562</span> </div>
<div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  value_type * data_result = detail::extract_raw_pointer<value_type>(result);</div>
<div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  value_type * data_p = detail::extract_raw_pointer<value_type>(p);</div>
<div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  value_type <span class="keyword">const</span> * data_s = detail::extract_raw_pointer<value_type>(s);</div>
<div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  value_type * data_residual = detail::extract_raw_pointer<value_type>(residual);</div>
<div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  value_type <span class="keyword">const</span> * data_As = detail::extract_raw_pointer<value_type>(As);</div>
<div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  value_type <span class="keyword">const</span> * data_Ap = detail::extract_raw_pointer<value_type>(Ap);</div>
<div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  value_type <span class="keyword">const</span> * data_r0star = detail::extract_raw_pointer<value_type>(r0star);</div>
<div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  value_type * data_buffer = detail::extract_raw_pointer<value_type>(inner_prod_buffer);</div>
<div class="line"><a name="l00571"></a><span class="lineno"> 571</span> </div>
<div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(result);</div>
<div class="line"><a name="l00573"></a><span class="lineno"> 573</span> </div>
<div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  value_type inner_prod_r_r0star = 0;</div>
<div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <span class="keywordflow">for</span> (<span class="keywordtype">long</span> i = 0; i < static_cast<long>(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>); ++i)</div>
<div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  {</div>
<div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> index = <span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i);</div>
<div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  value_type value_result = data_result[index];</div>
<div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  value_type value_p = data_p[index];</div>
<div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  value_type value_s = data_s[index];</div>
<div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  value_type value_residual = data_residual[index];</div>
<div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  value_type value_As = data_As[index];</div>
<div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  value_type value_Ap = data_Ap[index];</div>
<div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  value_type value_r0star = data_r0star[index];</div>
<div class="line"><a name="l00585"></a><span class="lineno"> 585</span> </div>
<div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  value_result += alpha * value_p + omega * value_s;</div>
<div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  value_residual = value_s - omega * value_As;</div>
<div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  value_p = value_residual + beta * (value_p - omega * value_Ap);</div>
<div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  inner_prod_r_r0star += value_residual * value_r0star;</div>
<div class="line"><a name="l00590"></a><span class="lineno"> 590</span> </div>
<div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  data_result[index] = value_result;</div>
<div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  data_residual[index] = value_residual;</div>
<div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  data_p[index] = value_p;</div>
<div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  }</div>
<div class="line"><a name="l00595"></a><span class="lineno"> 595</span> </div>
<div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  (void)buffer_chunk_size; <span class="comment">// not needed here, just silence compiler warning (unused variable)</span></div>
<div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  data_buffer[0] = inner_prod_r_r0star;</div>
<div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  }</div>
<div class="line"><a name="l00599"></a><span class="lineno"> 599</span> </div>
<div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00607"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#ac78885423ca2ebe2205b29a213883c61"> 607</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ac78885423ca2ebe2205b29a213883c61">pipelined_bicgstab_prod</a>(<a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & r0star,</div>
<div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size,</div>
<div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_offset)</div>
<div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  {</div>
<div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * data_r0star = detail::extract_raw_pointer<NumericT>(r0star);</div>
<div class="line"><a name="l00616"></a><span class="lineno"> 616</span> </div>
<div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">viennacl::linalg::host_based::detail::pipelined_prod_impl</a>(A, p, Ap, data_r0star, inner_prod_buffer, buffer_chunk_size, buffer_chunk_offset);</div>
<div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  }</div>
<div class="line"><a name="l00619"></a><span class="lineno"> 619</span> </div>
<div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00627"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a2f7dc9950987cea3c1cedc017c8cebef"> 627</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ac78885423ca2ebe2205b29a213883c61">pipelined_bicgstab_prod</a>(<a class="code" href="classviennacl_1_1coordinate__matrix.html">coordinate_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & r0star,</div>
<div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size,</div>
<div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_offset)</div>
<div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  {</div>
<div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * data_r0star = detail::extract_raw_pointer<NumericT>(r0star);</div>
<div class="line"><a name="l00636"></a><span class="lineno"> 636</span> </div>
<div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">viennacl::linalg::host_based::detail::pipelined_prod_impl</a>(A, p, Ap, data_r0star, inner_prod_buffer, buffer_chunk_size, buffer_chunk_offset);</div>
<div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  }</div>
<div class="line"><a name="l00639"></a><span class="lineno"> 639</span> </div>
<div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00647"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#afab7aa8f81633f10c702f617e27a9b79"> 647</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ac78885423ca2ebe2205b29a213883c61">pipelined_bicgstab_prod</a>(<a class="code" href="classviennacl_1_1ell__matrix.html">ell_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00648"></a><span class="lineno"> 648</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & r0star,</div>
<div class="line"><a name="l00651"></a><span class="lineno"> 651</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00652"></a><span class="lineno"> 652</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size,</div>
<div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_offset)</div>
<div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  {</div>
<div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * data_r0star = detail::extract_raw_pointer<NumericT>(r0star);</div>
<div class="line"><a name="l00656"></a><span class="lineno"> 656</span> </div>
<div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">viennacl::linalg::host_based::detail::pipelined_prod_impl</a>(A, p, Ap, data_r0star, inner_prod_buffer, buffer_chunk_size, buffer_chunk_offset);</div>
<div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  }</div>
<div class="line"><a name="l00659"></a><span class="lineno"> 659</span> </div>
<div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> IndexT></div>
<div class="line"><a name="l00667"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a9adec962a1a08ddb24ab4a9d0a9a19ab"> 667</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ac78885423ca2ebe2205b29a213883c61">pipelined_bicgstab_prod</a>(<a class="code" href="classviennacl_1_1sliced__ell__matrix.html">sliced_ell_matrix<NumericT, IndexT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & r0star,</div>
<div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size,</div>
<div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_offset)</div>
<div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  {</div>
<div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * data_r0star = detail::extract_raw_pointer<NumericT>(r0star);</div>
<div class="line"><a name="l00676"></a><span class="lineno"> 676</span> </div>
<div class="line"><a name="l00677"></a><span class="lineno"> 677</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">viennacl::linalg::host_based::detail::pipelined_prod_impl</a>(A, p, Ap, data_r0star, inner_prod_buffer, buffer_chunk_size, buffer_chunk_offset);</div>
<div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  }</div>
<div class="line"><a name="l00679"></a><span class="lineno"> 679</span> </div>
<div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00687"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a7b99fb1a7b869068376e649386b0f6bd"> 687</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ac78885423ca2ebe2205b29a213883c61">pipelined_bicgstab_prod</a>(<a class="code" href="classviennacl_1_1hyb__matrix.html">hyb_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & Ap,</div>
<div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & r0star,</div>
<div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size,</div>
<div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_offset)</div>
<div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  {</div>
<div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * data_r0star = detail::extract_raw_pointer<NumericT>(r0star);</div>
<div class="line"><a name="l00696"></a><span class="lineno"> 696</span> </div>
<div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">viennacl::linalg::host_based::detail::pipelined_prod_impl</a>(A, p, Ap, data_r0star, inner_prod_buffer, buffer_chunk_size, buffer_chunk_offset);</div>
<div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  }</div>
<div class="line"><a name="l00699"></a><span class="lineno"> 699</span> </div>
<div class="line"><a name="l00700"></a><span class="lineno"> 700</span> </div>
<div class="line"><a name="l00702"></a><span class="lineno"> 702</span> </div>
<div class="line"><a name="l00710"></a><span class="lineno"> 710</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00711"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#abb2b03970007010e3989b6474d5c8061"> 711</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#abb2b03970007010e3989b6474d5c8061">pipelined_gmres_normalize_vk</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & v_k,</div>
<div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & residual,</div>
<div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & R_buffer,</div>
<div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> offset_in_R,</div>
<div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & inner_prod_buffer,</div>
<div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & r_dot_vk_buffer,</div>
<div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size,</div>
<div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_offset)</div>
<div class="line"><a name="l00719"></a><span class="lineno"> 719</span> {</div>
<div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  <span class="keyword">typedef</span> T value_type;</div>
<div class="line"><a name="l00721"></a><span class="lineno"> 721</span> </div>
<div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  value_type * data_v_k = detail::extract_raw_pointer<value_type>(v_k);</div>
<div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  value_type <span class="keyword">const</span> * data_residual = detail::extract_raw_pointer<value_type>(residual);</div>
<div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  value_type * data_R = detail::extract_raw_pointer<value_type>(R_buffer);</div>
<div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  value_type <span class="keyword">const</span> * data_buffer = detail::extract_raw_pointer<value_type>(inner_prod_buffer);</div>
<div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  value_type * data_r_dot_vk = detail::extract_raw_pointer<value_type>(r_dot_vk_buffer);</div>
<div class="line"><a name="l00727"></a><span class="lineno"> 727</span> </div>
<div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  <span class="comment">// Note: Due to the special setting in GMRES, there is no need to check for sizes and strides</span></div>
<div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(v_k);</div>
<div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> vk_start = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(v_k);</div>
<div class="line"><a name="l00731"></a><span class="lineno"> 731</span> </div>
<div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  <span class="comment">// part 1: compute alpha:</span></div>
<div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  value_type norm_vk = 0;</div>
<div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i=0; i<buffer_chunk_size; ++i)</div>
<div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  norm_vk += data_buffer[i + buffer_chunk_size];</div>
<div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  norm_vk = std::sqrt(norm_vk);</div>
<div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  data_R[offset_in_R] = norm_vk;</div>
<div class="line"><a name="l00738"></a><span class="lineno"> 738</span> </div>
<div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  <span class="comment">// Compute <r, v_k> after normalization of v_k:</span></div>
<div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  value_type inner_prod_r_dot_vk = 0;</div>
<div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  <span class="keywordflow">for</span> (<span class="keywordtype">long</span> i = 0; i < static_cast<long>(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>); ++i)</div>
<div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  {</div>
<div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  value_type value_vk = data_v_k[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i) + vk_start] / norm_vk;</div>
<div class="line"><a name="l00744"></a><span class="lineno"> 744</span> </div>
<div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  inner_prod_r_dot_vk += data_residual[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)] * value_vk;</div>
<div class="line"><a name="l00746"></a><span class="lineno"> 746</span> </div>
<div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  data_v_k[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i) + vk_start] = value_vk;</div>
<div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  }</div>
<div class="line"><a name="l00749"></a><span class="lineno"> 749</span> </div>
<div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  data_r_dot_vk[buffer_chunk_offset] = inner_prod_r_dot_vk;</div>
<div class="line"><a name="l00751"></a><span class="lineno"> 751</span> }</div>
<div class="line"><a name="l00752"></a><span class="lineno"> 752</span> </div>
<div class="line"><a name="l00753"></a><span class="lineno"> 753</span> </div>
<div class="line"><a name="l00754"></a><span class="lineno"> 754</span> </div>
<div class="line"><a name="l00759"></a><span class="lineno"> 759</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00760"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#aa17b7680809f798794a5c2dc863931a6"> 760</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#aa17b7680809f798794a5c2dc863931a6">pipelined_gmres_gram_schmidt_stage1</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & device_krylov_basis,</div>
<div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> v_k_size,</div>
<div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> v_k_internal_size,</div>
<div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> k,</div>
<div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & vi_in_vk_buffer,</div>
<div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size)</div>
<div class="line"><a name="l00766"></a><span class="lineno"> 766</span> {</div>
<div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  <span class="keyword">typedef</span> T value_type;</div>
<div class="line"><a name="l00768"></a><span class="lineno"> 768</span> </div>
<div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  value_type <span class="keyword">const</span> * data_krylov_basis = detail::extract_raw_pointer<value_type>(device_krylov_basis);</div>
<div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  value_type * data_inner_prod = detail::extract_raw_pointer<value_type>(vi_in_vk_buffer);</div>
<div class="line"><a name="l00771"></a><span class="lineno"> 771</span> </div>
<div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  <span class="comment">// reset buffer:</span></div>
<div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> j = 0; j < k; ++j)</div>
<div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  data_inner_prod[j*buffer_chunk_size] = value_type(0);</div>
<div class="line"><a name="l00775"></a><span class="lineno"> 775</span> </div>
<div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  <span class="comment">// compute inner products:</span></div>
<div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 0; i < v_k_size; ++i)</div>
<div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  {</div>
<div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  value_type value_vk = data_krylov_basis[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i) + k * v_k_internal_size];</div>
<div class="line"><a name="l00780"></a><span class="lineno"> 780</span> </div>
<div class="line"><a name="l00781"></a><span class="lineno"> 781</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> j = 0; j < k; ++j)</div>
<div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  data_inner_prod[j*buffer_chunk_size] += data_krylov_basis[static_cast<vcl_size_t>(i) + j * v_k_internal_size] * value_vk;</div>
<div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  }</div>
<div class="line"><a name="l00784"></a><span class="lineno"> 784</span> }</div>
<div class="line"><a name="l00785"></a><span class="lineno"> 785</span> </div>
<div class="line"><a name="l00786"></a><span class="lineno"> 786</span> </div>
<div class="line"><a name="l00791"></a><span class="lineno"> 791</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00792"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a8e4aac801d1aeb7868dad15fc9691485"> 792</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a8e4aac801d1aeb7868dad15fc9691485">pipelined_gmres_gram_schmidt_stage2</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & device_krylov_basis,</div>
<div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> v_k_size,</div>
<div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> v_k_internal_size,</div>
<div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> k,</div>
<div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & vi_in_vk_buffer,</div>
<div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & R_buffer,</div>
<div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> krylov_dim,</div>
<div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & inner_prod_buffer,</div>
<div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> buffer_chunk_size)</div>
<div class="line"><a name="l00801"></a><span class="lineno"> 801</span> {</div>
<div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  <span class="keyword">typedef</span> T value_type;</div>
<div class="line"><a name="l00803"></a><span class="lineno"> 803</span> </div>
<div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  value_type * data_krylov_basis = detail::extract_raw_pointer<value_type>(device_krylov_basis);</div>
<div class="line"><a name="l00805"></a><span class="lineno"> 805</span> </div>
<div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  std::vector<T> values_vi_in_vk(k);</div>
<div class="line"><a name="l00807"></a><span class="lineno"> 807</span> </div>
<div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  <span class="comment">// Step 1: Finish reduction of <v_i, v_k> to obtain scalars:</span></div>
<div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  <span class="keywordflow">for</span> (std::size_t i=0; i<k; ++i)</div>
<div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> j=0; j<buffer_chunk_size; ++j)</div>
<div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  values_vi_in_vk[i] += vi_in_vk_buffer[i*buffer_chunk_size + j];</div>
<div class="line"><a name="l00812"></a><span class="lineno"> 812</span> </div>
<div class="line"><a name="l00813"></a><span class="lineno"> 813</span> </div>
<div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  <span class="comment">// Step 2: Compute v_k -= <v_i, v_k> v_i and reduction on ||v_k||:</span></div>
<div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  value_type norm_vk = 0;</div>
<div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 0; i < v_k_size; ++i)</div>
<div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  {</div>
<div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  value_type value_vk = data_krylov_basis[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i) + k * v_k_internal_size];</div>
<div class="line"><a name="l00819"></a><span class="lineno"> 819</span> </div>
<div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> j = 0; j < k; ++j)</div>
<div class="line"><a name="l00821"></a><span class="lineno"> 821</span>  value_vk -= values_vi_in_vk[j] * data_krylov_basis[static_cast<vcl_size_t>(i) + j * v_k_internal_size];</div>
<div class="line"><a name="l00822"></a><span class="lineno"> 822</span> </div>
<div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  norm_vk += value_vk * value_vk;</div>
<div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  data_krylov_basis[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i) + k * v_k_internal_size] = value_vk;</div>
<div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  }</div>
<div class="line"><a name="l00826"></a><span class="lineno"> 826</span> </div>
<div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  <span class="comment">// Step 3: Write values to R_buffer:</span></div>
<div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  <span class="keywordflow">for</span> (std::size_t i=0; i<k; ++i)</div>
<div class="line"><a name="l00829"></a><span class="lineno"> 829</span>  R_buffer[i + k * krylov_dim] = values_vi_in_vk[i];</div>
<div class="line"><a name="l00830"></a><span class="lineno"> 830</span> </div>
<div class="line"><a name="l00831"></a><span class="lineno"> 831</span>  inner_prod_buffer[buffer_chunk_size] = norm_vk;</div>
<div class="line"><a name="l00832"></a><span class="lineno"> 832</span> }</div>
<div class="line"><a name="l00833"></a><span class="lineno"> 833</span> </div>
<div class="line"><a name="l00835"></a><span class="lineno"> 835</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00836"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#af497e625d846f3e219b9467b82cda386"> 836</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#af497e625d846f3e219b9467b82cda386">pipelined_gmres_update_result</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & result,</div>
<div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & residual,</div>
<div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & krylov_basis,</div>
<div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> v_k_size,</div>
<div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> v_k_internal_size,</div>
<div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & coefficients,</div>
<div class="line"><a name="l00842"></a><span class="lineno"> 842</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> k)</div>
<div class="line"><a name="l00843"></a><span class="lineno"> 843</span> {</div>
<div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  <span class="keyword">typedef</span> T value_type;</div>
<div class="line"><a name="l00845"></a><span class="lineno"> 845</span> </div>
<div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  value_type * data_result = detail::extract_raw_pointer<value_type>(result);</div>
<div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  value_type <span class="keyword">const</span> * data_residual = detail::extract_raw_pointer<value_type>(residual);</div>
<div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  value_type <span class="keyword">const</span> * data_krylov_basis = detail::extract_raw_pointer<value_type>(krylov_basis);</div>
<div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  value_type <span class="keyword">const</span> * data_coefficients = detail::extract_raw_pointer<value_type>(coefficients);</div>
<div class="line"><a name="l00850"></a><span class="lineno"> 850</span> </div>
<div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 0; i < v_k_size; ++i)</div>
<div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  {</div>
<div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  value_type value_result = data_result[i];</div>
<div class="line"><a name="l00854"></a><span class="lineno"> 854</span> </div>
<div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  value_result += data_coefficients[0] * data_residual[i];</div>
<div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> j = 1; j<k; ++j)</div>
<div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  value_result += data_coefficients[j] * data_krylov_basis[i + (j-1) * v_k_internal_size];</div>
<div class="line"><a name="l00858"></a><span class="lineno"> 858</span> </div>
<div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  data_result[i] = value_result;</div>
<div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  }</div>
<div class="line"><a name="l00861"></a><span class="lineno"> 861</span> </div>
<div class="line"><a name="l00862"></a><span class="lineno"> 862</span> }</div>
<div class="line"><a name="l00863"></a><span class="lineno"> 863</span> </div>
<div class="line"><a name="l00864"></a><span class="lineno"> 864</span> <span class="comment">// Reuse implementation from CG:</span></div>
<div class="line"><a name="l00865"></a><span class="lineno"> 865</span> <span class="keyword">template</span> <<span class="keyword">typename</span> MatrixType, <span class="keyword">typename</span> T></div>
<div class="line"><a name="l00866"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#aeb57ebff0a27bc75b9340df9a99bf155"> 866</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#aeb57ebff0a27bc75b9340df9a99bf155">pipelined_gmres_prod</a>(MatrixType <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> <span class="keyword">const</span> & p,</div>
<div class="line"><a name="l00868"></a><span class="lineno"> 868</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & Ap,</div>
<div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<T></a> & inner_prod_buffer)</div>
<div class="line"><a name="l00870"></a><span class="lineno"> 870</span> {</div>
<div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a9cca5888f4345b3b4f3339c74dbf9042">pipelined_cg_prod</a>(A, p, Ap, inner_prod_buffer);</div>
<div class="line"><a name="l00872"></a><span class="lineno"> 872</span> }</div>
<div class="line"><a name="l00873"></a><span class="lineno"> 873</span> </div>
<div class="line"><a name="l00874"></a><span class="lineno"> 874</span> </div>
<div class="line"><a name="l00875"></a><span class="lineno"> 875</span> } <span class="comment">//namespace host_based</span></div>
<div class="line"><a name="l00876"></a><span class="lineno"> 876</span> } <span class="comment">//namespace linalg</span></div>
<div class="line"><a name="l00877"></a><span class="lineno"> 877</span> } <span class="comment">//namespace viennacl</span></div>
<div class="line"><a name="l00878"></a><span class="lineno"> 878</span> </div>
<div class="line"><a name="l00879"></a><span class="lineno"> 879</span> </div>
<div class="line"><a name="l00880"></a><span class="lineno"> 880</span> <span class="preprocessor">#endif</span></div>
<div class="ttc" id="classviennacl_1_1hyb__matrix_html_ac80cf4d3ab3ab38f398405ecf88419cd"><div class="ttname"><a href="classviennacl_1_1hyb__matrix.html#ac80cf4d3ab3ab38f398405ecf88419cd">viennacl::hyb_matrix::internal_ellnnz</a></div><div class="ttdeci">vcl_size_t internal_ellnnz() const </div><div class="ttdef"><b>Definition:</b> <a href="hyb__matrix_8hpp_source.html#l00101">hyb_matrix.hpp:101</a></div></div>
<div class="ttc" id="classviennacl_1_1hyb__matrix_html"><div class="ttname"><a href="classviennacl_1_1hyb__matrix.html">viennacl::hyb_matrix</a></div><div class="ttdoc">Sparse matrix class using a hybrid format composed of the ELL and CSR format for storing the nonzeros...</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00406">forwards.h:406</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_abb2b03970007010e3989b6474d5c8061"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#abb2b03970007010e3989b6474d5c8061">viennacl::linalg::host_based::pipelined_gmres_normalize_vk</a></div><div class="ttdeci">void pipelined_gmres_normalize_vk(vector_base< T > &v_k, vector_base< T > const &residual, vector_base< T > &R_buffer, vcl_size_t offset_in_R, vector_base< T > const &inner_prod_buffer, vector_base< T > &r_dot_vk_buffer, vcl_size_t buffer_chunk_size, vcl_size_t buffer_chunk_offset)</div><div class="ttdoc">Performs a vector normalization needed for an efficient pipelined GMRES algorithm. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2iterative__operations_8hpp_source.html#l00711">iterative_operations.hpp:711</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_a31d5fa9ec25dcfeb260f7e11c4db6571"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a31d5fa9ec25dcfeb260f7e11c4db6571">viennacl::sliced_ell_matrix::handle2</a></div><div class="ttdeci">handle_type & handle2()</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00112">sliced_ell_matrix.hpp:112</a></div></div>
<div class="ttc" id="classviennacl_1_1ell__matrix_html_a7a37f6e784757bd80c71f800efcefc3f"><div class="ttname"><a href="classviennacl_1_1ell__matrix.html#a7a37f6e784757bd80c71f800efcefc3f">viennacl::ell_matrix::size1</a></div><div class="ttdeci">vcl_size_t size1() const </div><div class="ttdef"><b>Definition:</b> <a href="ell__matrix_8hpp_source.html#l00091">ell_matrix.hpp:91</a></div></div>
<div class="ttc" id="classviennacl_1_1ell__matrix_html_a1260f11302263435b8f6de4a4c0ef4b6"><div class="ttname"><a href="classviennacl_1_1ell__matrix.html#a1260f11302263435b8f6de4a4c0ef4b6">viennacl::ell_matrix::handle2</a></div><div class="ttdeci">handle_type & handle2()</div><div class="ttdef"><b>Definition:</b> <a href="ell__matrix_8hpp_source.html#l00103">ell_matrix.hpp:103</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a4117795095db49147ba7305d3e0a1af5"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">viennacl::linalg::sum</a></div><div class="ttdeci">viennacl::scalar_expression< const viennacl::vector_base< NumericT >, const viennacl::vector_base< NumericT >, viennacl::op_sum > sum(viennacl::vector_base< NumericT > const &x)</div><div class="ttdoc">User interface function for computing the sum of all elements of a vector. </div><div class="ttdef"><b>Definition:</b> <a href="sum_8hpp_source.html#l00045">sum.hpp:45</a></div></div>
<div class="ttc" id="size_8hpp_html"><div class="ttname"><a href="size_8hpp.html">size.hpp</a></div><div class="ttdoc">Generic size and resize functionality for different vector and matrix types. </div></div>
<div class="ttc" id="classviennacl_1_1hyb__matrix_html_a85c8cfa2f303c11c2e8ebea46e4ea400"><div class="ttname"><a href="classviennacl_1_1hyb__matrix.html#a85c8cfa2f303c11c2e8ebea46e4ea400">viennacl::hyb_matrix::handle3</a></div><div class="ttdeci">const handle_type & handle3() const </div><div class="ttdef"><b>Definition:</b> <a href="hyb__matrix_8hpp_source.html#l00107">hyb_matrix.hpp:107</a></div></div>
<div class="ttc" id="classviennacl_1_1compressed__matrix_html_a463cf1739f9cdd387aa185cb574db183"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">viennacl::compressed_matrix::size1</a></div><div class="ttdeci">const vcl_size_t & size1() const </div><div class="ttdoc">Returns the number of rows. </div><div class="ttdef"><b>Definition:</b> <a href="compressed__matrix_8hpp_source.html#l00927">compressed_matrix.hpp:927</a></div></div>
<div class="ttc" id="start_8hpp_html"><div class="ttname"><a href="start_8hpp.html">start.hpp</a></div><div class="ttdoc">Extracts the underlying OpenCL start index handle from a vector, a matrix, an expression etc...</div></div>
<div class="ttc" id="tools_8hpp_html"><div class="ttname"><a href="tools_8hpp.html">tools.hpp</a></div><div class="ttdoc">Various little tools used here and there in ViennaCL. </div></div>
<div class="ttc" id="classviennacl_1_1hyb__matrix_html_a4b3f5963def504d05e7ab97b972067f0"><div class="ttname"><a href="classviennacl_1_1hyb__matrix.html#a4b3f5963def504d05e7ab97b972067f0">viennacl::hyb_matrix::handle</a></div><div class="ttdeci">const handle_type & handle() const </div><div class="ttdef"><b>Definition:</b> <a href="hyb__matrix_8hpp_source.html#l00105">hyb_matrix.hpp:105</a></div></div>
<div class="ttc" id="classviennacl_1_1coordinate__matrix_html_a875b6ccacbf0df8ef48ab7f7c46244f1"><div class="ttname"><a href="classviennacl_1_1coordinate__matrix.html#a875b6ccacbf0df8ef48ab7f7c46244f1">viennacl::coordinate_matrix::handle12</a></div><div class="ttdeci">const handle_type & handle12() const </div><div class="ttdoc">Returns the OpenCL handle to the (row, column) index array. </div><div class="ttdef"><b>Definition:</b> <a href="coordinate__matrix_8hpp_source.html#l00366">coordinate_matrix.hpp:366</a></div></div>
<div class="ttc" id="classviennacl_1_1hyb__matrix_html_a71a65b6963fe30384f160f4cf6c189c8"><div class="ttname"><a href="classviennacl_1_1hyb__matrix.html#a71a65b6963fe30384f160f4cf6c189c8">viennacl::hyb_matrix::internal_size1</a></div><div class="ttdeci">vcl_size_t internal_size1() const </div><div class="ttdef"><b>Definition:</b> <a href="hyb__matrix_8hpp_source.html#l00095">hyb_matrix.hpp:95</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_aa1f80e9f52a434ea819a0a38c91223a4"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#aa1f80e9f52a434ea819a0a38c91223a4">viennacl::linalg::host_based::pipelined_cg_vector_update</a></div><div class="ttdeci">void pipelined_cg_vector_update(vector_base< NumericT > &result, NumericT alpha, vector_base< NumericT > &p, vector_base< NumericT > &r, vector_base< NumericT > const &Ap, NumericT beta, vector_base< NumericT > &inner_prod_buffer)</div><div class="ttdoc">Performs a joint vector update operation needed for an efficient pipelined CG algorithm. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2iterative__operations_8hpp_source.html#l00367">iterative_operations.hpp:367</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_a8e4aac801d1aeb7868dad15fc9691485"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#a8e4aac801d1aeb7868dad15fc9691485">viennacl::linalg::host_based::pipelined_gmres_gram_schmidt_stage2</a></div><div class="ttdeci">void pipelined_gmres_gram_schmidt_stage2(vector_base< T > &device_krylov_basis, vcl_size_t v_k_size, vcl_size_t v_k_internal_size, vcl_size_t k, vector_base< T > const &vi_in_vk_buffer, vector_base< T > &R_buffer, vcl_size_t krylov_dim, vector_base< T > &inner_prod_buffer, vcl_size_t buffer_chunk_size)</div><div class="ttdoc">Computes the second reduction stage for multiple inner products <v_i, v_k>, i=0..k-1, then updates v_k -= <v_i, v_k> v_i and computes the first reduction stage for ||v_k||. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2iterative__operations_8hpp_source.html#l00792">iterative_operations.hpp:792</a></div></div>
<div class="ttc" id="forwards_8h_html"><div class="ttname"><a href="forwards_8h.html">forwards.h</a></div><div class="ttdoc">This file provides the forward declarations for the main types used within ViennaCL. </div></div>
<div class="ttc" id="classviennacl_1_1coordinate__matrix_html_a04c51b826e4bae9c97a3749ee2161b87"><div class="ttname"><a href="classviennacl_1_1coordinate__matrix.html#a04c51b826e4bae9c97a3749ee2161b87">viennacl::coordinate_matrix::nnz</a></div><div class="ttdeci">vcl_size_t nnz() const </div><div class="ttdoc">Returns the number of nonzero entries. </div><div class="ttdef"><b>Definition:</b> <a href="coordinate__matrix_8hpp_source.html#l00361">coordinate_matrix.hpp:361</a></div></div>
<div class="ttc" id="stride_8hpp_html"><div class="ttname"><a href="stride_8hpp.html">stride.hpp</a></div><div class="ttdoc">Determines row and column increments for matrices and matrix proxies. </div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_1_1spai_html_a7eeb3f2f51183bed7e6d0a1aeefc87bc"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail_1_1spai.html#a7eeb3f2f51183bed7e6d0a1aeefc87bc">viennacl::linalg::detail::spai::dot_prod</a></div><div class="ttdeci">void dot_prod(MatrixT const &A, unsigned int beg_ind, NumericT &res)</div><div class="ttdoc">Dot prod of particular column of martix A with it's self starting at a certain index beg_ind...</div><div class="ttdef"><b>Definition:</b> <a href="detail_2spai_2qr_8hpp_source.html#l00182">qr.hpp:182</a></div></div>
<div class="ttc" id="classviennacl_1_1hyb__matrix_html_acd8b0197ad9c5a92ed26cf6ec3ce6137"><div class="ttname"><a href="classviennacl_1_1hyb__matrix.html#acd8b0197ad9c5a92ed26cf6ec3ce6137">viennacl::hyb_matrix::handle4</a></div><div class="ttdeci">const handle_type & handle4() const </div><div class="ttdef"><b>Definition:</b> <a href="hyb__matrix_8hpp_source.html#l00108">hyb_matrix.hpp:108</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_aa9a7f4003687cae9a2af97f9fa328db5"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#aa9a7f4003687cae9a2af97f9fa328db5">viennacl::sliced_ell_matrix::rows_per_block</a></div><div class="ttdeci">vcl_size_t rows_per_block() const </div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00104">sliced_ell_matrix.hpp:104</a></div></div>
<div class="ttc" id="classviennacl_1_1compressed__matrix_html_a87a0ad5f26983b1c2d24ee302d886562"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html#a87a0ad5f26983b1c2d24ee302d886562">viennacl::compressed_matrix::handle</a></div><div class="ttdeci">const handle_type & handle() const </div><div class="ttdoc">Returns the OpenCL handle to the matrix entry array. </div><div class="ttdef"><b>Definition:</b> <a href="compressed__matrix_8hpp_source.html#l00942">compressed_matrix.hpp:942</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_ac78885423ca2ebe2205b29a213883c61"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#ac78885423ca2ebe2205b29a213883c61">viennacl::linalg::host_based::pipelined_bicgstab_prod</a></div><div class="ttdeci">void pipelined_bicgstab_prod(compressed_matrix< NumericT > const &A, vector_base< NumericT > const &p, vector_base< NumericT > &Ap, vector_base< NumericT > const &r0star, vector_base< NumericT > &inner_prod_buffer, vcl_size_t buffer_chunk_size, vcl_size_t buffer_chunk_offset)</div><div class="ttdoc">Performs a fused matrix-vector product with a compressed_matrix for an efficient pipelined BiCGStab a...</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2iterative__operations_8hpp_source.html#l00607">iterative_operations.hpp:607</a></div></div>
<div class="ttc" id="classviennacl_1_1compressed__matrix_html_af71dec61a70e8df4f78a527aa989a106"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html#af71dec61a70e8df4f78a527aa989a106">viennacl::compressed_matrix::handle1</a></div><div class="ttdeci">const handle_type & handle1() const </div><div class="ttdoc">Returns the OpenCL handle to the row index array. </div><div class="ttdef"><b>Definition:</b> <a href="compressed__matrix_8hpp_source.html#l00936">compressed_matrix.hpp:936</a></div></div>
<div class="ttc" id="classviennacl_1_1ell__matrix_html_af2e571bfc69f9f0acf3e9b19ce2b9b9f"><div class="ttname"><a href="classviennacl_1_1ell__matrix.html#af2e571bfc69f9f0acf3e9b19ce2b9b9f">viennacl::ell_matrix::internal_size1</a></div><div class="ttdeci">vcl_size_t internal_size1() const </div><div class="ttdef"><b>Definition:</b> <a href="ell__matrix_8hpp_source.html#l00088">ell_matrix.hpp:88</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_abbc671358c44037b7c2b22a01f17c3a7"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#abbc671358c44037b7c2b22a01f17c3a7">viennacl::sliced_ell_matrix::handle</a></div><div class="ttdeci">handle_type & handle()</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00118">sliced_ell_matrix.hpp:118</a></div></div>
<div class="ttc" id="tests_2src_2bisect_8cpp_html_a52b5d30a2d7b064678644a3bf49b7f6c"><div class="ttname"><a href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a></div><div class="ttdeci">float NumericT</div><div class="ttdef"><b>Definition:</b> <a href="tests_2src_2bisect_8cpp_source.html#l00040">bisect.cpp:40</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_ae379e200baf8decb11531e9284252bd8"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#ae379e200baf8decb11531e9284252bd8">viennacl::linalg::host_based::pipelined_bicgstab_vector_update</a></div><div class="ttdeci">void pipelined_bicgstab_vector_update(vector_base< NumericT > &result, NumericT alpha, vector_base< NumericT > &p, NumericT omega, vector_base< NumericT > const &s, vector_base< NumericT > &residual, vector_base< NumericT > const &As, NumericT beta, vector_base< NumericT > const &Ap, vector_base< NumericT > const &r0star, vector_base< NumericT > &inner_prod_buffer, vcl_size_t buffer_chunk_size)</div><div class="ttdoc">Performs a joint vector update operation needed for an efficient pipelined BiCGStab algorithm...</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2iterative__operations_8hpp_source.html#l00554">iterative_operations.hpp:554</a></div></div>
<div class="ttc" id="classviennacl_1_1hyb__matrix_html_a83cb07a6aa15fcf960b40b4a82fdc574"><div class="ttname"><a href="classviennacl_1_1hyb__matrix.html#a83cb07a6aa15fcf960b40b4a82fdc574">viennacl::hyb_matrix::handle2</a></div><div class="ttdeci">const handle_type & handle2() const </div><div class="ttdef"><b>Definition:</b> <a href="hyb__matrix_8hpp_source.html#l00106">hyb_matrix.hpp:106</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_aa2344ea20469f55fbc15a8e9526494d0"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a></div><div class="ttdeci">vcl_size_t size(VectorType const &vec)</div><div class="ttdoc">Generic routine for obtaining the size of a vector (ViennaCL, uBLAS, etc.) </div><div class="ttdef"><b>Definition:</b> <a href="size_8hpp_source.html#l00239">size.hpp:239</a></div></div>
<div class="ttc" id="classviennacl_1_1ell__matrix_html"><div class="ttname"><a href="classviennacl_1_1ell__matrix.html">viennacl::ell_matrix</a></div><div class="ttdoc">Sparse matrix class using the ELLPACK format for storing the nonzeros. </div><div class="ttdef"><b>Definition:</b> <a href="ell__matrix_8hpp_source.html#l00053">ell_matrix.hpp:53</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html">viennacl::sliced_ell_matrix</a></div><div class="ttdoc">Sparse matrix class using the sliced ELLPACK with parameters C, . </div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00403">forwards.h:403</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_a68603a1e1ca1bfb6d107831ba5096786"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a></div><div class="ttdeci">result_of::size_type< T >::type start(T const &obj)</div><div class="ttdef"><b>Definition:</b> <a href="start_8hpp_source.html#l00044">start.hpp:44</a></div></div>
<div class="ttc" id="classviennacl_1_1compressed__matrix_html_a91f5145351151a66f916bdc3901206f2"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html#a91f5145351151a66f916bdc3901206f2">viennacl::compressed_matrix::handle2</a></div><div class="ttdeci">const handle_type & handle2() const </div><div class="ttdoc">Returns the OpenCL handle to the column index array. </div><div class="ttdef"><b>Definition:</b> <a href="compressed__matrix_8hpp_source.html#l00938">compressed_matrix.hpp:938</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html"><div class="ttname"><a href="classviennacl_1_1vector__base.html">viennacl::vector_base< NumericT ></a></div></div>
<div class="ttc" id="namespaceviennacl_html_a98a0afcc513111ffa0bd138f891930df"><div class="ttname"><a href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">viennacl::vcl_size_t</a></div><div class="ttdeci">std::size_t vcl_size_t</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00075">forwards.h:75</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_a16cd8194ca5b263de32f131362498d77"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a16cd8194ca5b263de32f131362498d77">viennacl::sliced_ell_matrix::size1</a></div><div class="ttdeci">vcl_size_t size1() const </div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00101">sliced_ell_matrix.hpp:101</a></div></div>
<div class="ttc" id="linalg_2host__based_2common_8hpp_html"><div class="ttname"><a href="linalg_2host__based_2common_8hpp.html">common.hpp</a></div><div class="ttdoc">Common routines for single-threaded or OpenMP-enabled execution on CPU. </div></div>
<div class="ttc" id="namespaceviennacl_html_a0a574e6cd04ca0e42298b4ab845700e4"><div class="ttname"><a href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">viennacl::row</a></div><div class="ttdeci">vector_expression< const matrix_base< NumericT, F >, const unsigned int, op_row > row(const matrix_base< NumericT, F > &A, unsigned int i)</div><div class="ttdef"><b>Definition:</b> <a href="matrix_8hpp_source.html#l00910">matrix.hpp:910</a></div></div>
<div class="ttc" id="predicate_8hpp_html"><div class="ttname"><a href="predicate_8hpp.html">predicate.hpp</a></div><div class="ttdoc">All the predicates used within ViennaCL. Checks for expressions to be vectors, etc. </div></div>
<div class="ttc" id="classviennacl_1_1ell__matrix_html_a7fe5450dbe53bb797938aa920d4bbb68"><div class="ttname"><a href="classviennacl_1_1ell__matrix.html#a7fe5450dbe53bb797938aa920d4bbb68">viennacl::ell_matrix::handle</a></div><div class="ttdeci">handle_type & handle()</div><div class="ttdef"><b>Definition:</b> <a href="ell__matrix_8hpp_source.html#l00100">ell_matrix.hpp:100</a></div></div>
<div class="ttc" id="classviennacl_1_1coordinate__matrix_html_aeb74dd2ab673d7912a17f60777e9bf6c"><div class="ttname"><a href="classviennacl_1_1coordinate__matrix.html#aeb74dd2ab673d7912a17f60777e9bf6c">viennacl::coordinate_matrix::handle</a></div><div class="ttdeci">const handle_type & handle() const </div><div class="ttdoc">Returns the OpenCL handle to the matrix entry array. </div><div class="ttdef"><b>Definition:</b> <a href="coordinate__matrix_8hpp_source.html#l00368">coordinate_matrix.hpp:368</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_a9cca5888f4345b3b4f3339c74dbf9042"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#a9cca5888f4345b3b4f3339c74dbf9042">viennacl::linalg::host_based::pipelined_cg_prod</a></div><div class="ttdeci">void pipelined_cg_prod(compressed_matrix< NumericT > const &A, vector_base< NumericT > const &p, vector_base< NumericT > &Ap, vector_base< NumericT > &inner_prod_buffer)</div><div class="ttdoc">Performs a fused matrix-vector product with a compressed_matrix for an efficient pipelined CG algorit...</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2iterative__operations_8hpp_source.html#l00413">iterative_operations.hpp:413</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_html_a6a0b43a49ee675bc1f60fcc5a8e4f884"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a6a0b43a49ee675bc1f60fcc5a8e4f884">viennacl::linalg::host_based::detail::pipelined_prod_impl</a></div><div class="ttdeci">void pipelined_prod_impl(compressed_matrix< NumericT > const &A, vector_base< NumericT > const &p, vector_base< NumericT > &Ap, NumericT const *r0star, vector_base< NumericT > &inner_prod_buffer, vcl_size_t buffer_chunk_size, vcl_size_t buffer_chunk_offset)</div><div class="ttdoc">Implementation of a fused matrix-vector product with a compressed_matrix for an efficient pipelined C...</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2iterative__operations_8hpp_source.html#l00061">iterative_operations.hpp:61</a></div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_aa59ae796d592a679a4c6036ba84f61b0"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#aa59ae796d592a679a4c6036ba84f61b0">viennacl::sliced_ell_matrix::handle3</a></div><div class="ttdeci">handle_type & handle3()</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00115">sliced_ell_matrix.hpp:115</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_ac1b61075d4b2a3d605fb08dc0dca95ea"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#ac1b61075d4b2a3d605fb08dc0dca95ea">viennacl::linalg::host_based::pipelined_bicgstab_update_s</a></div><div class="ttdeci">void pipelined_bicgstab_update_s(vector_base< NumericT > &s, vector_base< NumericT > &r, vector_base< NumericT > const &Ap, vector_base< NumericT > &inner_prod_buffer, vcl_size_t buffer_chunk_size, vcl_size_t buffer_chunk_offset)</div><div class="ttdoc">Performs a joint vector update operation needed for an efficient pipelined BiCGStab algorithm...</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2iterative__operations_8hpp_source.html#l00504">iterative_operations.hpp:504</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html_a15c47ae4326098aeaa4ed6b91fc6df9b"><div class="ttname"><a href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">viennacl::vector_base::size</a></div><div class="ttdeci">size_type size() const </div><div class="ttdoc">Returns the length of the vector (cf. std::vector) </div><div class="ttdef"><b>Definition:</b> <a href="vector__def_8hpp_source.html#l00118">vector_def.hpp:118</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_af497e625d846f3e219b9467b82cda386"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#af497e625d846f3e219b9467b82cda386">viennacl::linalg::host_based::pipelined_gmres_update_result</a></div><div class="ttdeci">void pipelined_gmres_update_result(vector_base< T > &result, vector_base< T > const &residual, vector_base< T > const &krylov_basis, vcl_size_t v_k_size, vcl_size_t v_k_internal_size, vector_base< T > const &coefficients, vcl_size_t k)</div><div class="ttdoc">Computes x += eta_0 r + sum_{i=1}^{k-1} eta_i v_{i-1}. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2iterative__operations_8hpp_source.html#l00836">iterative_operations.hpp:836</a></div></div>
<div class="ttc" id="classviennacl_1_1compressed__matrix_html"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html">viennacl::compressed_matrix< NumericT ></a></div></div>
<div class="ttc" id="classviennacl_1_1hyb__matrix_html_aed5ff60ddfef1cd59108064a5d4cdd7f"><div class="ttname"><a href="classviennacl_1_1hyb__matrix.html#aed5ff60ddfef1cd59108064a5d4cdd7f">viennacl::hyb_matrix::handle5</a></div><div class="ttdeci">const handle_type & handle5() const </div><div class="ttdef"><b>Definition:</b> <a href="hyb__matrix_8hpp_source.html#l00109">hyb_matrix.hpp:109</a></div></div>
<div class="ttc" id="classviennacl_1_1hyb__matrix_html_ab5f077832dd0efade9f5037327a1786d"><div class="ttname"><a href="classviennacl_1_1hyb__matrix.html#ab5f077832dd0efade9f5037327a1786d">viennacl::hyb_matrix::size1</a></div><div class="ttdeci">vcl_size_t size1() const </div><div class="ttdef"><b>Definition:</b> <a href="hyb__matrix_8hpp_source.html#l00098">hyb_matrix.hpp:98</a></div></div>
<div class="ttc" id="classviennacl_1_1ell__matrix_html_ae3280590756e720a8d8dacdeed4b702a"><div class="ttname"><a href="classviennacl_1_1ell__matrix.html#ae3280590756e720a8d8dacdeed4b702a">viennacl::ell_matrix::internal_maxnnz</a></div><div class="ttdeci">vcl_size_t internal_maxnnz() const </div><div class="ttdef"><b>Definition:</b> <a href="ell__matrix_8hpp_source.html#l00094">ell_matrix.hpp:94</a></div></div>
<div class="ttc" id="op__applier_8hpp_html"><div class="ttname"><a href="op__applier_8hpp.html">op_applier.hpp</a></div><div class="ttdoc">Defines the action of certain unary and binary operators and its arguments (for host execution)...</div></div>
<div class="ttc" id="classviennacl_1_1sliced__ell__matrix_html_a94043424c01974b2db8062f74f625825"><div class="ttname"><a href="classviennacl_1_1sliced__ell__matrix.html#a94043424c01974b2db8062f74f625825">viennacl::sliced_ell_matrix::handle1</a></div><div class="ttdeci">handle_type & handle1()</div><div class="ttdef"><b>Definition:</b> <a href="sliced__ell__matrix_8hpp_source.html#l00109">sliced_ell_matrix.hpp:109</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_aa17b7680809f798794a5c2dc863931a6"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#aa17b7680809f798794a5c2dc863931a6">viennacl::linalg::host_based::pipelined_gmres_gram_schmidt_stage1</a></div><div class="ttdeci">void pipelined_gmres_gram_schmidt_stage1(vector_base< T > const &device_krylov_basis, vcl_size_t v_k_size, vcl_size_t v_k_internal_size, vcl_size_t k, vector_base< T > &vi_in_vk_buffer, vcl_size_t buffer_chunk_size)</div><div class="ttdoc">Computes first reduction stage for multiple inner products <v_i, v_k>, i=0..k-1. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2iterative__operations_8hpp_source.html#l00760">iterative_operations.hpp:760</a></div></div>
<div class="ttc" id="scalar_8hpp_html"><div class="ttname"><a href="scalar_8hpp.html">scalar.hpp</a></div><div class="ttdoc">Implementation of the ViennaCL scalar class. </div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html_a64e98aea5aa298ad63e3832a04c19648"><div class="ttname"><a href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">viennacl::vector_base::handle</a></div><div class="ttdeci">const handle_type & handle() const </div><div class="ttdoc">Returns the memory handle. </div><div class="ttdef"><b>Definition:</b> <a href="vector__def_8hpp_source.html#l00128">vector_def.hpp:128</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_aeb57ebff0a27bc75b9340df9a99bf155"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#aeb57ebff0a27bc75b9340df9a99bf155">viennacl::linalg::host_based::pipelined_gmres_prod</a></div><div class="ttdeci">void pipelined_gmres_prod(MatrixType const &A, vector_base< T > const &p, vector_base< T > &Ap, vector_base< T > &inner_prod_buffer)</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2iterative__operations_8hpp_source.html#l00866">iterative_operations.hpp:866</a></div></div>
<div class="ttc" id="enable__if_8hpp_html"><div class="ttname"><a href="enable__if_8hpp.html">enable_if.hpp</a></div><div class="ttdoc">Simple enable-if variant that uses the SFINAE pattern. </div></div>
<div class="ttc" id="classviennacl_1_1coordinate__matrix_html"><div class="ttname"><a href="classviennacl_1_1coordinate__matrix.html">viennacl::coordinate_matrix</a></div><div class="ttdoc">A sparse square matrix, where entries are stored as triplets (i,j, val), where i and j are the row an...</div><div class="ttdef"><b>Definition:</b> <a href="coordinate__matrix_8hpp_source.html#l00186">coordinate_matrix.hpp:186</a></div></div>
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