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<div class="title">vector_operations.hpp</div> </div>
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<a href="host__based_2vector__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_VECTOR_OPERATIONS_HPP_</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="preprocessor">#define VIENNACL_LINALG_HOST_BASED_VECTOR_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> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="preprocessor">#include <omp.h></span></div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="comment">// Minimum vector size for using OpenMP on vector operations:</span></div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="preprocessor">#ifndef VIENNACL_OPENMP_VECTOR_MIN_SIZE</span></div>
<div class="line"><a name="l00045"></a><span class="lineno"><a class="line" href="host__based_2vector__operations_8hpp.html#aa1b0719a06924fc82f8d8ed6c739a04d"> 45</a></span> <span class="preprocessor"> #define VIENNACL_OPENMP_VECTOR_MIN_SIZE 5000</span></div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span> </div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="keyword">namespace </span>viennacl</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span> {</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="keyword">namespace </span>linalg</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>host_based</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span> {</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="keyword">namespace </span>detail</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span> {</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00057"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#abd382e4bde97fb842b7b52b2b4d36379"> 57</a></span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#abd382e4bde97fb842b7b52b2b4d36379">flip_sign</a>(<a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> val) { <span class="keywordflow">return</span> -val; }</div>
<div class="line"><a name="l00058"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#ae3225408ae3e81b004fab27aeb6a9482"> 58</a></span>  <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">long</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#abd382e4bde97fb842b7b52b2b4d36379">flip_sign</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">long</span> val) { <span class="keywordflow">return</span> val; }</div>
<div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a9d0a372a4ffd0c6347ecff6046ca4dec"> 59</a></span>  <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#abd382e4bde97fb842b7b52b2b4d36379">flip_sign</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> val) { <span class="keywordflow">return</span> val; }</div>
<div class="line"><a name="l00060"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a7446f9329fa901df46a4f487a43601ca"> 60</a></span>  <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">short</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#abd382e4bde97fb842b7b52b2b4d36379">flip_sign</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">short</span> val) { <span class="keywordflow">return</span> val; }</div>
<div class="line"><a name="l00061"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a306a6b1400991db3671a1511fa8f6f40"> 61</a></span>  <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#abd382e4bde97fb842b7b52b2b4d36379">flip_sign</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span> val) { <span class="keywordflow">return</span> val; }</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span> }</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="comment">//</span></div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="comment">// Introductory note: By convention, all dimensions are already checked in the dispatcher frontend. No need to double-check again in here!</span></div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="comment">//</span></div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="keyword">template</span><<span class="keyword">typename</span> DestNumericT, <span class="keyword">typename</span> SrcNumericT></div>
<div class="line"><a name="l00068"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a4741c01014517323f006507e09de2143"> 68</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a4fe3f1e7af78cbeb1125758a635eb99d">convert</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<DestNumericT></a> & dest, <a class="code" href="classviennacl_1_1vector__base.html">vector_base<SrcNumericT></a> <span class="keyword">const</span> & src)</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span> {</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  DestNumericT * data_dest = detail::extract_raw_pointer<DestNumericT>(dest);</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  SrcNumericT <span class="keyword">const</span> * data_src = detail::extract_raw_pointer<SrcNumericT>(src);</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> start_dest = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(dest);</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc_dest = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(dest);</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> size_dest = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(dest);</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> start_src = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(src);</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc_src = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(src);</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="preprocessor"> #pragma omp parallel for if (size_dest > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordflow">for</span> (<span class="keywordtype">long</span> i = 0; i < static_cast<long>(size_dest); ++i)</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  data_dest[static_cast<vcl_size_t>(i)*inc_dest+start_dest] = <span class="keyword">static_cast<</span>DestNumericT<span class="keyword">></span>(data_src[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc_src+start_src]);</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> </div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> ScalarT1></div>
<div class="line"><a name="l00088"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a47e4fa3cd849b7beab25f195633a38ad"> 88</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a47e4fa3cd849b7beab25f195633a38ad">av</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec1,</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec2, ScalarT1 <span class="keyword">const</span> & alpha, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <span class="comment">/*len_alpha*/</span>, <span class="keywordtype">bool</span> reciprocal_alpha, <span class="keywordtype">bool</span> flip_sign_alpha)</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span> {</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</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="l00092"></a><span class="lineno"> 92</span> </div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  value_type * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  value_type <span class="keyword">const</span> * data_vec2 = detail::extract_raw_pointer<value_type>(vec2);</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>  value_type data_alpha = alpha;</div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordflow">if</span> (flip_sign_alpha)</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  data_alpha = <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#abd382e4bde97fb842b7b52b2b4d36379">detail::flip_sign</a>(data_alpha);</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</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>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2);</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc2 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2);</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keywordflow">if</span> (reciprocal_alpha)</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  {</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>] = data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2] / data_alpha;</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  }</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  {</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>] = data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2] * data_alpha;</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  }</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span> }</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span> </div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> ScalarT1, <span class="keyword">typename</span> ScalarT2></div>
<div class="line"><a name="l00127"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a7634739b4c75267d38297dfcb19fad63"> 127</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a7634739b4c75267d38297dfcb19fad63">avbv</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec1,</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec2, ScalarT1 <span class="keyword">const</span> & alpha, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <span class="comment">/* len_alpha */</span>, <span class="keywordtype">bool</span> reciprocal_alpha, <span class="keywordtype">bool</span> flip_sign_alpha,</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec3, ScalarT2 <span class="keyword">const</span> & beta, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <span class="comment">/* len_beta */</span>, <span class="keywordtype">bool</span> reciprocal_beta, <span class="keywordtype">bool</span> flip_sign_beta)</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span> {</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</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="l00132"></a><span class="lineno"> 132</span> </div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  value_type * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  value_type <span class="keyword">const</span> * data_vec2 = detail::extract_raw_pointer<value_type>(vec2);</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  value_type <span class="keyword">const</span> * data_vec3 = detail::extract_raw_pointer<value_type>(vec3);</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span> </div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  value_type data_alpha = alpha;</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="keywordflow">if</span> (flip_sign_alpha)</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  data_alpha = <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#abd382e4bde97fb842b7b52b2b4d36379">detail::flip_sign</a>(data_alpha);</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  value_type data_beta = beta;</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="keywordflow">if</span> (flip_sign_beta)</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  data_beta = <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#abd382e4bde97fb842b7b52b2b4d36379">detail::flip_sign</a>(data_beta);</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2);</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc2 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2);</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> start3 = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec3);</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc3 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec3);</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span> </div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keywordflow">if</span> (reciprocal_alpha)</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>  <span class="keywordflow">if</span> (reciprocal_beta)</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  {</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>] = data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2] / data_alpha + data_vec3[static_cast<vcl_size_t>(i)*inc3+start3] / data_beta;</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  }</div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  {</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>] = data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2] / data_alpha + data_vec3[static_cast<vcl_size_t>(i)*inc3+start3] * data_beta;</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>  }</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  {</div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keywordflow">if</span> (reciprocal_beta)</div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  {</div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>] = data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2] * data_alpha + data_vec3[static_cast<vcl_size_t>(i)*inc3+start3] / data_beta;</div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  }</div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordflow">else</span></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> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>] = data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2] * data_alpha + data_vec3[static_cast<vcl_size_t>(i)*inc3+start3] * data_beta;</div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  }</div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  }</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> </div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> ScalarT1, <span class="keyword">typename</span> ScalarT2></div>
<div class="line"><a name="l00197"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a9e173eb4a7b8b63e7bddb53074d764ec"> 197</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a9e173eb4a7b8b63e7bddb53074d764ec">avbv_v</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec1,</div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec2, ScalarT1 <span class="keyword">const</span> & alpha, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <span class="comment">/*len_alpha*/</span>, <span class="keywordtype">bool</span> reciprocal_alpha, <span class="keywordtype">bool</span> flip_sign_alpha,</div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec3, ScalarT2 <span class="keyword">const</span> & beta, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <span class="comment">/*len_beta*/</span>, <span class="keywordtype">bool</span> reciprocal_beta, <span class="keywordtype">bool</span> flip_sign_beta)</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span> {</div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</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="l00202"></a><span class="lineno"> 202</span> </div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  value_type * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  value_type <span class="keyword">const</span> * data_vec2 = detail::extract_raw_pointer<value_type>(vec2);</div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  value_type <span class="keyword">const</span> * data_vec3 = detail::extract_raw_pointer<value_type>(vec3);</div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span> </div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  value_type data_alpha = alpha;</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keywordflow">if</span> (flip_sign_alpha)</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  data_alpha = <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#abd382e4bde97fb842b7b52b2b4d36379">detail::flip_sign</a>(data_alpha);</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span> </div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  value_type data_beta = beta;</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="keywordflow">if</span> (flip_sign_beta)</div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  data_beta = <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#abd382e4bde97fb842b7b52b2b4d36379">detail::flip_sign</a>(data_beta);</div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span> </div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span> </div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2);</div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc2 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2);</div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span> </div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> start3 = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec3);</div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc3 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec3);</div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span> </div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordflow">if</span> (reciprocal_alpha)</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  {</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="keywordflow">if</span> (reciprocal_beta)</div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  {</div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>] += data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2] / data_alpha + data_vec3[static_cast<vcl_size_t>(i)*inc3+start3] / data_beta;</div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  }</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  {</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>] += data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2] / data_alpha + data_vec3[static_cast<vcl_size_t>(i)*inc3+start3] * data_beta;</div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  }</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>  <span class="keywordflow">else</span></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">if</span> (reciprocal_beta)</div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  {</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>] += data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2] * data_alpha + data_vec3[static_cast<vcl_size_t>(i)*inc3+start3] / data_beta;</div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  }</div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  {</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>] += data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2] * data_alpha + data_vec3[static_cast<vcl_size_t>(i)*inc3+start3] * data_beta;</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> </div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span> </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> </div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00275"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a38954effaaf57109159e51a31293a6c1"> 275</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a38954effaaf57109159e51a31293a6c1">vector_assign</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec1, <span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> & alpha, <span class="keywordtype">bool</span> up_to_internal_size = <span class="keyword">false</span>)</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>  <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="l00278"></a><span class="lineno"> 278</span> </div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  value_type * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span> </div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> loop_bound = up_to_internal_size ? vec1.<a class="code" href="classviennacl_1_1vector__base.html#a47350ccdc4b0a24eaea0e8d5f9fe7fec">internal_size</a>() : <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>; <span class="comment">//Note: Do NOT use traits::internal_size() here, because vector proxies don't require padding.</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>  value_type data_alpha = <span class="keyword">static_cast<</span>value_type<span class="keyword">></span>(alpha);</div>
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span> </div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span> <span class="preprocessor"> #pragma omp parallel for if (loop_bound > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keywordflow">for</span> (<span class="keywordtype">long</span> i = 0; i < static_cast<long>(loop_bound); ++i)</div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>] = data_alpha;</div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span> }</div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span> </div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span> </div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00302"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#ac765726382000520401dc9d70483dabb"> 302</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ac765726382000520401dc9d70483dabb">vector_swap</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec1, <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec2)</div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span> {</div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</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="l00305"></a><span class="lineno"> 305</span> </div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  value_type * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  value_type * data_vec2 = detail::extract_raw_pointer<value_type>(vec2);</div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span> </div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span> </div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2);</div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc2 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2);</div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span> </div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  {</div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  value_type temp = data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2];</div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2] = data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>];</div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  data_vec1[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc1+start1] = temp;</div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  }</div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span> }</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> </div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span> </div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> OpT></div>
<div class="line"><a name="l00336"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#affd4a240838f3d33cfd0f37c4085d558"> 336</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ae02ec8df2561e6d99747334dc2e5cec8">element_op</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec1,</div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <a class="code" href="classviennacl_1_1vector__expression.html">vector_expression</a><<span class="keyword">const</span> <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a>, <span class="keyword">const</span> <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a>, <a class="code" href="structviennacl_1_1op__element__binary.html">op_element_binary<OpT></a> > <span class="keyword">const</span> & proxy)</div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span> {</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</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="l00340"></a><span class="lineno"> 340</span>  <span class="keyword">typedef</span> <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1op__applier.html">viennacl::linalg::detail::op_applier<op_element_binary<OpT></a> > OpFunctor;</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span> </div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  value_type * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  value_type <span class="keyword">const</span> * data_vec2 = detail::extract_raw_pointer<value_type>(proxy.lhs());</div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  value_type <span class="keyword">const</span> * data_vec3 = detail::extract_raw_pointer<value_type>(proxy.rhs());</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span> </div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span> </div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(proxy.lhs());</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc2 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(proxy.lhs());</div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span> </div>
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> start3 = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(proxy.rhs());</div>
<div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc3 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(proxy.rhs());</div>
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span> </div>
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00359"></a><span class="lineno"> 359</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  OpFunctor::apply(data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>], data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2], data_vec3[static_cast<vcl_size_t>(i)*inc3+start3]);</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span> }</div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span> </div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> OpT></div>
<div class="line"><a name="l00369"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#ade366c76e4b0db7585c51d890c88051d"> 369</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ae02ec8df2561e6d99747334dc2e5cec8">element_op</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec1,</div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <a class="code" href="classviennacl_1_1vector__expression.html">vector_expression</a><<span class="keyword">const</span> <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a>, <span class="keyword">const</span> <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a>, <a class="code" href="structviennacl_1_1op__element__unary.html">op_element_unary<OpT></a> > <span class="keyword">const</span> & proxy)</div>
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span> {</div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</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="l00373"></a><span class="lineno"> 373</span>  <span class="keyword">typedef</span> <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1op__applier.html">viennacl::linalg::detail::op_applier<op_element_unary<OpT></a> > OpFunctor;</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>  value_type * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  value_type <span class="keyword">const</span> * data_vec2 = detail::extract_raw_pointer<value_type>(proxy.lhs());</div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span> </div>
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span> </div>
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(proxy.lhs());</div>
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc2 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(proxy.lhs());</div>
<div class="line"><a name="l00384"></a><span class="lineno"> 384</span> </div>
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00386"></a><span class="lineno"> 386</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00388"></a><span class="lineno"> 388</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  OpFunctor::apply(data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>], data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2]);</div>
<div class="line"><a name="l00390"></a><span class="lineno"> 390</span> }</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="l00394"></a><span class="lineno"> 394</span> </div>
<div class="line"><a name="l00395"></a><span class="lineno"> 395</span> </div>
<div class="line"><a name="l00396"></a><span class="lineno"> 396</span> <span class="comment">//implementation of inner product:</span></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> <span class="keyword">namespace </span>detail</div>
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span> {</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> <span class="comment">// the following circumvents problems when trying to use a variable of template parameter type for a reduction.</span></div>
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span> <span class="comment">// Such a behavior is not covered by the OpenMP standard, hence we manually apply some preprocessor magic to resolve the problem.</span></div>
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span> <span class="comment">// See https://github.com/viennacl/viennacl-dev/issues/112 for a detailed explanation and discussion.</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"><a class="line" href="host__based_2vector__operations_8hpp.html#aaf35aadcae50e5e59946aa92b7f22aa2"> 405</a></span> <span class="preprocessor">#define VIENNACL_INNER_PROD_IMPL_1(RESULTSCALART, TEMPSCALART) \</span></div>
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span> <span class="preprocessor"> inline RESULTSCALART inner_prod_impl(RESULTSCALART const * data_vec1, vcl_size_t start1, vcl_size_t inc1, vcl_size_t size1, \</span></div>
<div class="line"><a name="l00407"></a><span class="lineno"> 407</span> <span class="preprocessor"> RESULTSCALART const * data_vec2, vcl_size_t start2, vcl_size_t inc2) { \</span></div>
<div class="line"><a name="l00408"></a><span class="lineno"> 408</span> <span class="preprocessor"> TEMPSCALART temp = 0;</span></div>
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span> </div>
<div class="line"><a name="l00410"></a><span class="lineno"><a class="line" href="host__based_2vector__operations_8hpp.html#a71fb7fd5be61a0297a8d19220cff479b"> 410</a></span> <span class="preprocessor">#define VIENNACL_INNER_PROD_IMPL_2(RESULTSCALART) \</span></div>
<div class="line"><a name="l00411"></a><span class="lineno"> 411</span> <span class="preprocessor"> for (long i = 0; i < static_cast<long>(size1); ++i) \</span></div>
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span> <span class="preprocessor"> temp += data_vec1[static_cast<vcl_size_t>(i)*inc1+start1] * data_vec2[static_cast<vcl_size_t>(i)*inc2+start2]; \</span></div>
<div class="line"><a name="l00413"></a><span class="lineno"> 413</span> <span class="preprocessor"> return static_cast<RESULTSCALART>(temp); \</span></div>
<div class="line"><a name="l00414"></a><span class="lineno"> 414</span> <span class="preprocessor"> }</span></div>
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span> </div>
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span> <span class="comment">// char</span></div>
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span> <a class="code" href="host__based_2vector__operations_8hpp.html#aaf35aadcae50e5e59946aa92b7f22aa2">VIENNACL_INNER_PROD_IMPL_1</a>(<span class="keywordtype">char</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a71fb7fd5be61a0297a8d19220cff479b">VIENNACL_INNER_PROD_IMPL_2</a>(<span class="keywordtype">char</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> <a class="code" href="host__based_2vector__operations_8hpp.html#aaf35aadcae50e5e59946aa92b7f22aa2">VIENNACL_INNER_PROD_IMPL_1</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00424"></a><span class="lineno"> 424</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00425"></a><span class="lineno"> 425</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00427"></a><span class="lineno"> 427</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a71fb7fd5be61a0297a8d19220cff479b">VIENNACL_INNER_PROD_IMPL_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>)</div>
<div class="line"><a name="l00428"></a><span class="lineno"> 428</span> </div>
<div class="line"><a name="l00429"></a><span class="lineno"> 429</span> </div>
<div class="line"><a name="l00430"></a><span class="lineno"> 430</span> <span class="comment">// short</span></div>
<div class="line"><a name="l00431"></a><span class="lineno"> 431</span> <a class="code" href="host__based_2vector__operations_8hpp.html#aaf35aadcae50e5e59946aa92b7f22aa2">VIENNACL_INNER_PROD_IMPL_1</a>(<span class="keywordtype">short</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00432"></a><span class="lineno"> 432</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00433"></a><span class="lineno"> 433</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00434"></a><span class="lineno"> 434</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00435"></a><span class="lineno"> 435</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a71fb7fd5be61a0297a8d19220cff479b">VIENNACL_INNER_PROD_IMPL_2</a>(<span class="keywordtype">short</span>)</div>
<div class="line"><a name="l00436"></a><span class="lineno"> 436</span> </div>
<div class="line"><a name="l00437"></a><span class="lineno"> 437</span> <a class="code" href="host__based_2vector__operations_8hpp.html#aaf35aadcae50e5e59946aa92b7f22aa2">VIENNACL_INNER_PROD_IMPL_1</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">short</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00438"></a><span class="lineno"> 438</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00439"></a><span class="lineno"> 439</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00440"></a><span class="lineno"> 440</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00441"></a><span class="lineno"> 441</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a71fb7fd5be61a0297a8d19220cff479b">VIENNACL_INNER_PROD_IMPL_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">short</span>)</div>
<div class="line"><a name="l00442"></a><span class="lineno"> 442</span> </div>
<div class="line"><a name="l00443"></a><span class="lineno"> 443</span> </div>
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span> <span class="comment">// int</span></div>
<div class="line"><a name="l00445"></a><span class="lineno"> 445</span> <a class="code" href="host__based_2vector__operations_8hpp.html#aaf35aadcae50e5e59946aa92b7f22aa2">VIENNACL_INNER_PROD_IMPL_1</a>(<span class="keywordtype">int</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00446"></a><span class="lineno"> 446</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00448"></a><span class="lineno"> 448</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a71fb7fd5be61a0297a8d19220cff479b">VIENNACL_INNER_PROD_IMPL_2</a>(<span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span> </div>
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span> <a class="code" href="host__based_2vector__operations_8hpp.html#aaf35aadcae50e5e59946aa92b7f22aa2">VIENNACL_INNER_PROD_IMPL_1</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00452"></a><span class="lineno"> 452</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a71fb7fd5be61a0297a8d19220cff479b">VIENNACL_INNER_PROD_IMPL_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</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="l00458"></a><span class="lineno"> 458</span> <span class="comment">// long</span></div>
<div class="line"><a name="l00459"></a><span class="lineno"> 459</span> <a class="code" href="host__based_2vector__operations_8hpp.html#aaf35aadcae50e5e59946aa92b7f22aa2">VIENNACL_INNER_PROD_IMPL_1</a>(<span class="keywordtype">long</span>, <span class="keywordtype">long</span>)</div>
<div class="line"><a name="l00460"></a><span class="lineno"> 460</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00461"></a><span class="lineno"> 461</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00462"></a><span class="lineno"> 462</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00463"></a><span class="lineno"> 463</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a71fb7fd5be61a0297a8d19220cff479b">VIENNACL_INNER_PROD_IMPL_2</a>(<span class="keywordtype">long</span>)</div>
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span> </div>
<div class="line"><a name="l00465"></a><span class="lineno"> 465</span> <a class="code" href="host__based_2vector__operations_8hpp.html#aaf35aadcae50e5e59946aa92b7f22aa2">VIENNACL_INNER_PROD_IMPL_1</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">long</span>, <span class="keywordtype">unsigned</span> <span class="keywordtype">long</span>)</div>
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00469"></a><span class="lineno"> 469</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a71fb7fd5be61a0297a8d19220cff479b">VIENNACL_INNER_PROD_IMPL_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">long</span>)</div>
<div class="line"><a name="l00470"></a><span class="lineno"> 470</span> </div>
<div class="line"><a name="l00471"></a><span class="lineno"> 471</span> </div>
<div class="line"><a name="l00472"></a><span class="lineno"> 472</span> <span class="comment">// float</span></div>
<div class="line"><a name="l00473"></a><span class="lineno"> 473</span> <a class="code" href="host__based_2vector__operations_8hpp.html#aaf35aadcae50e5e59946aa92b7f22aa2">VIENNACL_INNER_PROD_IMPL_1</a>(<span class="keywordtype">float</span>, <span class="keywordtype">float</span>)</div>
<div class="line"><a name="l00474"></a><span class="lineno"> 474</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00475"></a><span class="lineno"> 475</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00476"></a><span class="lineno"> 476</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00477"></a><span class="lineno"> 477</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a71fb7fd5be61a0297a8d19220cff479b">VIENNACL_INNER_PROD_IMPL_2</a>(<span class="keywordtype">float</span>)</div>
<div class="line"><a name="l00478"></a><span class="lineno"> 478</span> </div>
<div class="line"><a name="l00479"></a><span class="lineno"> 479</span> <span class="comment">// double</span></div>
<div class="line"><a name="l00480"></a><span class="lineno"> 480</span> <a class="code" href="host__based_2vector__operations_8hpp.html#aaf35aadcae50e5e59946aa92b7f22aa2">VIENNACL_INNER_PROD_IMPL_1</a>(<span class="keywordtype">double</span>, <span class="keywordtype">double</span>)</div>
<div class="line"><a name="l00481"></a><span class="lineno"> 481</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00482"></a><span class="lineno"> 482</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a71fb7fd5be61a0297a8d19220cff479b">VIENNACL_INNER_PROD_IMPL_2</a>(<span class="keywordtype">double</span>)</div>
<div class="line"><a name="l00485"></a><span class="lineno"> 485</span> </div>
<div class="line"><a name="l00486"></a><span class="lineno"> 486</span> <span class="preprocessor">#undef VIENNACL_INNER_PROD_IMPL_1</span></div>
<div class="line"><a name="l00487"></a><span class="lineno"> 487</span> <span class="preprocessor">#undef VIENNACL_INNER_PROD_IMPL_2</span></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> </div>
<div class="line"><a name="l00496"></a><span class="lineno"> 496</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> ScalarT></div>
<div class="line"><a name="l00497"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#ad78c38a7e4a3ae75bc2e149b28854eaa"> 497</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ad78c38a7e4a3ae75bc2e149b28854eaa">inner_prod_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec2,</div>
<div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  ScalarT & result)</div>
<div class="line"><a name="l00500"></a><span class="lineno"> 500</span> {</div>
<div class="line"><a name="l00501"></a><span class="lineno"> 501</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="l00502"></a><span class="lineno"> 502</span> </div>
<div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  value_type <span class="keyword">const</span> * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  value_type <span class="keyword">const</span> * data_vec2 = detail::extract_raw_pointer<value_type>(vec2);</div>
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span> </div>
<div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span> </div>
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2);</div>
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc2 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2);</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>  result = <a class="code" href="namespaceviennacl_1_1linalg.html#af170246b8ee051270ea2c9fbd141d832">detail::inner_prod_impl</a>(data_vec1, start1, inc1, size1,</div>
<div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  data_vec2, start2, inc2); <span class="comment">//Note: Assignment to result might be expensive, thus a temporary is introduced here</span></div>
<div class="line"><a name="l00515"></a><span class="lineno"> 515</span> }</div>
<div class="line"><a name="l00516"></a><span class="lineno"> 516</span> </div>
<div class="line"><a name="l00517"></a><span class="lineno"> 517</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00518"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#abd70c99f406759e0f1ae2ffc6c9e8fed"> 518</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ad78c38a7e4a3ae75bc2e149b28854eaa">inner_prod_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & x,</div>
<div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <a class="code" href="classviennacl_1_1vector__tuple.html">vector_tuple<NumericT></a> <span class="keyword">const</span> & vec_tuple,</div>
<div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & result)</div>
<div class="line"><a name="l00521"></a><span class="lineno"> 521</span> {</div>
<div class="line"><a name="l00522"></a><span class="lineno"> 522</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="l00523"></a><span class="lineno"> 523</span> </div>
<div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  value_type <span class="keyword">const</span> * data_x = detail::extract_raw_pointer<value_type>(x);</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>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> start_x = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(x);</div>
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc_x = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(x);</div>
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> size_x = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(x);</div>
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span> </div>
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  std::vector<value_type> temp(vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9f2fc8200f0199e396eaeca310f8e9f4">const_size</a>());</div>
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  std::vector<value_type const *> data_y(vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9f2fc8200f0199e396eaeca310f8e9f4">const_size</a>());</div>
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  std::vector<vcl_size_t> start_y(vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9f2fc8200f0199e396eaeca310f8e9f4">const_size</a>());</div>
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  std::vector<vcl_size_t> stride_y(vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9f2fc8200f0199e396eaeca310f8e9f4">const_size</a>());</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>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> j=0; j<vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9f2fc8200f0199e396eaeca310f8e9f4">const_size</a>(); ++j)</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>  data_y[j] = detail::extract_raw_pointer<value_type>(vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(j));</div>
<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  start_y[j] = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(j));</div>
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  stride_y[j] = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">const_at</a>(j));</div>
<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  }</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>  <span class="comment">// Note: No OpenMP here because it cannot perform a reduction on temp-array. Savings in memory bandwidth are expected to still justify this approach...</span></div>
<div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 0; i < size_x; ++i)</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>  value_type entry_x = data_x[i*inc_x+start_x];</div>
<div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> j=0; j < vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9f2fc8200f0199e396eaeca310f8e9f4">const_size</a>(); ++j)</div>
<div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  temp[j] += entry_x * data_y[j][i*stride_y[j]+start_y[j]];</div>
<div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  }</div>
<div class="line"><a name="l00549"></a><span class="lineno"> 549</span> </div>
<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> j=0; j < vec_tuple.<a class="code" href="classviennacl_1_1vector__tuple.html#a9f2fc8200f0199e396eaeca310f8e9f4">const_size</a>(); ++j)</div>
<div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  result[j] = temp[j]; <span class="comment">//Note: Assignment to result might be expensive, thus 'temp' is used for accumulation</span></div>
<div class="line"><a name="l00552"></a><span class="lineno"> 552</span> }</div>
<div class="line"><a name="l00553"></a><span class="lineno"> 553</span> </div>
<div class="line"><a name="l00554"></a><span class="lineno"> 554</span> </div>
<div class="line"><a name="l00555"></a><span class="lineno"> 555</span> <span class="keyword">namespace </span>detail</div>
<div class="line"><a name="l00556"></a><span class="lineno"> 556</span> {</div>
<div class="line"><a name="l00557"></a><span class="lineno"> 557</span> </div>
<div class="line"><a name="l00558"></a><span class="lineno"><a class="line" href="host__based_2vector__operations_8hpp.html#a5ac8ca975475c4350eba91cc3d97ae81"> 558</a></span> <span class="preprocessor">#define VIENNACL_NORM_1_IMPL_1(RESULTSCALART, TEMPSCALART) \</span></div>
<div class="line"><a name="l00559"></a><span class="lineno"> 559</span> <span class="preprocessor"> inline RESULTSCALART norm_1_impl(RESULTSCALART const * data_vec1, vcl_size_t start1, vcl_size_t inc1, vcl_size_t size1) { \</span></div>
<div class="line"><a name="l00560"></a><span class="lineno"> 560</span> <span class="preprocessor"> TEMPSCALART temp = 0;</span></div>
<div class="line"><a name="l00561"></a><span class="lineno"> 561</span> </div>
<div class="line"><a name="l00562"></a><span class="lineno"><a class="line" href="host__based_2vector__operations_8hpp.html#af7aa8317885702b7e1295d9eb802fba5"> 562</a></span> <span class="preprocessor">#define VIENNACL_NORM_1_IMPL_2(RESULTSCALART, TEMPSCALART) \</span></div>
<div class="line"><a name="l00563"></a><span class="lineno"> 563</span> <span class="preprocessor"> for (long i = 0; i < static_cast<long>(size1); ++i) \</span></div>
<div class="line"><a name="l00564"></a><span class="lineno"> 564</span> <span class="preprocessor"> temp += static_cast<TEMPSCALART>(std::fabs(static_cast<double>(data_vec1[static_cast<vcl_size_t>(i)*inc1+start1]))); \</span></div>
<div class="line"><a name="l00565"></a><span class="lineno"> 565</span> <span class="preprocessor"> return static_cast<RESULTSCALART>(temp); \</span></div>
<div class="line"><a name="l00566"></a><span class="lineno"> 566</span> <span class="preprocessor"> }</span></div>
<div class="line"><a name="l00567"></a><span class="lineno"> 567</span> </div>
<div class="line"><a name="l00568"></a><span class="lineno"> 568</span> <span class="comment">// char</span></div>
<div class="line"><a name="l00569"></a><span class="lineno"> 569</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a5ac8ca975475c4350eba91cc3d97ae81">VIENNACL_NORM_1_IMPL_1</a>(<span class="keywordtype">char</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00570"></a><span class="lineno"> 570</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00571"></a><span class="lineno"> 571</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00572"></a><span class="lineno"> 572</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00573"></a><span class="lineno"> 573</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af7aa8317885702b7e1295d9eb802fba5">VIENNACL_NORM_1_IMPL_2</a>(<span class="keywordtype">char</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00574"></a><span class="lineno"> 574</span> </div>
<div class="line"><a name="l00575"></a><span class="lineno"> 575</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a5ac8ca975475c4350eba91cc3d97ae81">VIENNACL_NORM_1_IMPL_1</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00576"></a><span class="lineno"> 576</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00577"></a><span class="lineno"> 577</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00578"></a><span class="lineno"> 578</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00579"></a><span class="lineno"> 579</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af7aa8317885702b7e1295d9eb802fba5">VIENNACL_NORM_1_IMPL_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00580"></a><span class="lineno"> 580</span> </div>
<div class="line"><a name="l00581"></a><span class="lineno"> 581</span> <span class="comment">// short</span></div>
<div class="line"><a name="l00582"></a><span class="lineno"> 582</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a5ac8ca975475c4350eba91cc3d97ae81">VIENNACL_NORM_1_IMPL_1</a>(<span class="keywordtype">short</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00583"></a><span class="lineno"> 583</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00584"></a><span class="lineno"> 584</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00585"></a><span class="lineno"> 585</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00586"></a><span class="lineno"> 586</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af7aa8317885702b7e1295d9eb802fba5">VIENNACL_NORM_1_IMPL_2</a>(<span class="keywordtype">short</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00587"></a><span class="lineno"> 587</span> </div>
<div class="line"><a name="l00588"></a><span class="lineno"> 588</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a5ac8ca975475c4350eba91cc3d97ae81">VIENNACL_NORM_1_IMPL_1</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">short</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00589"></a><span class="lineno"> 589</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00590"></a><span class="lineno"> 590</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00591"></a><span class="lineno"> 591</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00592"></a><span class="lineno"> 592</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af7aa8317885702b7e1295d9eb802fba5">VIENNACL_NORM_1_IMPL_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">short</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00593"></a><span class="lineno"> 593</span> </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> <span class="comment">// int</span></div>
<div class="line"><a name="l00596"></a><span class="lineno"> 596</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a5ac8ca975475c4350eba91cc3d97ae81">VIENNACL_NORM_1_IMPL_1</a>(<span class="keywordtype">int</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00597"></a><span class="lineno"> 597</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00598"></a><span class="lineno"> 598</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00599"></a><span class="lineno"> 599</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00600"></a><span class="lineno"> 600</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af7aa8317885702b7e1295d9eb802fba5">VIENNACL_NORM_1_IMPL_2</a>(<span class="keywordtype">int</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00601"></a><span class="lineno"> 601</span> </div>
<div class="line"><a name="l00602"></a><span class="lineno"> 602</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a5ac8ca975475c4350eba91cc3d97ae81">VIENNACL_NORM_1_IMPL_1</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00603"></a><span class="lineno"> 603</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00604"></a><span class="lineno"> 604</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00605"></a><span class="lineno"> 605</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00606"></a><span class="lineno"> 606</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af7aa8317885702b7e1295d9eb802fba5">VIENNACL_NORM_1_IMPL_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00607"></a><span class="lineno"> 607</span> </div>
<div class="line"><a name="l00608"></a><span class="lineno"> 608</span> </div>
<div class="line"><a name="l00609"></a><span class="lineno"> 609</span> <span class="comment">// long</span></div>
<div class="line"><a name="l00610"></a><span class="lineno"> 610</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a5ac8ca975475c4350eba91cc3d97ae81">VIENNACL_NORM_1_IMPL_1</a>(<span class="keywordtype">long</span>, <span class="keywordtype">long</span>)</div>
<div class="line"><a name="l00611"></a><span class="lineno"> 611</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00612"></a><span class="lineno"> 612</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00613"></a><span class="lineno"> 613</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00614"></a><span class="lineno"> 614</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af7aa8317885702b7e1295d9eb802fba5">VIENNACL_NORM_1_IMPL_2</a>(<span class="keywordtype">long</span>, <span class="keywordtype">long</span>)</div>
<div class="line"><a name="l00615"></a><span class="lineno"> 615</span> </div>
<div class="line"><a name="l00616"></a><span class="lineno"> 616</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a5ac8ca975475c4350eba91cc3d97ae81">VIENNACL_NORM_1_IMPL_1</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">long</span>, <span class="keywordtype">unsigned</span> <span class="keywordtype">long</span>)</div>
<div class="line"><a name="l00617"></a><span class="lineno"> 617</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00618"></a><span class="lineno"> 618</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00619"></a><span class="lineno"> 619</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00620"></a><span class="lineno"> 620</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af7aa8317885702b7e1295d9eb802fba5">VIENNACL_NORM_1_IMPL_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">long</span>, <span class="keywordtype">unsigned</span> <span class="keywordtype">long</span>)</div>
<div class="line"><a name="l00621"></a><span class="lineno"> 621</span> </div>
<div class="line"><a name="l00622"></a><span class="lineno"> 622</span> </div>
<div class="line"><a name="l00623"></a><span class="lineno"> 623</span> <span class="comment">// float</span></div>
<div class="line"><a name="l00624"></a><span class="lineno"> 624</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a5ac8ca975475c4350eba91cc3d97ae81">VIENNACL_NORM_1_IMPL_1</a>(<span class="keywordtype">float</span>, <span class="keywordtype">float</span>)</div>
<div class="line"><a name="l00625"></a><span class="lineno"> 625</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00626"></a><span class="lineno"> 626</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00627"></a><span class="lineno"> 627</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00628"></a><span class="lineno"> 628</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af7aa8317885702b7e1295d9eb802fba5">VIENNACL_NORM_1_IMPL_2</a>(<span class="keywordtype">float</span>, <span class="keywordtype">float</span>)</div>
<div class="line"><a name="l00629"></a><span class="lineno"> 629</span> </div>
<div class="line"><a name="l00630"></a><span class="lineno"> 630</span> <span class="comment">// double</span></div>
<div class="line"><a name="l00631"></a><span class="lineno"> 631</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a5ac8ca975475c4350eba91cc3d97ae81">VIENNACL_NORM_1_IMPL_1</a>(<span class="keywordtype">double</span>, <span class="keywordtype">double</span>)</div>
<div class="line"><a name="l00632"></a><span class="lineno"> 632</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00633"></a><span class="lineno"> 633</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00634"></a><span class="lineno"> 634</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00635"></a><span class="lineno"> 635</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af7aa8317885702b7e1295d9eb802fba5">VIENNACL_NORM_1_IMPL_2</a>(<span class="keywordtype">double</span>, <span class="keywordtype">double</span>)</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> <span class="preprocessor">#undef VIENNACL_NORM_1_IMPL_1</span></div>
<div class="line"><a name="l00638"></a><span class="lineno"> 638</span> <span class="preprocessor">#undef VIENNACL_NORM_1_IMPL_2</span></div>
<div class="line"><a name="l00639"></a><span class="lineno"> 639</span> </div>
<div class="line"><a name="l00640"></a><span class="lineno"> 640</span> }</div>
<div class="line"><a name="l00641"></a><span class="lineno"> 641</span> </div>
<div class="line"><a name="l00647"></a><span class="lineno"> 647</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> ScalarT></div>
<div class="line"><a name="l00648"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#ad21ec9fa116f8f1bd34d426c058c504b"> 648</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ad21ec9fa116f8f1bd34d426c058c504b">norm_1_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  ScalarT & result)</div>
<div class="line"><a name="l00650"></a><span class="lineno"> 650</span> {</div>
<div class="line"><a name="l00651"></a><span class="lineno"> 651</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="l00652"></a><span class="lineno"> 652</span> </div>
<div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  value_type <span class="keyword">const</span> * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</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="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</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>  result = <a class="code" href="namespaceviennacl_1_1linalg.html#a94c58051a4819c96e29cd360e784c68f">detail::norm_1_impl</a>(data_vec1, start1, inc1, size1); <span class="comment">//Note: Assignment to result might be expensive, thus using a temporary for accumulation</span></div>
<div class="line"><a name="l00660"></a><span class="lineno"> 660</span> }</div>
<div class="line"><a name="l00661"></a><span class="lineno"> 661</span> </div>
<div class="line"><a name="l00662"></a><span class="lineno"> 662</span> </div>
<div class="line"><a name="l00663"></a><span class="lineno"> 663</span> </div>
<div class="line"><a name="l00664"></a><span class="lineno"> 664</span> <span class="keyword">namespace </span>detail</div>
<div class="line"><a name="l00665"></a><span class="lineno"> 665</span> {</div>
<div class="line"><a name="l00666"></a><span class="lineno"> 666</span> </div>
<div class="line"><a name="l00667"></a><span class="lineno"><a class="line" href="host__based_2vector__operations_8hpp.html#af97743e472ad389e0ad82849002fd0af"> 667</a></span> <span class="preprocessor">#define VIENNACL_NORM_2_IMPL_1(RESULTSCALART, TEMPSCALART) \</span></div>
<div class="line"><a name="l00668"></a><span class="lineno"> 668</span> <span class="preprocessor"> inline RESULTSCALART norm_2_impl(RESULTSCALART const * data_vec1, vcl_size_t start1, vcl_size_t inc1, vcl_size_t size1) { \</span></div>
<div class="line"><a name="l00669"></a><span class="lineno"> 669</span> <span class="preprocessor"> TEMPSCALART temp = 0;</span></div>
<div class="line"><a name="l00670"></a><span class="lineno"> 670</span> </div>
<div class="line"><a name="l00671"></a><span class="lineno"><a class="line" href="host__based_2vector__operations_8hpp.html#a2fff34b2cb787d5c2ae89f59a93cfde8"> 671</a></span> <span class="preprocessor">#define VIENNACL_NORM_2_IMPL_2(RESULTSCALART, TEMPSCALART) \</span></div>
<div class="line"><a name="l00672"></a><span class="lineno"> 672</span> <span class="preprocessor"> for (long i = 0; i < static_cast<long>(size1); ++i) { \</span></div>
<div class="line"><a name="l00673"></a><span class="lineno"> 673</span> <span class="preprocessor"> RESULTSCALART data = data_vec1[static_cast<vcl_size_t>(i)*inc1+start1]; \</span></div>
<div class="line"><a name="l00674"></a><span class="lineno"> 674</span> <span class="preprocessor"> temp += static_cast<TEMPSCALART>(data * data); \</span></div>
<div class="line"><a name="l00675"></a><span class="lineno"> 675</span> <span class="preprocessor"> } \</span></div>
<div class="line"><a name="l00676"></a><span class="lineno"> 676</span> <span class="preprocessor"> return static_cast<RESULTSCALART>(temp); \</span></div>
<div class="line"><a name="l00677"></a><span class="lineno"> 677</span> <span class="preprocessor"> }</span></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> <span class="comment">// char</span></div>
<div class="line"><a name="l00680"></a><span class="lineno"> 680</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af97743e472ad389e0ad82849002fd0af">VIENNACL_NORM_2_IMPL_1</a>(<span class="keywordtype">char</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00681"></a><span class="lineno"> 681</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00682"></a><span class="lineno"> 682</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00683"></a><span class="lineno"> 683</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00684"></a><span class="lineno"> 684</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a2fff34b2cb787d5c2ae89f59a93cfde8">VIENNACL_NORM_2_IMPL_2</a>(<span class="keywordtype">char</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00685"></a><span class="lineno"> 685</span> </div>
<div class="line"><a name="l00686"></a><span class="lineno"> 686</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af97743e472ad389e0ad82849002fd0af">VIENNACL_NORM_2_IMPL_1</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00687"></a><span class="lineno"> 687</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00688"></a><span class="lineno"> 688</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00689"></a><span class="lineno"> 689</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00690"></a><span class="lineno"> 690</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a2fff34b2cb787d5c2ae89f59a93cfde8">VIENNACL_NORM_2_IMPL_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00691"></a><span class="lineno"> 691</span> </div>
<div class="line"><a name="l00692"></a><span class="lineno"> 692</span> </div>
<div class="line"><a name="l00693"></a><span class="lineno"> 693</span> <span class="comment">// short</span></div>
<div class="line"><a name="l00694"></a><span class="lineno"> 694</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af97743e472ad389e0ad82849002fd0af">VIENNACL_NORM_2_IMPL_1</a>(<span class="keywordtype">short</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00695"></a><span class="lineno"> 695</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00696"></a><span class="lineno"> 696</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00697"></a><span class="lineno"> 697</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00698"></a><span class="lineno"> 698</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a2fff34b2cb787d5c2ae89f59a93cfde8">VIENNACL_NORM_2_IMPL_2</a>(<span class="keywordtype">short</span>, <span class="keywordtype">int</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> <a class="code" href="host__based_2vector__operations_8hpp.html#af97743e472ad389e0ad82849002fd0af">VIENNACL_NORM_2_IMPL_1</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">short</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00701"></a><span class="lineno"> 701</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00702"></a><span class="lineno"> 702</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00703"></a><span class="lineno"> 703</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00704"></a><span class="lineno"> 704</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a2fff34b2cb787d5c2ae89f59a93cfde8">VIENNACL_NORM_2_IMPL_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">short</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00705"></a><span class="lineno"> 705</span> </div>
<div class="line"><a name="l00706"></a><span class="lineno"> 706</span> </div>
<div class="line"><a name="l00707"></a><span class="lineno"> 707</span> <span class="comment">// int</span></div>
<div class="line"><a name="l00708"></a><span class="lineno"> 708</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af97743e472ad389e0ad82849002fd0af">VIENNACL_NORM_2_IMPL_1</a>(<span class="keywordtype">int</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00709"></a><span class="lineno"> 709</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00710"></a><span class="lineno"> 710</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00711"></a><span class="lineno"> 711</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00712"></a><span class="lineno"> 712</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a2fff34b2cb787d5c2ae89f59a93cfde8">VIENNACL_NORM_2_IMPL_2</a>(<span class="keywordtype">int</span>, <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00713"></a><span class="lineno"> 713</span> </div>
<div class="line"><a name="l00714"></a><span class="lineno"> 714</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af97743e472ad389e0ad82849002fd0af">VIENNACL_NORM_2_IMPL_1</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>)</div>
<div class="line"><a name="l00715"></a><span class="lineno"> 715</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00716"></a><span class="lineno"> 716</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00717"></a><span class="lineno"> 717</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00718"></a><span class="lineno"> 718</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a2fff34b2cb787d5c2ae89f59a93cfde8">VIENNACL_NORM_2_IMPL_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>)</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> </div>
<div class="line"><a name="l00721"></a><span class="lineno"> 721</span> <span class="comment">// long</span></div>
<div class="line"><a name="l00722"></a><span class="lineno"> 722</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af97743e472ad389e0ad82849002fd0af">VIENNACL_NORM_2_IMPL_1</a>(<span class="keywordtype">long</span>, <span class="keywordtype">long</span>)</div>
<div class="line"><a name="l00723"></a><span class="lineno"> 723</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00724"></a><span class="lineno"> 724</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00725"></a><span class="lineno"> 725</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00726"></a><span class="lineno"> 726</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a2fff34b2cb787d5c2ae89f59a93cfde8">VIENNACL_NORM_2_IMPL_2</a>(<span class="keywordtype">long</span>, <span class="keywordtype">long</span>)</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> <a class="code" href="host__based_2vector__operations_8hpp.html#af97743e472ad389e0ad82849002fd0af">VIENNACL_NORM_2_IMPL_1</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">long</span>, <span class="keywordtype">unsigned</span> <span class="keywordtype">long</span>)</div>
<div class="line"><a name="l00729"></a><span class="lineno"> 729</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00730"></a><span class="lineno"> 730</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00731"></a><span class="lineno"> 731</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00732"></a><span class="lineno"> 732</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a2fff34b2cb787d5c2ae89f59a93cfde8">VIENNACL_NORM_2_IMPL_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">long</span>, <span class="keywordtype">unsigned</span> <span class="keywordtype">long</span>)</div>
<div class="line"><a name="l00733"></a><span class="lineno"> 733</span> </div>
<div class="line"><a name="l00734"></a><span class="lineno"> 734</span> </div>
<div class="line"><a name="l00735"></a><span class="lineno"> 735</span> <span class="comment">// float</span></div>
<div class="line"><a name="l00736"></a><span class="lineno"> 736</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af97743e472ad389e0ad82849002fd0af">VIENNACL_NORM_2_IMPL_1</a>(<span class="keywordtype">float</span>, <span class="keywordtype">float</span>)</div>
<div class="line"><a name="l00737"></a><span class="lineno"> 737</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00738"></a><span class="lineno"> 738</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00739"></a><span class="lineno"> 739</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00740"></a><span class="lineno"> 740</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a2fff34b2cb787d5c2ae89f59a93cfde8">VIENNACL_NORM_2_IMPL_2</a>(<span class="keywordtype">float</span>, <span class="keywordtype">float</span>)</div>
<div class="line"><a name="l00741"></a><span class="lineno"> 741</span> </div>
<div class="line"><a name="l00742"></a><span class="lineno"> 742</span> <span class="comment">// double</span></div>
<div class="line"><a name="l00743"></a><span class="lineno"> 743</span> <a class="code" href="host__based_2vector__operations_8hpp.html#af97743e472ad389e0ad82849002fd0af">VIENNACL_NORM_2_IMPL_1</a>(<span class="keywordtype">double</span>, <span class="keywordtype">double</span>)</div>
<div class="line"><a name="l00744"></a><span class="lineno"> 744</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00745"></a><span class="lineno"> 745</span> <span class="preprocessor"> #pragma omp parallel for reduction(+: temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00746"></a><span class="lineno"> 746</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00747"></a><span class="lineno"> 747</span> <a class="code" href="host__based_2vector__operations_8hpp.html#a2fff34b2cb787d5c2ae89f59a93cfde8">VIENNACL_NORM_2_IMPL_2</a>(<span class="keywordtype">double</span>, <span class="keywordtype">double</span>)</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> <span class="preprocessor">#undef VIENNACL_NORM_2_IMPL_1</span></div>
<div class="line"><a name="l00750"></a><span class="lineno"> 750</span> <span class="preprocessor">#undef VIENNACL_NORM_2_IMPL_2</span></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="l00760"></a><span class="lineno"> 760</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> ScalarT></div>
<div class="line"><a name="l00761"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a84f017afe97029f92d48c968774f245b"> 761</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a84f017afe97029f92d48c968774f245b">norm_2_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  ScalarT & result)</div>
<div class="line"><a name="l00763"></a><span class="lineno"> 763</span> {</div>
<div class="line"><a name="l00764"></a><span class="lineno"> 764</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="l00765"></a><span class="lineno"> 765</span> </div>
<div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  value_type <span class="keyword">const</span> * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00767"></a><span class="lineno"> 767</span> </div>
<div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</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>  result = std::sqrt(<a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#a430b9424a974bdacda10b5a323976c0a">detail::norm_2_impl</a>(data_vec1, start1, inc1, size1)); <span class="comment">//Note: Assignment to result might be expensive, thus 'temp' is used for accumulation</span></div>
<div class="line"><a name="l00773"></a><span class="lineno"> 773</span> }</div>
<div class="line"><a name="l00774"></a><span class="lineno"> 774</span> </div>
<div class="line"><a name="l00780"></a><span class="lineno"> 780</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> ScalarT></div>
<div class="line"><a name="l00781"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a64a65b7cd5c499e1a2e12ae921ec1ca2"> 781</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a64a65b7cd5c499e1a2e12ae921ec1ca2">norm_inf_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  ScalarT & result)</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>  <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="l00785"></a><span class="lineno"> 785</span> </div>
<div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  value_type <span class="keyword">const</span> * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00787"></a><span class="lineno"> 787</span> </div>
<div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l00791"></a><span class="lineno"> 791</span> </div>
<div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> thread_count=1;</div>
<div class="line"><a name="l00793"></a><span class="lineno"> 793</span> </div>
<div class="line"><a name="l00794"></a><span class="lineno"> 794</span> <span class="preprocessor"> #ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  <span class="keywordflow">if</span>(size1 > <a class="code" href="host__based_2vector__operations_8hpp.html#aa1b0719a06924fc82f8d8ed6c739a04d">VIENNACL_OPENMP_VECTOR_MIN_SIZE</a>)</div>
<div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  thread_count = omp_get_max_threads();</div>
<div class="line"><a name="l00797"></a><span class="lineno"> 797</span> <span class="preprocessor"> #endif</span></div>
<div class="line"><a name="l00798"></a><span class="lineno"> 798</span> </div>
<div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  std::vector<value_type> temp(thread_count);</div>
<div class="line"><a name="l00800"></a><span class="lineno"> 800</span> </div>
<div class="line"><a name="l00801"></a><span class="lineno"> 801</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00802"></a><span class="lineno"> 802</span> <span class="preprocessor"> #pragma omp parallel if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00803"></a><span class="lineno"> 803</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  {</div>
<div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <span class="keywordtype">id</span> = 0;</div>
<div class="line"><a name="l00806"></a><span class="lineno"> 806</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  <span class="keywordtype">id</span> = omp_get_thread_num();</div>
<div class="line"><a name="l00808"></a><span class="lineno"> 808</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00809"></a><span class="lineno"> 809</span> </div>
<div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> begin = (size1 * id) / thread_count;</div>
<div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> end = (size1 * (<span class="keywordtype">id</span> + 1)) / thread_count;</div>
<div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  temp[id] = 0;</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="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = begin; i < end; ++i)</div>
<div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  temp[<span class="keywordtype">id</span>] = std::max<value_type>(temp[<span class="keywordtype">id</span>], static_cast<value_type>(std::fabs(static_cast<double>(data_vec1[i*inc1+start1])))); <span class="comment">//casting to double in order to avoid problems if T is an integer type</span></div>
<div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  }</div>
<div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 1; i < thread_count; ++i)</div>
<div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  temp[0] = std::max<value_type>( temp[0], temp[i]);</div>
<div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  result = temp[0];</div>
<div class="line"><a name="l00820"></a><span class="lineno"> 820</span> }</div>
<div class="line"><a name="l00821"></a><span class="lineno"> 821</span> </div>
<div class="line"><a name="l00822"></a><span class="lineno"> 822</span> <span class="comment">//This function should return a CPU scalar, otherwise statements like</span></div>
<div class="line"><a name="l00823"></a><span class="lineno"> 823</span> <span class="comment">// vcl_rhs[index_norm_inf(vcl_rhs)]</span></div>
<div class="line"><a name="l00824"></a><span class="lineno"> 824</span> <span class="comment">// are ambiguous</span></div>
<div class="line"><a name="l00830"></a><span class="lineno"> 830</span> <span class="comment"></span><span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00831"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#aa9936ab7a49e99f2935f7dc33b95c976"> 831</a></span> <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#aa9936ab7a49e99f2935f7dc33b95c976">index_norm_inf</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec1)</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>  <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="l00834"></a><span class="lineno"> 834</span> </div>
<div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  value_type <span class="keyword">const</span> * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00836"></a><span class="lineno"> 836</span> </div>
<div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> thread_count=1;</div>
<div class="line"><a name="l00841"></a><span class="lineno"> 841</span> </div>
<div class="line"><a name="l00842"></a><span class="lineno"> 842</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  <span class="keywordflow">if</span>(size1 > <a class="code" href="host__based_2vector__operations_8hpp.html#aa1b0719a06924fc82f8d8ed6c739a04d">VIENNACL_OPENMP_VECTOR_MIN_SIZE</a>)</div>
<div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  thread_count = omp_get_max_threads();</div>
<div class="line"><a name="l00845"></a><span class="lineno"> 845</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00846"></a><span class="lineno"> 846</span> </div>
<div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  std::vector<value_type> temp(thread_count);</div>
<div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  std::vector<vcl_size_t> index(thread_count);</div>
<div class="line"><a name="l00849"></a><span class="lineno"> 849</span> </div>
<div class="line"><a name="l00850"></a><span class="lineno"> 850</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00851"></a><span class="lineno"> 851</span> <span class="preprocessor"> #pragma omp parallel if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00852"></a><span class="lineno"> 852</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  {</div>
<div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <span class="keywordtype">id</span> = 0;</div>
<div class="line"><a name="l00855"></a><span class="lineno"> 855</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  <span class="keywordtype">id</span> = omp_get_thread_num();</div>
<div class="line"><a name="l00857"></a><span class="lineno"> 857</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> begin = (size1 * id) / thread_count;</div>
<div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> end = (size1 * (<span class="keywordtype">id</span> + 1)) / thread_count;</div>
<div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  index[id] = <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>;</div>
<div class="line"><a name="l00861"></a><span class="lineno"> 861</span>  temp[id] = 0;</div>
<div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  value_type data;</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="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = begin; i < end; ++i)</div>
<div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  {</div>
<div class="line"><a name="l00866"></a><span class="lineno"> 866</span>  data = <span class="keyword">static_cast<</span>value_type<span class="keyword">></span>(std::fabs(static_cast<double>(data_vec1[i*inc1+start1]))); <span class="comment">//casting to double in order to avoid problems if T is an integer type</span></div>
<div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  <span class="keywordflow">if</span> (data > temp[<span class="keywordtype">id</span>])</div>
<div class="line"><a name="l00868"></a><span class="lineno"> 868</span>  {</div>
<div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  index[id] = i;</div>
<div class="line"><a name="l00870"></a><span class="lineno"> 870</span>  temp[id] = data;</div>
<div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  }</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>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 1; i < thread_count; ++i)</div>
<div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  {</div>
<div class="line"><a name="l00876"></a><span class="lineno"> 876</span>  <span class="keywordflow">if</span> (temp[i] > temp[0])</div>
<div class="line"><a name="l00877"></a><span class="lineno"> 877</span>  {</div>
<div class="line"><a name="l00878"></a><span class="lineno"> 878</span>  index[0] = index[i];</div>
<div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  temp[0] = temp[i];</div>
<div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  }</div>
<div class="line"><a name="l00881"></a><span class="lineno"> 881</span>  }</div>
<div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  <span class="keywordflow">return</span> index[0];</div>
<div class="line"><a name="l00883"></a><span class="lineno"> 883</span> }</div>
<div class="line"><a name="l00884"></a><span class="lineno"> 884</span> </div>
<div class="line"><a name="l00890"></a><span class="lineno"> 890</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> ScalarT></div>
<div class="line"><a name="l00891"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#ade2c77ef8044d4664c6857e96398304b"> 891</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ade2c77ef8044d4664c6857e96398304b">max_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  ScalarT & result)</div>
<div class="line"><a name="l00893"></a><span class="lineno"> 893</span> {</div>
<div class="line"><a name="l00894"></a><span class="lineno"> 894</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="l00895"></a><span class="lineno"> 895</span> </div>
<div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  value_type <span class="keyword">const</span> * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00897"></a><span class="lineno"> 897</span> </div>
<div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00899"></a><span class="lineno"> 899</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00900"></a><span class="lineno"> 900</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l00901"></a><span class="lineno"> 901</span> </div>
<div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> thread_count=1;</div>
<div class="line"><a name="l00903"></a><span class="lineno"> 903</span> </div>
<div class="line"><a name="l00904"></a><span class="lineno"> 904</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00905"></a><span class="lineno"> 905</span>  <span class="keywordflow">if</span>(size1 > <a class="code" href="host__based_2vector__operations_8hpp.html#aa1b0719a06924fc82f8d8ed6c739a04d">VIENNACL_OPENMP_VECTOR_MIN_SIZE</a>)</div>
<div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  thread_count = omp_get_max_threads();</div>
<div class="line"><a name="l00907"></a><span class="lineno"> 907</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00908"></a><span class="lineno"> 908</span> </div>
<div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  std::vector<value_type> temp(thread_count);</div>
<div class="line"><a name="l00910"></a><span class="lineno"> 910</span> </div>
<div class="line"><a name="l00911"></a><span class="lineno"> 911</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00912"></a><span class="lineno"> 912</span> <span class="preprocessor"> #pragma omp parallel if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00913"></a><span class="lineno"> 913</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  {</div>
<div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <span class="keywordtype">id</span> = 0;</div>
<div class="line"><a name="l00916"></a><span class="lineno"> 916</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  <span class="keywordtype">id</span> = omp_get_thread_num();</div>
<div class="line"><a name="l00918"></a><span class="lineno"> 918</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00919"></a><span class="lineno"> 919</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> begin = (size1 * id) / thread_count;</div>
<div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> end = (size1 * (<span class="keywordtype">id</span> + 1)) / thread_count;</div>
<div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  temp[id] = data_vec1[<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>];</div>
<div class="line"><a name="l00922"></a><span class="lineno"> 922</span> </div>
<div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = begin; i < end; ++i)</div>
<div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  {</div>
<div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  value_type v = data_vec1[i*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>];<span class="comment">//Note: Assignment to 'vec1' in std::min might be expensive, thus 'v' is used for the function</span></div>
<div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  temp[id] = std::max<value_type>(temp[id],v);</div>
<div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  }</div>
<div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  }</div>
<div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 1; i < thread_count; ++i)</div>
<div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  temp[0] = std::max<value_type>( temp[0], temp[i]);</div>
<div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  result = temp[0];<span class="comment">//Note: Assignment to result might be expensive, thus 'temp' is used for accumulation</span></div>
<div class="line"><a name="l00932"></a><span class="lineno"> 932</span> }</div>
<div class="line"><a name="l00933"></a><span class="lineno"> 933</span> </div>
<div class="line"><a name="l00939"></a><span class="lineno"> 939</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> ScalarT></div>
<div class="line"><a name="l00940"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#ac4670f3fd14af7a2caf44c4036536010"> 940</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ac4670f3fd14af7a2caf44c4036536010">min_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l00941"></a><span class="lineno"> 941</span>  ScalarT & result)</div>
<div class="line"><a name="l00942"></a><span class="lineno"> 942</span> {</div>
<div class="line"><a name="l00943"></a><span class="lineno"> 943</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="l00944"></a><span class="lineno"> 944</span> </div>
<div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  value_type <span class="keyword">const</span> * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00946"></a><span class="lineno"> 946</span> </div>
<div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00948"></a><span class="lineno"> 948</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00949"></a><span class="lineno"> 949</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l00950"></a><span class="lineno"> 950</span> </div>
<div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> thread_count=1;</div>
<div class="line"><a name="l00952"></a><span class="lineno"> 952</span> </div>
<div class="line"><a name="l00953"></a><span class="lineno"> 953</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  <span class="keywordflow">if</span>(size1 > <a class="code" href="host__based_2vector__operations_8hpp.html#aa1b0719a06924fc82f8d8ed6c739a04d">VIENNACL_OPENMP_VECTOR_MIN_SIZE</a>)</div>
<div class="line"><a name="l00955"></a><span class="lineno"> 955</span>  thread_count = omp_get_max_threads();</div>
<div class="line"><a name="l00956"></a><span class="lineno"> 956</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00957"></a><span class="lineno"> 957</span> </div>
<div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  std::vector<value_type> temp(thread_count);</div>
<div class="line"><a name="l00959"></a><span class="lineno"> 959</span> </div>
<div class="line"><a name="l00960"></a><span class="lineno"> 960</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00961"></a><span class="lineno"> 961</span> <span class="preprocessor"> #pragma omp parallel if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l00962"></a><span class="lineno"> 962</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00963"></a><span class="lineno"> 963</span>  {</div>
<div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <span class="keywordtype">id</span> = 0;</div>
<div class="line"><a name="l00965"></a><span class="lineno"> 965</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l00966"></a><span class="lineno"> 966</span>  <span class="keywordtype">id</span> = omp_get_thread_num();</div>
<div class="line"><a name="l00967"></a><span class="lineno"> 967</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00968"></a><span class="lineno"> 968</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> begin = (size1 * id) / thread_count;</div>
<div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> end = (size1 * (<span class="keywordtype">id</span> + 1)) / thread_count;</div>
<div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  temp[id] = data_vec1[<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>];</div>
<div class="line"><a name="l00971"></a><span class="lineno"> 971</span> </div>
<div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = begin; i < end; ++i)</div>
<div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  {</div>
<div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  value_type v = data_vec1[i*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>];<span class="comment">//Note: Assignment to 'vec1' in std::min might be expensive, thus 'v' is used for the function</span></div>
<div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  temp[id] = std::min<value_type>(temp[id],v);</div>
<div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  }</div>
<div class="line"><a name="l00977"></a><span class="lineno"> 977</span>  }</div>
<div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 1; i < thread_count; ++i)</div>
<div class="line"><a name="l00979"></a><span class="lineno"> 979</span>  temp[0] = std::min<value_type>( temp[0], temp[i]);</div>
<div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  result = temp[0];<span class="comment">//Note: Assignment to result might be expensive, thus 'temp' is used for accumulation</span></div>
<div class="line"><a name="l00981"></a><span class="lineno"> 981</span> }</div>
<div class="line"><a name="l00982"></a><span class="lineno"> 982</span> </div>
<div class="line"><a name="l00988"></a><span class="lineno"> 988</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keyword">typename</span> ScalarT></div>
<div class="line"><a name="l00989"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#ae2bfa1890191051eeca95db258511533"> 989</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ae2bfa1890191051eeca95db258511533">sum_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  ScalarT & result)</div>
<div class="line"><a name="l00991"></a><span class="lineno"> 991</span> {</div>
<div class="line"><a name="l00992"></a><span class="lineno"> 992</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="l00993"></a><span class="lineno"> 993</span> </div>
<div class="line"><a name="l00994"></a><span class="lineno"> 994</span>  value_type <span class="keyword">const</span> * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l00995"></a><span class="lineno"> 995</span> </div>
<div class="line"><a name="l00996"></a><span class="lineno"> 996</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l00999"></a><span class="lineno"> 999</span> </div>
<div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>  value_type temp = 0;</div>
<div class="line"><a name="l01001"></a><span class="lineno"> 1001</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l01002"></a><span class="lineno"> 1002</span> <span class="preprocessor"> #pragma omp parallel for reduction(+:temp) if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l01003"></a><span class="lineno"> 1003</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01004"></a><span class="lineno"> 1004</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>  temp += data_vec1[static_cast<vcl_size_t>(i)*inc1+<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>];</div>
<div class="line"><a name="l01006"></a><span class="lineno"> 1006</span> </div>
<div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  result = temp; <span class="comment">//Note: Assignment to result might be expensive, thus 'temp' is used for accumulation</span></div>
<div class="line"><a name="l01008"></a><span class="lineno"> 1008</span> }</div>
<div class="line"><a name="l01009"></a><span class="lineno"> 1009</span> </div>
<div class="line"><a name="l01019"></a><span class="lineno"> 1019</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l01020"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a7038bea435ceada730575e20bbcd56a6"> 1020</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a7038bea435ceada730575e20bbcd56a6">plane_rotation</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec1,</div>
<div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec2,</div>
<div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> alpha, <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> beta)</div>
<div class="line"><a name="l01023"></a><span class="lineno"> 1023</span> {</div>
<div class="line"><a name="l01024"></a><span class="lineno"> 1024</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="l01025"></a><span class="lineno"> 1025</span> </div>
<div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>  value_type * data_vec1 = detail::extract_raw_pointer<value_type>(vec1);</div>
<div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>  value_type * data_vec2 = detail::extract_raw_pointer<value_type>(vec2);</div>
<div class="line"><a name="l01028"></a><span class="lineno"> 1028</span> </div>
<div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l01032"></a><span class="lineno"> 1032</span> </div>
<div class="line"><a name="l01033"></a><span class="lineno"> 1033</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2);</div>
<div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc2 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2);</div>
<div class="line"><a name="l01035"></a><span class="lineno"> 1035</span> </div>
<div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>  value_type data_alpha = alpha;</div>
<div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>  value_type data_beta = beta;</div>
<div class="line"><a name="l01038"></a><span class="lineno"> 1038</span> </div>
<div class="line"><a name="l01039"></a><span class="lineno"> 1039</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l01040"></a><span class="lineno"> 1040</span> <span class="preprocessor"> #pragma omp parallel for if (size1 > VIENNACL_OPENMP_VECTOR_MIN_SIZE)</span></div>
<div class="line"><a name="l01041"></a><span class="lineno"> 1041</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01042"></a><span class="lineno"> 1042</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#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>); ++i)</div>
<div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>  {</div>
<div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>  value_type temp1 = data_vec1[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc1+start1];</div>
<div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>  value_type temp2 = data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2];</div>
<div class="line"><a name="l01046"></a><span class="lineno"> 1046</span> </div>
<div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  data_vec1[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc1+start1] = data_alpha * temp1 + data_beta * temp2;</div>
<div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>  data_vec2[<span class="keyword">static_cast<</span><a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a><span class="keyword">></span>(i)*inc2+start2] = data_alpha * temp2 - data_beta * temp1;</div>
<div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>  }</div>
<div class="line"><a name="l01050"></a><span class="lineno"> 1050</span> }</div>
<div class="line"><a name="l01051"></a><span class="lineno"> 1051</span> </div>
<div class="line"><a name="l01052"></a><span class="lineno"> 1052</span> <span class="keyword">namespace </span>detail</div>
<div class="line"><a name="l01053"></a><span class="lineno"> 1053</span> {</div>
<div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>  <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l01056"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a90e2cace173fdf7396eae21660fdbc22"> 1056</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a90e2cace173fdf7396eae21660fdbc22">vector_scan_impl</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec2,</div>
<div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>  <span class="keywordtype">bool</span> is_inclusive)</div>
<div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>  {</div>
<div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * data_vec1 = detail::extract_raw_pointer<NumericT>(vec1);</div>
<div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * data_vec2 = detail::extract_raw_pointer<NumericT>(vec2);</div>
<div class="line"><a name="l01062"></a><span class="lineno"> 1062</span> </div>
<div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec1);</div>
<div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc1 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec1);</div>
<div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a> = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a>(vec1);</div>
<div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>  <span class="keywordflow">if</span> (size1 < 1)</div>
<div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>  <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l01068"></a><span class="lineno"> 1068</span> </div>
<div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a> = <a class="code" href="namespaceviennacl_1_1traits.html#a68603a1e1ca1bfb6d107831ba5096786">viennacl::traits::start</a>(vec2);</div>
<div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> inc2 = <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a>(vec2);</div>
<div class="line"><a name="l01071"></a><span class="lineno"> 1071</span> </div>
<div class="line"><a name="l01072"></a><span class="lineno"> 1072</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENMP</span></div>
<div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>  <span class="keywordflow">if</span> (size1 > <a class="code" href="host__based_2vector__operations_8hpp.html#aa1b0719a06924fc82f8d8ed6c739a04d">VIENNACL_OPENMP_VECTOR_MIN_SIZE</a>)</div>
<div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>  {</div>
<div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>  std::vector<NumericT> thread_results(omp_get_max_threads());</div>
<div class="line"><a name="l01076"></a><span class="lineno"> 1076</span> </div>
<div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>  <span class="comment">// inclusive scan each thread segment:</span></div>
<div class="line"><a name="l01078"></a><span class="lineno"> 1078</span> <span class="preprocessor"> #pragma omp parallel</span></div>
<div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>  {</div>
<div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_per_thread = (size1 - 1) / thread_results.size() + 1;</div>
<div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> thread_start = work_per_thread * omp_get_thread_num();</div>
<div class="line"><a name="l01082"></a><span class="lineno"> 1082</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> thread_stop = std::min<vcl_size_t>(thread_start + work_per_thread, <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>);</div>
<div class="line"><a name="l01083"></a><span class="lineno"> 1083</span> </div>
<div class="line"><a name="l01084"></a><span class="lineno"> 1084</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> thread_sum = 0;</div>
<div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>  <span class="keywordflow">for</span>(<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = thread_start; i < thread_stop; i++)</div>
<div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>  thread_sum += data_vec1[i * inc1 + start1];</div>
<div class="line"><a name="l01087"></a><span class="lineno"> 1087</span> </div>
<div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>  thread_results[omp_get_thread_num()] = thread_sum;</div>
<div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>  }</div>
<div class="line"><a name="l01090"></a><span class="lineno"> 1090</span> </div>
<div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>  <span class="comment">// exclusive-scan of thread results:</span></div>
<div class="line"><a name="l01092"></a><span class="lineno"> 1092</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> current_offset = 0;</div>
<div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i=0; i<thread_results.size(); ++i)</div>
<div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>  {</div>
<div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> tmp = thread_results[i];</div>
<div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>  thread_results[i] = current_offset;</div>
<div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>  current_offset += tmp;</div>
<div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>  }</div>
<div class="line"><a name="l01099"></a><span class="lineno"> 1099</span> </div>
<div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>  <span class="comment">// exclusive/inclusive scan of each segment with correct offset:</span></div>
<div class="line"><a name="l01101"></a><span class="lineno"> 1101</span> <span class="preprocessor"> #pragma omp parallel</span></div>
<div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>  {</div>
<div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> work_per_thread = (size1 - 1) / thread_results.size() + 1;</div>
<div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> thread_start = work_per_thread * omp_get_thread_num();</div>
<div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> thread_stop = std::min<vcl_size_t>(thread_start + work_per_thread, <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>);</div>
<div class="line"><a name="l01106"></a><span class="lineno"> 1106</span> </div>
<div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> thread_sum = thread_results[omp_get_thread_num()];</div>
<div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>  <span class="keywordflow">if</span> (is_inclusive)</div>
<div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>  {</div>
<div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>  <span class="keywordflow">for</span>(<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = thread_start; i < thread_stop; i++)</div>
<div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>  {</div>
<div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>  thread_sum += data_vec1[i * inc1 + <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>];</div>
<div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>  data_vec2[i * inc2 + <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a>] = thread_sum;</div>
<div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>  }</div>
<div class="line"><a name="l01115"></a><span class="lineno"> 1115</span>  }</div>
<div class="line"><a name="l01116"></a><span class="lineno"> 1116</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>  {</div>
<div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>  <span class="keywordflow">for</span>(<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = thread_start; i < thread_stop; i++)</div>
<div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>  {</div>
<div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> tmp = data_vec1[i * inc1 + <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>];</div>
<div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>  data_vec2[i * inc2 + <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a>] = thread_sum;</div>
<div class="line"><a name="l01122"></a><span class="lineno"> 1122</span>  thread_sum += tmp;</div>
<div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>  }</div>
<div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>  }</div>
<div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>  }</div>
<div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>  } <span class="keywordflow">else</span></div>
<div class="line"><a name="l01127"></a><span class="lineno"> 1127</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>  {</div>
<div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a> = 0;</div>
<div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>  <span class="keywordflow">if</span> (is_inclusive)</div>
<div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>  {</div>
<div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>  <span class="keywordflow">for</span>(<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 0; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>; i++)</div>
<div class="line"><a name="l01133"></a><span class="lineno"> 1133</span>  {</div>
<div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>  sum += data_vec1[i * inc1 + <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>];</div>
<div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>  data_vec2[i * inc2 + <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a>] = <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a>;</div>
<div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>  }</div>
<div class="line"><a name="l01137"></a><span class="lineno"> 1137</span>  }</div>
<div class="line"><a name="l01138"></a><span class="lineno"> 1138</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l01139"></a><span class="lineno"> 1139</span>  {</div>
<div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>  <span class="keywordflow">for</span>(<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 0; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>; i++)</div>
<div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>  {</div>
<div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> tmp = data_vec1[i * inc1 + <a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">start1</a>];</div>
<div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>  data_vec2[i * inc2 + <a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">start2</a>] = <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a>;</div>
<div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>  sum += tmp;</div>
<div class="line"><a name="l01145"></a><span class="lineno"> 1145</span>  }</div>
<div class="line"><a name="l01146"></a><span class="lineno"> 1146</span>  }</div>
<div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>  }</div>
<div class="line"><a name="l01148"></a><span class="lineno"> 1148</span> </div>
<div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>  }</div>
<div class="line"><a name="l01150"></a><span class="lineno"> 1150</span> }</div>
<div class="line"><a name="l01151"></a><span class="lineno"> 1151</span> </div>
<div class="line"><a name="l01160"></a><span class="lineno"> 1160</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l01161"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#ace2ac2eae0198df73a1960c45cbbb7c7"> 1161</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#ace2ac2eae0198df73a1960c45cbbb7c7">inclusive_scan</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec2)</div>
<div class="line"><a name="l01163"></a><span class="lineno"> 1163</span> {</div>
<div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a90e2cace173fdf7396eae21660fdbc22">detail::vector_scan_impl</a>(vec1, vec2, <span class="keyword">true</span>);</div>
<div class="line"><a name="l01165"></a><span class="lineno"> 1165</span> }</div>
<div class="line"><a name="l01166"></a><span class="lineno"> 1166</span> </div>
<div class="line"><a name="l01175"></a><span class="lineno"> 1175</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l01176"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1host__based.html#a43942d99b5d1ce74238e073aac275eb7"> 1176</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based.html#a43942d99b5d1ce74238e073aac275eb7">exclusive_scan</a>(<a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> <span class="keyword">const</span> & vec1,</div>
<div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>  <a class="code" href="classviennacl_1_1vector__base.html">vector_base<NumericT></a> & vec2)</div>
<div class="line"><a name="l01178"></a><span class="lineno"> 1178</span> {</div>
<div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a90e2cace173fdf7396eae21660fdbc22">detail::vector_scan_impl</a>(vec1, vec2, <span class="keyword">false</span>);</div>
<div class="line"><a name="l01180"></a><span class="lineno"> 1180</span> }</div>
<div class="line"><a name="l01181"></a><span class="lineno"> 1181</span> </div>
<div class="line"><a name="l01182"></a><span class="lineno"> 1182</span> </div>
<div class="line"><a name="l01183"></a><span class="lineno"> 1183</span> } <span class="comment">//namespace host_based</span></div>
<div class="line"><a name="l01184"></a><span class="lineno"> 1184</span> } <span class="comment">//namespace linalg</span></div>
<div class="line"><a name="l01185"></a><span class="lineno"> 1185</span> } <span class="comment">//namespace viennacl</span></div>
<div class="line"><a name="l01186"></a><span class="lineno"> 1186</span> </div>
<div class="line"><a name="l01187"></a><span class="lineno"> 1187</span> </div>
<div class="line"><a name="l01188"></a><span class="lineno"> 1188</span> <span class="preprocessor">#endif</span></div>
<div class="ttc" id="classviennacl_1_1vector__tuple_html_a9f2fc8200f0199e396eaeca310f8e9f4"><div class="ttname"><a href="classviennacl_1_1vector__tuple.html#a9f2fc8200f0199e396eaeca310f8e9f4">viennacl::vector_tuple::const_size</a></div><div class="ttdeci">vcl_size_t const_size() const </div><div class="ttdef"><b>Definition:</b> <a href="vector_8hpp_source.html#l01143">vector.hpp:1143</a></div></div>
<div class="ttc" id="host__based_2vector__operations_8hpp_html_a71fb7fd5be61a0297a8d19220cff479b"><div class="ttname"><a href="host__based_2vector__operations_8hpp.html#a71fb7fd5be61a0297a8d19220cff479b">VIENNACL_INNER_PROD_IMPL_2</a></div><div class="ttdeci">#define VIENNACL_INNER_PROD_IMPL_2(RESULTSCALART)</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00410">vector_operations.hpp:410</a></div></div>
<div class="ttc" id="host__based_2vector__operations_8hpp_html_af7aa8317885702b7e1295d9eb802fba5"><div class="ttname"><a href="host__based_2vector__operations_8hpp.html#af7aa8317885702b7e1295d9eb802fba5">VIENNACL_NORM_1_IMPL_2</a></div><div class="ttdeci">#define VIENNACL_NORM_1_IMPL_2(RESULTSCALART, TEMPSCALART)</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00562">vector_operations.hpp:562</a></div></div>
<div class="ttc" id="host__based_2vector__operations_8hpp_html_a2fff34b2cb787d5c2ae89f59a93cfde8"><div class="ttname"><a href="host__based_2vector__operations_8hpp.html#a2fff34b2cb787d5c2ae89f59a93cfde8">VIENNACL_NORM_2_IMPL_2</a></div><div class="ttdeci">#define VIENNACL_NORM_2_IMPL_2(RESULTSCALART, TEMPSCALART)</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00671">vector_operations.hpp:671</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_a430b9424a974bdacda10b5a323976c0a"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#a430b9424a974bdacda10b5a323976c0a">viennacl::linalg::opencl::norm_2_impl</a></div><div class="ttdeci">void norm_2_impl(vector_base< T > const &vec, scalar< T > &result)</div><div class="ttdoc">Computes the l^2-norm of a vector - implementation using OpenCL summation at second step...</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2vector__operations_8hpp_source.html#l00801">vector_operations.hpp:801</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_ace2ac2eae0198df73a1960c45cbbb7c7"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#ace2ac2eae0198df73a1960c45cbbb7c7">viennacl::linalg::host_based::inclusive_scan</a></div><div class="ttdeci">void inclusive_scan(vector_base< NumericT > const &vec1, vector_base< NumericT > &vec2)</div><div class="ttdoc">This function implements an inclusive scan on the host using OpenMP. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l01161">vector_operations.hpp:1161</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="namespaceviennacl_1_1linalg_1_1host__based_html_ad21ec9fa116f8f1bd34d426c058c504b"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#ad21ec9fa116f8f1bd34d426c058c504b">viennacl::linalg::host_based::norm_1_impl</a></div><div class="ttdeci">void norm_1_impl(vector_base< NumericT > const &vec1, ScalarT &result)</div><div class="ttdoc">Computes the l^1-norm of a vector. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00648">vector_operations.hpp:648</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="namespaceviennacl_1_1linalg_1_1host__based_html_a64a65b7cd5c499e1a2e12ae921ec1ca2"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#a64a65b7cd5c499e1a2e12ae921ec1ca2">viennacl::linalg::host_based::norm_inf_impl</a></div><div class="ttdeci">void norm_inf_impl(vector_base< NumericT > const &vec1, ScalarT &result)</div><div class="ttdoc">Computes the supremum-norm of a vector. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00781">vector_operations.hpp:781</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_a47e4fa3cd849b7beab25f195633a38ad"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#a47e4fa3cd849b7beab25f195633a38ad">viennacl::linalg::host_based::av</a></div><div class="ttdeci">void av(vector_base< NumericT > &vec1, vector_base< NumericT > const &vec2, ScalarT1 const &alpha, vcl_size_t, bool reciprocal_alpha, bool flip_sign_alpha)</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00088">vector_operations.hpp:88</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_ae2bfa1890191051eeca95db258511533"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#ae2bfa1890191051eeca95db258511533">viennacl::linalg::host_based::sum_impl</a></div><div class="ttdeci">void sum_impl(vector_base< NumericT > const &vec1, ScalarT &result)</div><div class="ttdoc">Computes the sum of all elements from the vector. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00989">vector_operations.hpp:989</a></div></div>
<div class="ttc" id="host__based_2vector__operations_8hpp_html_a5ac8ca975475c4350eba91cc3d97ae81"><div class="ttname"><a href="host__based_2vector__operations_8hpp.html#a5ac8ca975475c4350eba91cc3d97ae81">VIENNACL_NORM_1_IMPL_1</a></div><div class="ttdeci">#define VIENNACL_NORM_1_IMPL_1(RESULTSCALART, TEMPSCALART)</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00558">vector_operations.hpp:558</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="namespaceviennacl_1_1traits_html_aa756f5d6820722094cae0d8b9bb6d5e2"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">viennacl::traits::size1</a></div><div class="ttdeci">vcl_size_t size1(MatrixType const &mat)</div><div class="ttdoc">Generic routine for obtaining the number of rows of a matrix (ViennaCL, uBLAS, etc.) </div><div class="ttdef"><b>Definition:</b> <a href="size_8hpp_source.html#l00163">size.hpp:163</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1detail_1_1op__applier_html"><div class="ttname"><a href="structviennacl_1_1linalg_1_1detail_1_1op__applier.html">viennacl::linalg::detail::op_applier</a></div><div class="ttdoc">Worker class for decomposing expression templates. </div><div class="ttdef"><b>Definition:</b> <a href="op__applier_8hpp_source.html#l00043">op_applier.hpp:43</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_a09997870f4802fa5d4ac2c43cf4020d1"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a></div><div class="ttdeci">result_of::size_type< viennacl::vector_base< T > >::type stride(viennacl::vector_base< T > const &s)</div><div class="ttdef"><b>Definition:</b> <a href="stride_8hpp_source.html#l00045">stride.hpp:45</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="namespaceviennacl_1_1traits_html_ae601425decc5f1a8763ab5272e9e492f"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">viennacl::traits::start1</a></div><div class="ttdeci">result_of::size_type< T >::type start1(T const &obj)</div><div class="ttdef"><b>Definition:</b> <a href="start_8hpp_source.html#l00065">start.hpp:65</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="classviennacl_1_1vector__expression_html"><div class="ttname"><a href="classviennacl_1_1vector__expression.html">viennacl::vector_expression</a></div><div class="ttdoc">An expression template class that represents a binary operation that yields a vector. </div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00239">forwards.h:239</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_a38954effaaf57109159e51a31293a6c1"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#a38954effaaf57109159e51a31293a6c1">viennacl::linalg::host_based::vector_assign</a></div><div class="ttdeci">void vector_assign(vector_base< NumericT > &vec1, const NumericT &alpha, bool up_to_internal_size=false)</div><div class="ttdoc">Assign a constant value to a vector (-range/-slice) </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00275">vector_operations.hpp:275</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_a4fe3f1e7af78cbeb1125758a635eb99d"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#a4fe3f1e7af78cbeb1125758a635eb99d">viennacl::linalg::host_based::convert</a></div><div class="ttdeci">void convert(matrix_base< DestNumericT > &mat1, matrix_base< SrcNumericT > const &mat2)</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2matrix__operations_8hpp_source.html#l00058">matrix_operations.hpp:58</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="namespaceviennacl_1_1traits_html_ac53fc8cc9836953dc87aaaaa56f382c2"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">viennacl::traits::start2</a></div><div class="ttdeci">result_of::size_type< T >::type start2(T const &obj)</div><div class="ttdef"><b>Definition:</b> <a href="start_8hpp_source.html#l00084">start.hpp:84</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_a84f017afe97029f92d48c968774f245b"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#a84f017afe97029f92d48c968774f245b">viennacl::linalg::host_based::norm_2_impl</a></div><div class="ttdeci">void norm_2_impl(vector_base< NumericT > const &vec1, ScalarT &result)</div><div class="ttdoc">Computes the l^2-norm of a vector - implementation. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00761">vector_operations.hpp:761</a></div></div>
<div class="ttc" id="host__based_2vector__operations_8hpp_html_aaf35aadcae50e5e59946aa92b7f22aa2"><div class="ttname"><a href="host__based_2vector__operations_8hpp.html#aaf35aadcae50e5e59946aa92b7f22aa2">VIENNACL_INNER_PROD_IMPL_1</a></div><div class="ttdeci">#define VIENNACL_INNER_PROD_IMPL_1(RESULTSCALART, TEMPSCALART)</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00405">vector_operations.hpp:405</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_aa9936ab7a49e99f2935f7dc33b95c976"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#aa9936ab7a49e99f2935f7dc33b95c976">viennacl::linalg::host_based::index_norm_inf</a></div><div class="ttdeci">vcl_size_t index_norm_inf(vector_base< NumericT > const &vec1)</div><div class="ttdoc">Computes the index of the first entry that is equal to the supremum-norm in modulus. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00831">vector_operations.hpp:831</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__tuple_html"><div class="ttname"><a href="classviennacl_1_1vector__tuple.html">viennacl::vector_tuple</a></div><div class="ttdoc">Tuple class holding pointers to multiple vectors. Mainly used as a temporary object returned from vie...</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00269">forwards.h:269</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_ac4670f3fd14af7a2caf44c4036536010"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#ac4670f3fd14af7a2caf44c4036536010">viennacl::linalg::host_based::min_impl</a></div><div class="ttdeci">void min_impl(vector_base< NumericT > const &vec1, ScalarT &result)</div><div class="ttdoc">Computes the minimum of a vector. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00940">vector_operations.hpp:940</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_ac765726382000520401dc9d70483dabb"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#ac765726382000520401dc9d70483dabb">viennacl::linalg::host_based::vector_swap</a></div><div class="ttdeci">void vector_swap(vector_base< NumericT > &vec1, vector_base< NumericT > &vec2)</div><div class="ttdoc">Swaps the contents of two vectors, data is copied. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00302">vector_operations.hpp:302</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_ae02ec8df2561e6d99747334dc2e5cec8"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#ae02ec8df2561e6d99747334dc2e5cec8">viennacl::linalg::host_based::element_op</a></div><div class="ttdeci">void element_op(matrix_base< NumericT > &A, matrix_expression< const matrix_base< NumericT >, const matrix_base< NumericT >, op_element_binary< OpT > > const &proxy)</div><div class="ttdoc">Implementation of the element-wise operations A = B .* C and A = B ./ C (using MATLAB syntax) ...</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2matrix__operations_8hpp_source.html#l00848">matrix_operations.hpp:848</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="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_html_abd382e4bde97fb842b7b52b2b4d36379"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#abd382e4bde97fb842b7b52b2b4d36379">viennacl::linalg::host_based::detail::flip_sign</a></div><div class="ttdeci">NumericT flip_sign(NumericT val)</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00057">vector_operations.hpp:57</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_a7634739b4c75267d38297dfcb19fad63"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#a7634739b4c75267d38297dfcb19fad63">viennacl::linalg::host_based::avbv</a></div><div class="ttdeci">void avbv(vector_base< NumericT > &vec1, vector_base< NumericT > const &vec2, ScalarT1 const &alpha, vcl_size_t, bool reciprocal_alpha, bool flip_sign_alpha, vector_base< NumericT > const &vec3, ScalarT2 const &beta, vcl_size_t, bool reciprocal_beta, bool flip_sign_beta)</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00127">vector_operations.hpp:127</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</a></div><div class="ttdoc">Common base class for dense vectors, vector ranges, and vector slices. </div><div class="ttdef"><b>Definition:</b> <a href="vector__def_8hpp_source.html#l00104">vector_def.hpp:104</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="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_1_1linalg_1_1host__based_html_a43942d99b5d1ce74238e073aac275eb7"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#a43942d99b5d1ce74238e073aac275eb7">viennacl::linalg::host_based::exclusive_scan</a></div><div class="ttdeci">void exclusive_scan(vector_base< NumericT > const &vec1, vector_base< NumericT > &vec2)</div><div class="ttdoc">This function implements an exclusive scan on the host using OpenMP. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l01176">vector_operations.hpp:1176</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="namespaceviennacl_1_1linalg_1_1host__based_html_ad78c38a7e4a3ae75bc2e149b28854eaa"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#ad78c38a7e4a3ae75bc2e149b28854eaa">viennacl::linalg::host_based::inner_prod_impl</a></div><div class="ttdeci">void inner_prod_impl(vector_base< NumericT > const &vec1, vector_base< NumericT > const &vec2, ScalarT &result)</div><div class="ttdoc">Computes the inner product of two vectors - implementation. Library users should call inner_prod(vec1...</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00497">vector_operations.hpp:497</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_html_a90e2cace173fdf7396eae21660fdbc22"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail.html#a90e2cace173fdf7396eae21660fdbc22">viennacl::linalg::host_based::detail::vector_scan_impl</a></div><div class="ttdeci">void vector_scan_impl(vector_base< NumericT > const &vec1, vector_base< NumericT > &vec2, bool is_inclusive)</div><div class="ttdoc">Implementation of inclusive_scan and exclusive_scan for the host (OpenMP) backend. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l01056">vector_operations.hpp:1056</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_ade2c77ef8044d4664c6857e96398304b"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#ade2c77ef8044d4664c6857e96398304b">viennacl::linalg::host_based::max_impl</a></div><div class="ttdeci">void max_impl(vector_base< NumericT > const &vec1, ScalarT &result)</div><div class="ttdoc">Computes the maximum of a vector. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00891">vector_operations.hpp:891</a></div></div>
<div class="ttc" id="host__based_2vector__operations_8hpp_html_af97743e472ad389e0ad82849002fd0af"><div class="ttname"><a href="host__based_2vector__operations_8hpp.html#af97743e472ad389e0ad82849002fd0af">VIENNACL_NORM_2_IMPL_1</a></div><div class="ttdeci">#define VIENNACL_NORM_2_IMPL_1(RESULTSCALART, TEMPSCALART)</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00667">vector_operations.hpp:667</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__tuple_html_a9e4b9367232f8937dfaddeaeca64e0e0"><div class="ttname"><a href="classviennacl_1_1vector__tuple.html#a9e4b9367232f8937dfaddeaeca64e0e0">viennacl::vector_tuple::const_at</a></div><div class="ttdeci">VectorType const & const_at(vcl_size_t i) const </div><div class="ttdef"><b>Definition:</b> <a href="vector_8hpp_source.html#l01146">vector.hpp:1146</a></div></div>
<div class="ttc" id="structviennacl_1_1op__element__binary_html"><div class="ttname"><a href="structviennacl_1_1op__element__binary.html">viennacl::op_element_binary</a></div><div class="ttdoc">A tag class representing element-wise binary operations (like multiplication) on vectors or matrices...</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00130">forwards.h:130</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html_a47350ccdc4b0a24eaea0e8d5f9fe7fec"><div class="ttname"><a href="classviennacl_1_1vector__base.html#a47350ccdc4b0a24eaea0e8d5f9fe7fec">viennacl::vector_base::internal_size</a></div><div class="ttdeci">size_type internal_size() const </div><div class="ttdoc">Returns the internal length of the vector, which is given by size() plus the extra memory due to padd...</div><div class="ttdef"><b>Definition:</b> <a href="vector__def_8hpp_source.html#l00120">vector_def.hpp:120</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="structviennacl_1_1op__element__unary_html"><div class="ttname"><a href="structviennacl_1_1op__element__unary.html">viennacl::op_element_unary</a></div><div class="ttdoc">A tag class representing element-wise unary operations (like sin()) on vectors or matrices...</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00134">forwards.h:134</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_html_a7038bea435ceada730575e20bbcd56a6"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#a7038bea435ceada730575e20bbcd56a6">viennacl::linalg::host_based::plane_rotation</a></div><div class="ttdeci">void plane_rotation(vector_base< NumericT > &vec1, vector_base< NumericT > &vec2, NumericT alpha, NumericT beta)</div><div class="ttdoc">Computes a plane rotation of two vectors. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l01020">vector_operations.hpp:1020</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_af170246b8ee051270ea2c9fbd141d832"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#af170246b8ee051270ea2c9fbd141d832">viennacl::linalg::inner_prod_impl</a></div><div class="ttdeci">void inner_prod_impl(vector_base< T > const &x, vector_tuple< T > const &y_tuple, vector_base< T > &result)</div><div class="ttdoc">Computes the inner products <x, y1>, <x, y2>, ..., <x, y_N> and writes the result to a (sub-)vector...</div><div class="ttdef"><b>Definition:</b> <a href="vector__operations_8hpp_source.html#l00530">vector_operations.hpp:530</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="namespaceviennacl_1_1linalg_1_1host__based_html_a9e173eb4a7b8b63e7bddb53074d764ec"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based.html#a9e173eb4a7b8b63e7bddb53074d764ec">viennacl::linalg::host_based::avbv_v</a></div><div class="ttdeci">void avbv_v(vector_base< NumericT > &vec1, vector_base< NumericT > const &vec2, ScalarT1 const &alpha, vcl_size_t, bool reciprocal_alpha, bool flip_sign_alpha, vector_base< NumericT > const &vec3, ScalarT2 const &beta, vcl_size_t, bool reciprocal_beta, bool flip_sign_beta)</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00197">vector_operations.hpp:197</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a94c58051a4819c96e29cd360e784c68f"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a94c58051a4819c96e29cd360e784c68f">viennacl::linalg::norm_1_impl</a></div><div class="ttdeci">void norm_1_impl(viennacl::vector_expression< LHS, RHS, OP > const &vec, S2 &result)</div><div class="ttdoc">Computes the l^1-norm of a vector - interface for a vector expression. Creates a temporary. </div><div class="ttdef"><b>Definition:</b> <a href="vector__operations_8hpp_source.html#l00598">vector_operations.hpp:598</a></div></div>
<div class="ttc" id="host__based_2vector__operations_8hpp_html_aa1b0719a06924fc82f8d8ed6c739a04d"><div class="ttname"><a href="host__based_2vector__operations_8hpp.html#aa1b0719a06924fc82f8d8ed6c739a04d">VIENNACL_OPENMP_VECTOR_MIN_SIZE</a></div><div class="ttdeci">#define VIENNACL_OPENMP_VECTOR_MIN_SIZE</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2vector__operations_8hpp_source.html#l00045">vector_operations.hpp:45</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>
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