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<div class="title">dense_blas.cpp</div> </div>
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<a href="dense__blas_8cpp.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="comment">/* =========================================================================</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> Copyright (c) 2010-2016, Institute for Microelectronics,</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> Institute for Analysis and Scientific Computing,</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> TU Wien.</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> Portions of this software are copyright by UChicago Argonne, LLC.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"></span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> -----------------</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> ViennaCL - The Vienna Computing Library</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"> Project Head: Karl Rupp rupp@iue.tuwien.ac.at</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"> (A list of authors and contributors can be found in the PDF manual)</span></div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"></span></div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> License: MIT (X11), see file LICENSE in the base directory</span></div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment">============================================================================= */</span></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include "<a class="code" href="matrix_8hpp.html">viennacl/matrix.hpp</a>"</span></div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include "<a class="code" href="matrix__proxy_8hpp.html">viennacl/matrix_proxy.hpp</a>"</span></div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include "<a class="code" href="vector_8hpp.html">viennacl/vector.hpp</a>"</span></div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include "<a class="code" href="vector__proxy_8hpp.html">viennacl/vector_proxy.hpp</a>"</span></div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="preprocessor">#include "<a class="code" href="inner__prod_8hpp.html">viennacl/linalg/inner_prod.hpp</a>"</span></div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include "<a class="code" href="prod_8hpp.html">viennacl/linalg/prod.hpp</a>"</span></div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include "<a class="code" href="lu_8hpp.html">viennacl/linalg/lu.hpp</a>"</span></div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include "<a class="code" href="timer_8hpp.html">viennacl/tools/timer.hpp</a>"</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 <iomanip></span></div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include <stdlib.h></span></div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="keyword">template</span><<span class="keyword">class</span> T, <span class="keyword">class</span> F></div>
<div class="line"><a name="l00032"></a><span class="lineno"><a class="line" href="dense__blas_8cpp.html#a394a1b0572531e380bc94ec20cd7a20c"> 32</a></span> <span class="keywordtype">void</span> <a class="code" href="dense__blas_8cpp.html#a394a1b0572531e380bc94ec20cd7a20c">init_random</a>(<a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<T, F></a> & M)</div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> {</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  std::vector<T> cM(M.<a class="code" href="classviennacl_1_1matrix__base.html#a7f1b176eaa22875c3dc04750498616a1">internal_size</a>());</div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keywordflow">for</span> (std::size_t i = 0; i < M.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>(); ++i)</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keywordflow">for</span> (std::size_t j = 0; j < M.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>(); ++j)</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  cM[F::mem_index(i, j, M.<a class="code" href="classviennacl_1_1matrix__base.html#a82018b4e169973bdfb9d3be68ceb5be0">internal_size1</a>(), M.<a class="code" href="classviennacl_1_1matrix__base.html#a00e30fdc61081a73995b54175a91d220">internal_size2</a>())] = T(rand())/T(RAND_MAX);</div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <a class="code" href="namespaceviennacl.html#aaa5c8726b45bc89a523ca2fa8c42107a">viennacl::fast_copy</a>(&cM[0],&cM[0] + cM.size(),M);</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> }</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="keyword">template</span><<span class="keyword">class</span> T></div>
<div class="line"><a name="l00042"></a><span class="lineno"><a class="line" href="dense__blas_8cpp.html#a7044d46a24870e1508e14dc2b6c3c104"> 42</a></span> <span class="keywordtype">void</span> <a class="code" href="dense__blas_8cpp.html#a394a1b0572531e380bc94ec20cd7a20c">init_random</a>(<a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> & x)</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span> {</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  std::vector<T> cx(x.<a class="code" href="classviennacl_1_1vector__base.html#a47350ccdc4b0a24eaea0e8d5f9fe7fec">internal_size</a>());</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordflow">for</span> (std::size_t i = 0; i < cx.size(); ++i)</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  cx[i] = T(rand())/T(RAND_MAX);</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <a class="code" href="namespaceviennacl.html#aaa5c8726b45bc89a523ca2fa8c42107a">viennacl::fast_copy</a>(&cx[0], &cx[0] + cx.size(), x.<a class="code" href="classviennacl_1_1vector__base.html#a762d98e2f912fc534951f25555b6077f">begin</a>());</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span> }</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="keyword">template</span><<span class="keyword">class</span> T></div>
<div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="dense__blas_8cpp.html#af6bb6f04705830fb7e059fe0572778d6"> 51</a></span> <span class="keywordtype">void</span> <a class="code" href="dense__blas_8cpp.html#af6bb6f04705830fb7e059fe0572778d6">bench</a>(<span class="keywordtype">size_t</span> BLAS1_N, <span class="keywordtype">size_t</span> BLAS2_M, <span class="keywordtype">size_t</span> BLAS2_N, <span class="keywordtype">size_t</span> BLAS3_M, <span class="keywordtype">size_t</span> BLAS3_N, <span class="keywordtype">size_t</span> BLAS3_K, std::string <span class="keyword">const</span> & prefix)</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> {</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">using</span> <a class="code" href="namespaceviennacl_1_1linalg.html#ab35950c4374eb3be08a03d852508c01a">viennacl::linalg::inner_prod</a>;</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keyword">using</span> <a class="code" href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a>;</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keyword">using</span> <a class="code" href="namespaceviennacl_1_1linalg.html#a1050039fb153ae8ad818390a30f96bc4">viennacl::linalg::lu_factorize</a>;</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keyword">using</span> <a class="code" href="namespaceviennacl.html#a2ee5dd77d41040e0a937a60346475b84">viennacl::trans</a>;</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="classviennacl_1_1tools_1_1timer.html">viennacl::tools::timer</a> timer;</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keywordtype">double</span> time_previous, time_spent;</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keywordtype">size_t</span> Nruns;</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordtype">double</span> time_per_benchmark = 1;</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> <span class="preprocessor">#define BENCHMARK_OP(OPERATION, NAME, PERF, INDEX) \</span></div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="preprocessor"> OPERATION; \</span></div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="preprocessor"> viennacl::backend::finish();\</span></div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="preprocessor"> timer.start(); \</span></div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="preprocessor"> Nruns = 0; \</span></div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="preprocessor"> time_spent = 0; \</span></div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="preprocessor"> while (time_spent < time_per_benchmark) \</span></div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="preprocessor"> { \</span></div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="preprocessor"> time_previous = timer.get(); \</span></div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="preprocessor"> OPERATION; \</span></div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="preprocessor"> viennacl::backend::finish(); \</span></div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="preprocessor"> time_spent += timer.get() - time_previous; \</span></div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="preprocessor"> Nruns+=1; \</span></div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="preprocessor"> } \</span></div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="preprocessor"> time_spent/=(double)Nruns; \</span></div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="preprocessor"> std::cout << prefix << NAME " : " << PERF << " " INDEX << std::endl; \</span></div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="preprocessor"></span></div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="comment">//BLAS1</span></div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  {</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="classviennacl_1_1scalar.html">viennacl::scalar<T></a> s(0);</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  T alpha = (T)2.4;</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> x(BLAS1_N);</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> y(BLAS1_N);</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> z(BLAS1_N);</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="dense__blas_8cpp.html#a394a1b0572531e380bc94ec20cd7a20c">init_random</a>(x);</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="dense__blas_8cpp.html#a394a1b0572531e380bc94ec20cd7a20c">init_random</a>(y);</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <a class="code" href="dense__blas_8cpp.html#a394a1b0572531e380bc94ec20cd7a20c">init_random</a>(z);</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="dense__blas_8cpp.html#a0c464e202ab39eece213320f33750b8b">BENCHMARK_OP</a>(x = y, <span class="stringliteral">"COPY"</span>, std::setprecision(3) << <span class="keywordtype">double</span>(2*BLAS1_N*<span class="keyword">sizeof</span>(T))/time_spent * 1e-9, <span class="stringliteral">"GB/s"</span>)</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <a class="code" href="dense__blas_8cpp.html#a0c464e202ab39eece213320f33750b8b">BENCHMARK_OP</a>(x = y + alpha*x, <span class="stringliteral">"AXPY"</span>, std::setprecision(3) << <span class="keywordtype">double</span>(3*BLAS1_N*<span class="keyword">sizeof</span>(T))/time_spent * 1e-9, <span class="stringliteral">"GB/s"</span>)</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <a class="code" href="dense__blas_8cpp.html#a0c464e202ab39eece213320f33750b8b">BENCHMARK_OP</a>(s = <a class="code" href="namespaceviennacl_1_1linalg.html#ab35950c4374eb3be08a03d852508c01a">inner_prod</a>(x, y), <span class="stringliteral">"DOT"</span>, std::setprecision(3) << <span class="keywordtype">double</span>(2*BLAS1_N*<span class="keyword">sizeof</span>(T))/time_spent * 1e-9, <span class="stringliteral">"GB/s"</span>)</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  }</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span> </div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="comment">//BLAS2</span></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="classviennacl_1_1matrix.html">viennacl::matrix<T,viennacl::column_major></a> A(BLAS2_M, BLAS2_N);</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> x(BLAS2_N);</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<T></a> y(BLAS2_M);</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <a class="code" href="dense__blas_8cpp.html#a394a1b0572531e380bc94ec20cd7a20c">init_random</a>(A);</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="dense__blas_8cpp.html#a394a1b0572531e380bc94ec20cd7a20c">init_random</a>(x);</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <a class="code" href="dense__blas_8cpp.html#a394a1b0572531e380bc94ec20cd7a20c">init_random</a>(y);</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>  <a class="code" href="dense__blas_8cpp.html#a0c464e202ab39eece213320f33750b8b">BENCHMARK_OP</a>(y = <a class="code" href="sparse__prod_8cpp.html#a2c8637b3d6a972d1d8fd85fb3089c6da">prod</a>(A, x), <span class="stringliteral">"GEMV-N"</span>, std::setprecision(3) << <span class="keywordtype">double</span>((BLAS2_M + BLAS2_N + BLAS2_M*BLAS2_N)*<span class="keyword">sizeof</span>(T))/time_spent * 1e-9, <span class="stringliteral">"GB/s"</span>)</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <a class="code" href="dense__blas_8cpp.html#a0c464e202ab39eece213320f33750b8b">BENCHMARK_OP</a>(x = <a class="code" href="sparse__prod_8cpp.html#a2c8637b3d6a972d1d8fd85fb3089c6da">prod</a>(<a class="code" href="blas3__solve_8cpp.html#ad8f94754a20a0c6dc74fd3cb5eb675b3">trans</a>(A), y), <span class="stringliteral">"GEMV-T"</span>, std::setprecision(3) << <span class="keywordtype">double</span>((BLAS2_M + BLAS2_N + BLAS2_M*BLAS2_N)*<span class="keyword">sizeof</span>(T))/time_spent * 1e-9, <span class="stringliteral">"GB/s"</span>)</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  }</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="comment">//BLAS3</span></div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  {</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<T,viennacl::column_major></a> C(BLAS3_M, BLAS3_N);</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<T,viennacl::column_major></a> A(BLAS3_M, BLAS3_K);</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<T,viennacl::column_major></a> B(BLAS3_K, BLAS3_N);</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<T,viennacl::column_major></a> AT = <a class="code" href="blas3__solve_8cpp.html#ad8f94754a20a0c6dc74fd3cb5eb675b3">trans</a>(A);</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<T,viennacl::column_major></a> BT = <a class="code" href="blas3__solve_8cpp.html#ad8f94754a20a0c6dc74fd3cb5eb675b3">trans</a>(B);</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="dense__blas_8cpp.html#a394a1b0572531e380bc94ec20cd7a20c">init_random</a>(A);</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <a class="code" href="dense__blas_8cpp.html#a394a1b0572531e380bc94ec20cd7a20c">init_random</a>(B);</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <a class="code" href="dense__blas_8cpp.html#a0c464e202ab39eece213320f33750b8b">BENCHMARK_OP</a>(C = <a class="code" href="sparse__prod_8cpp.html#a2c8637b3d6a972d1d8fd85fb3089c6da">prod</a>(A, B), <span class="stringliteral">"GEMM-NN"</span>, <span class="keywordtype">double</span>(2*BLAS3_M*BLAS3_N*BLAS3_K)/time_spent*1e-9, <span class="stringliteral">"GFLOPs/s"</span>);</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <a class="code" href="dense__blas_8cpp.html#a0c464e202ab39eece213320f33750b8b">BENCHMARK_OP</a>(C = <a class="code" href="sparse__prod_8cpp.html#a2c8637b3d6a972d1d8fd85fb3089c6da">prod</a>(A, <a class="code" href="blas3__solve_8cpp.html#ad8f94754a20a0c6dc74fd3cb5eb675b3">trans</a>(BT)), <span class="stringliteral">"GEMM-NT"</span>, <span class="keywordtype">double</span>(2*BLAS3_M*BLAS3_N*BLAS3_K)/time_spent*1e-9, <span class="stringliteral">"GFLOPs/s"</span>);</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <a class="code" href="dense__blas_8cpp.html#a0c464e202ab39eece213320f33750b8b">BENCHMARK_OP</a>(C = <a class="code" href="sparse__prod_8cpp.html#a2c8637b3d6a972d1d8fd85fb3089c6da">prod</a>(<a class="code" href="blas3__solve_8cpp.html#ad8f94754a20a0c6dc74fd3cb5eb675b3">trans</a>(AT), B), <span class="stringliteral">"GEMM-TN"</span>, <span class="keywordtype">double</span>(2*BLAS3_M*BLAS3_N*BLAS3_K)/time_spent*1e-9, <span class="stringliteral">"GFLOPs/s"</span>);</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="dense__blas_8cpp.html#a0c464e202ab39eece213320f33750b8b">BENCHMARK_OP</a>(C = <a class="code" href="sparse__prod_8cpp.html#a2c8637b3d6a972d1d8fd85fb3089c6da">prod</a>(<a class="code" href="blas3__solve_8cpp.html#ad8f94754a20a0c6dc74fd3cb5eb675b3">trans</a>(AT), <a class="code" href="blas3__solve_8cpp.html#ad8f94754a20a0c6dc74fd3cb5eb675b3">trans</a>(BT)), <span class="stringliteral">"GEMM-TT"</span>, <span class="keywordtype">double</span>(2*BLAS3_M*BLAS3_N*BLAS3_K)/time_spent*1e-9, <span class="stringliteral">"GFLOPs/s"</span>);</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="comment">//BENCHMARK_OP(lu_factorize(A), "LU-FACTORIZE", double(2*BLAS3_M*BLAS3_K*BLAS3_K)/time_spent*1e-9, "GFLOPs/s");</span></div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  }</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span> }</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span> </div>
<div class="line"><a name="l00131"></a><span class="lineno"><a class="line" href="dense__blas_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4"> 131</a></span> <span class="keywordtype">int</span> <a class="code" href="dense__blas_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a>()</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> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENCL</span></div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  std::cout << std::endl;</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  std::cout << <span class="stringliteral">"----------------------------------------------"</span> << std::endl;</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  std::cout << <span class="stringliteral">" Device Info"</span> << std::endl;</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  std::cout << <span class="stringliteral">"----------------------------------------------"</span> << std::endl;</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  std::cout << std::endl;</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  std::cout << <a class="code" href="namespaceviennacl_1_1ocl.html#ac54d59a74deaccec81f64e738b856348">viennacl::ocl::current_device</a>().<a class="code" href="classviennacl_1_1ocl_1_1device.html#a26a424782f982725453808a94763bd19">info</a>() << std::endl;</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  std::cout << std::endl;</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  std::size_t BLAS1_N = 10000000;</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>  std::size_t BLAS2_M = 3840;</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  std::size_t BLAS2_N = 3840;</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span> </div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  std::size_t BLAS3_M = 1976;</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  std::size_t BLAS3_N = 1976;</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  std::size_t BLAS3_K = 1976;</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>  std::cout << <span class="stringliteral">"Benchmark : BLAS"</span> << std::endl;</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  std::cout << <span class="stringliteral">"----------------"</span> << std::endl;</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  bench<float>(BLAS1_N, BLAS2_M, BLAS2_N, BLAS3_M, BLAS3_N, BLAS3_K, <span class="stringliteral">"s"</span>);</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  std::cout << <span class="stringliteral">"----"</span> << std::endl;</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="preprocessor">#ifdef VIENNACL_WITH_OPENCL</span></div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keywordflow">if</span> ( <a class="code" href="namespaceviennacl_1_1ocl.html#ac54d59a74deaccec81f64e738b856348">viennacl::ocl::current_device</a>().<a class="code" href="classviennacl_1_1ocl_1_1device.html#a5182025f56c76de6770e26b14165b00a">double_support</a>() )</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span> #endif</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  bench<double>(BLAS1_N, BLAS2_M, BLAS2_N, BLAS3_M, BLAS3_N, BLAS3_K, <span class="stringliteral">"d"</span>);</div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span> }</div>
<div class="ttc" id="dense__blas_8cpp_html_a394a1b0572531e380bc94ec20cd7a20c"><div class="ttname"><a href="dense__blas_8cpp.html#a394a1b0572531e380bc94ec20cd7a20c">init_random</a></div><div class="ttdeci">void init_random(viennacl::matrix< T, F > &M)</div><div class="ttdef"><b>Definition:</b> <a href="dense__blas_8cpp_source.html#l00032">dense_blas.cpp:32</a></div></div>
<div class="ttc" id="classviennacl_1_1tools_1_1timer_html"><div class="ttname"><a href="classviennacl_1_1tools_1_1timer.html">viennacl::tools::timer</a></div><div class="ttdoc">Simple timer class based on gettimeofday (POSIX) or QueryPerformanceCounter (Windows). </div><div class="ttdef"><b>Definition:</b> <a href="timer_8hpp_source.html#l00090">timer.hpp:90</a></div></div>
<div class="ttc" id="classviennacl_1_1scalar_html"><div class="ttname"><a href="classviennacl_1_1scalar.html">viennacl::scalar</a></div><div class="ttdoc">This class represents a single scalar value on the GPU and behaves mostly like a built-in scalar type...</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00227">forwards.h:227</a></div></div>
<div class="ttc" id="namespaceviennacl_html_a2ee5dd77d41040e0a937a60346475b84"><div class="ttname"><a href="namespaceviennacl.html#a2ee5dd77d41040e0a937a60346475b84">viennacl::trans</a></div><div class="ttdeci">viennacl::enable_if< viennacl::is_any_sparse_matrix< M1 >::value, matrix_expression< const M1, const M1, op_trans > >::type trans(const M1 &mat)</div><div class="ttdoc">Returns an expression template class representing a transposed matrix. </div><div class="ttdef"><b>Definition:</b> <a href="sparse__matrix__operations_8hpp_source.html#l00376">sparse_matrix_operations.hpp:376</a></div></div>
<div class="ttc" id="dense__blas_8cpp_html_af6bb6f04705830fb7e059fe0572778d6"><div class="ttname"><a href="dense__blas_8cpp.html#af6bb6f04705830fb7e059fe0572778d6">bench</a></div><div class="ttdeci">void bench(size_t BLAS1_N, size_t BLAS2_M, size_t BLAS2_N, size_t BLAS3_M, size_t BLAS3_N, size_t BLAS3_K, std::string const &prefix)</div><div class="ttdef"><b>Definition:</b> <a href="dense__blas_8cpp_source.html#l00051">dense_blas.cpp:51</a></div></div>
<div class="ttc" id="classviennacl_1_1matrix__base_html_a7f1b176eaa22875c3dc04750498616a1"><div class="ttname"><a href="classviennacl_1_1matrix__base.html#a7f1b176eaa22875c3dc04750498616a1">viennacl::matrix_base< NumericT >::internal_size</a></div><div class="ttdeci">size_type internal_size() const</div><div class="ttdoc">Returns the total amount of allocated memory in multiples of sizeof(NumericT) </div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00242">matrix_def.hpp:242</a></div></div>
<div class="ttc" id="blas3__solve_8cpp_html_ad8f94754a20a0c6dc74fd3cb5eb675b3"><div class="ttname"><a href="blas3__solve_8cpp.html#ad8f94754a20a0c6dc74fd3cb5eb675b3">trans</a></div><div class="ttdeci">std::vector< std::vector< NumericT > > trans(std::vector< std::vector< NumericT > > const &A)</div><div class="ttdef"><b>Definition:</b> <a href="blas3__solve_8cpp_source.html#l00195">blas3_solve.cpp:195</a></div></div>
<div class="ttc" id="prod_8hpp_html"><div class="ttname"><a href="prod_8hpp.html">prod.hpp</a></div><div class="ttdoc">Generic interface for matrix-vector and matrix-matrix products. See viennacl/linalg/vector_operations...</div></div>
<div class="ttc" id="matrix_8hpp_html"><div class="ttname"><a href="matrix_8hpp.html">matrix.hpp</a></div><div class="ttdoc">Implementation of the dense matrix class. </div></div>
<div class="ttc" id="classviennacl_1_1matrix_html"><div class="ttname"><a href="classviennacl_1_1matrix.html">viennacl::matrix</a></div><div class="ttdoc">A dense matrix class. </div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00375">forwards.h:375</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_ab35950c4374eb3be08a03d852508c01a"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#ab35950c4374eb3be08a03d852508c01a">viennacl::linalg::inner_prod</a></div><div class="ttdeci">viennacl::enable_if< viennacl::is_stl< typename viennacl::traits::tag_of< VectorT1 >::type >::value, typename VectorT1::value_type >::type inner_prod(VectorT1 const &v1, VectorT2 const &v2)</div><div class="ttdef"><b>Definition:</b> <a href="inner__prod_8hpp_source.html#l00100">inner_prod.hpp:100</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1ocl_html_ac54d59a74deaccec81f64e738b856348"><div class="ttname"><a href="namespaceviennacl_1_1ocl.html#ac54d59a74deaccec81f64e738b856348">viennacl::ocl::current_device</a></div><div class="ttdeci">viennacl::ocl::device const & current_device()</div><div class="ttdoc">Convenience function for returning the active device in the current context. </div><div class="ttdef"><b>Definition:</b> <a href="backend_8hpp_source.html#l00351">backend.hpp:351</a></div></div>
<div class="ttc" id="inner__prod_8hpp_html"><div class="ttname"><a href="inner__prod_8hpp.html">inner_prod.hpp</a></div><div class="ttdoc">Generic interface for the computation of inner products. See viennacl/linalg/vector_operations.hpp for implementations. </div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1device_html_a26a424782f982725453808a94763bd19"><div class="ttname"><a href="classviennacl_1_1ocl_1_1device.html#a26a424782f982725453808a94763bd19">viennacl::ocl::device::info</a></div><div class="ttdeci">std::string info(vcl_size_t indent=0, char indent_char= ' ') const </div><div class="ttdoc">Returns an info string with a few properties of the device. Use full_info() to get all details...</div><div class="ttdef"><b>Definition:</b> <a href="device_8hpp_source.html#l00995">device.hpp:995</a></div></div>
<div class="ttc" id="dense__blas_8cpp_html_a0c464e202ab39eece213320f33750b8b"><div class="ttname"><a href="dense__blas_8cpp.html#a0c464e202ab39eece213320f33750b8b">BENCHMARK_OP</a></div><div class="ttdeci">#define BENCHMARK_OP(OPERATION, NAME, PERF, INDEX)</div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_aa18d10f8a90e38bd9ff43c650fc670ef"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a></div><div class="ttdeci">VectorT prod(std::vector< std::vector< T, A1 >, A2 > const &matrix, VectorT const &vector)</div><div class="ttdef"><b>Definition:</b> <a href="prod_8hpp_source.html#l00102">prod.hpp:102</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html_a762d98e2f912fc534951f25555b6077f"><div class="ttname"><a href="classviennacl_1_1vector__base.html#a762d98e2f912fc534951f25555b6077f">viennacl::vector_base< NumericT >::begin</a></div><div class="ttdeci">iterator begin()</div><div class="ttdoc">Returns an iterator pointing to the beginning of the vector (STL like) </div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1device_html_a5182025f56c76de6770e26b14165b00a"><div class="ttname"><a href="classviennacl_1_1ocl_1_1device.html#a5182025f56c76de6770e26b14165b00a">viennacl::ocl::device::double_support</a></div><div class="ttdeci">bool double_support() const </div><div class="ttdoc">ViennaCL convenience function: Returns true if the device supports double precision. </div><div class="ttdef"><b>Definition:</b> <a href="device_8hpp_source.html#l00956">device.hpp:956</a></div></div>
<div class="ttc" id="classviennacl_1_1matrix__base_html_a4348766b3b9cb049f7acd6a795272dbe"><div class="ttname"><a href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">viennacl::matrix_base< NumericT >::size2</a></div><div class="ttdeci">size_type size2() const</div><div class="ttdoc">Returns the number of columns. </div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00226">matrix_def.hpp:226</a></div></div>
<div class="ttc" id="classviennacl_1_1vector_html"><div class="ttname"><a href="classviennacl_1_1vector.html">viennacl::vector</a></div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00266">forwards.h:266</a></div></div>
<div class="ttc" id="lu_8hpp_html"><div class="ttname"><a href="lu_8hpp.html">lu.hpp</a></div><div class="ttdoc">Implementations of LU factorization for row-major and column-major dense matrices. </div></div>
<div class="ttc" id="classviennacl_1_1matrix__base_html_a24e4f5fa27a1af5ad47e52a97c065d68"><div class="ttname"><a href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">viennacl::matrix_base< NumericT >::size1</a></div><div class="ttdeci">size_type size1() const</div><div class="ttdoc">Returns the number of rows. </div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00224">matrix_def.hpp:224</a></div></div>
<div class="ttc" id="vector__proxy_8hpp_html"><div class="ttname"><a href="vector__proxy_8hpp.html">vector_proxy.hpp</a></div><div class="ttdoc">Proxy classes for vectors. </div></div>
<div class="ttc" id="timer_8hpp_html"><div class="ttname"><a href="timer_8hpp.html">timer.hpp</a></div><div class="ttdoc">A simple, yet (mostly) sufficiently accurate timer for benchmarking and profiling. </div></div>
<div class="ttc" id="matrix__proxy_8hpp_html"><div class="ttname"><a href="matrix__proxy_8hpp.html">matrix_proxy.hpp</a></div><div class="ttdoc">Proxy classes for matrices. </div></div>
<div class="ttc" id="sparse__prod_8cpp_html_a2c8637b3d6a972d1d8fd85fb3089c6da"><div class="ttname"><a href="sparse__prod_8cpp.html#a2c8637b3d6a972d1d8fd85fb3089c6da">prod</a></div><div class="ttdeci">void prod(std::vector< std::map< IndexT, NumericT > > const &stl_A, std::vector< std::map< IndexT, NumericT > > const &stl_B, std::vector< std::map< IndexT, NumericT > > &stl_C)</div><div class="ttdef"><b>Definition:</b> <a href="sparse__prod_8cpp_source.html#l00114">sparse_prod.cpp:114</a></div></div>
<div class="ttc" id="vector_8hpp_html"><div class="ttname"><a href="vector_8hpp.html">vector.hpp</a></div><div class="ttdoc">The vector type with operator-overloads and proxy classes is defined here. Linear algebra operations ...</div></div>
<div class="ttc" id="classviennacl_1_1matrix__base_html_a00e30fdc61081a73995b54175a91d220"><div class="ttname"><a href="classviennacl_1_1matrix__base.html#a00e30fdc61081a73995b54175a91d220">viennacl::matrix_base< NumericT >::internal_size2</a></div><div class="ttdeci">size_type internal_size2() const</div><div class="ttdoc">Returns the internal number of columns. Usually required for launching OpenCL kernels only...</div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00240">matrix_def.hpp:240</a></div></div>
<div class="ttc" id="dense__blas_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="dense__blas_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> <a href="dense__blas_8cpp_source.html#l00131">dense_blas.cpp:131</a></div></div>
<div class="ttc" id="classviennacl_1_1matrix__base_html_a82018b4e169973bdfb9d3be68ceb5be0"><div class="ttname"><a href="classviennacl_1_1matrix__base.html#a82018b4e169973bdfb9d3be68ceb5be0">viennacl::matrix_base< NumericT >::internal_size1</a></div><div class="ttdeci">size_type internal_size1() const</div><div class="ttdoc">Returns the internal number of rows. Usually required for launching OpenCL kernels only...</div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00238">matrix_def.hpp:238</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< NumericT >::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="namespaceviennacl_1_1linalg_html_a1050039fb153ae8ad818390a30f96bc4"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a1050039fb153ae8ad818390a30f96bc4">viennacl::linalg::lu_factorize</a></div><div class="ttdeci">void lu_factorize(matrix< NumericT, viennacl::row_major > &A)</div><div class="ttdoc">LU factorization of a row-major dense matrix. </div><div class="ttdef"><b>Definition:</b> <a href="lu_8hpp_source.html#l00042">lu.hpp:42</a></div></div>
<div class="ttc" id="namespaceviennacl_html_aaa5c8726b45bc89a523ca2fa8c42107a"><div class="ttname"><a href="namespaceviennacl.html#aaa5c8726b45bc89a523ca2fa8c42107a">viennacl::fast_copy</a></div><div class="ttdeci">void fast_copy(const const_vector_iterator< SCALARTYPE, ALIGNMENT > &gpu_begin, const const_vector_iterator< SCALARTYPE, ALIGNMENT > &gpu_end, CPU_ITERATOR cpu_begin)</div></div>
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