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<div class="title">BifrostTuner.cpp</div> </div>
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<a href="_bifrost_tuner_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment"> * Copyright (c) 2018 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_bifrost_tuner_8h.xhtml">arm_compute/runtime/CL/tuners/BifrostTuner.h</a>&quot;</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="core_2_c_l_2_c_l_helpers_8h.xhtml">arm_compute/core/CL/CLHelpers.h</a>&quot;</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_c_l_kernels_8h.xhtml">arm_compute/core/CL/CLKernels.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_cast_8h.xhtml">arm_compute/core/utils/misc/Cast.h</a>&quot;</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;{</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<span class="keyword">namespace </span>tuners</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;{</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;<span class="keyword">namespace</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;{</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;<span class="keywordtype">void</span> tune_direct_convolution_kernel(CLDirectConvolutionLayerKernel &amp;k)</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160;{</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; cl::NDRange lws_hint = k.lws_hint();</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target = k.get_target();</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dt = k._input-&gt;info()-&gt;data_type();</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="keyword">const</span> TensorShape <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae8f0126f051c787279a8c9ee3c3a5d55">weights_shape</a> = k._weights-&gt;info()-&gt;tensor_shape();</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="keyword">const</span> TensorShape inputs_shape = k._input-&gt;info()-&gt;tensor_shape();</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> kernel_size = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae8f0126f051c787279a8c9ee3c3a5d55">weights_shape</a>.x();</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> stride_x = k._conv_stride_x;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> stride_y = k._conv_stride_y;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute.xhtml#a1da498e9b2c2d24883087f62c6bbe75d">gpu_target_is_in</a>(gpu_target, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6">GPUTarget::G71</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc">GPUTarget::G72</a>) &amp;&amp; (kernel_size &lt;= 5) &amp;&amp; (stride_x == 1) &amp;&amp; (stride_y == 1) &amp;&amp; (dt == <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>))</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; {</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="comment">// Through extensive experimentation with over 30 representative tensor</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; <span class="comment">// shapes, we found a small number of local work size configurations</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="comment">// that result in nearly optimal execution times. Selecting the right</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <span class="comment">// lws for a given shape, however, required a complex decision tree,</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="comment">// until we constructed a simple feature as described below.</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <span class="comment">//</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <span class="comment">// We started from the number of multiply-accumulate operations for a</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <span class="comment">// convolution layer, which is equal to the product of the input</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <span class="comment">// dimensions 0..2 and the weights dimensions 0..2. Unfortunately,</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <span class="comment">// this resulted in ties between distinct shapes that required distinct</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="comment">// lws configurations. Replacing the width of the input with the kernel</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="comment">// size, however, resulted in nearly optimal predictions. We use underscores</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="comment">// in variable names to indicate when they are intentionally misleading.</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> product_of_weights_dimensions = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae8f0126f051c787279a8c9ee3c3a5d55">weights_shape</a>[0] * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae8f0126f051c787279a8c9ee3c3a5d55">weights_shape</a>[1] * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae8f0126f051c787279a8c9ee3c3a5d55">weights_shape</a>[2];</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> product_of_input_dimensions_ = inputs_shape[0] * inputs_shape[1] * inputs_shape[2];</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <span class="keyword">const</span> <span class="keywordtype">float</span> mega_ops_ = 1e-6 * product_of_weights_dimensions * product_of_input_dimensions_;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; <span class="keywordflow">switch</span>(kernel_size)</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; {</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; {</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <span class="keywordflow">if</span>(mega_ops_ &lt; 1.f)</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; {</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; lws_hint = cl::NDRange(1, 1, 8);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; }</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(mega_ops_ &lt; 7.f)</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; {</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; lws_hint = cl::NDRange(1, 1, 4);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; }</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; {</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; lws_hint = cl::NDRange(1, 1, 2);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; }</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; }</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; <span class="keywordflow">case</span> 3:</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; {</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <span class="keywordflow">if</span>(mega_ops_ &lt; 1.f)</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; {</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; lws_hint = cl::NDRange(1, 1, 8);</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; }</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(mega_ops_ &lt; 13.f)</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; {</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; lws_hint = cl::NDRange(2, 1, 4);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; }</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(mega_ops_ &lt; 50.f)</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; {</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; lws_hint = cl::NDRange(3, 1, 4);</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; }</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; {</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; lws_hint = cl::NDRange(2, 1, 6);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; }</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; }</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <span class="keywordflow">case</span> 5:</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; {</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <span class="keywordflow">if</span>(mega_ops_ &lt; 2.f || mega_ops_ &gt; 80.f)</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; {</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; lws_hint = cl::NDRange(2, 1, 4);</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; }</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; {</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; lws_hint = cl::NDRange(2, 1, 8);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; }</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; }</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="keywordflow">default</span>:</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; }</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; k.set_lws_hint(lws_hint);</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; }</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160;}</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160;</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160;<span class="keywordtype">void</span> tune_col2im_kernel(CLCol2ImKernel &amp;k)</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160;{</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; cl::NDRange lws_hint = k.lws_hint();</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target = k.get_target();</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <span class="comment">// Configure the local work size for Bifrost with a value obtained</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; <span class="comment">// via exhaustive autotuning over 30 representative tensor shapes.</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute.xhtml#a1da498e9b2c2d24883087f62c6bbe75d">gpu_target_is_in</a>(gpu_target,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6">GPUTarget::G71</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc">GPUTarget::G72</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3aa46ce37da51477a1af33a8810e0ed04d">GPUTarget::G76</a>,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a0a2d4856ae75ec5a7b78851f6e5875f0">GPUTarget::G51</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afc99dd3bc5650c5116886eefd3d18988">GPUTarget::G51BIG</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a9d0acedfece9dfaf5cc3e63bfbeecf2f">GPUTarget::G51LIT</a>,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a3731064380218cfc2b9613d2b6293cfb">GPUTarget::G52</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a4b3e9b93a7e833f9d7ab01d4cf9f7837">GPUTarget::G52LIT</a>))</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; {</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <span class="keywordflow">if</span>((k._convolved_dims.width == 7) || (k._convolved_dims.width == 14))</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; {</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; lws_hint = cl::NDRange(1, 7, 1);</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; }</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; {</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; lws_hint = cl::NDRange(1, 8, 1);</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; }</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; }</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; k.set_lws_hint(lws_hint);</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160;}</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160;</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160;<span class="keywordtype">void</span> tune_im2col_kernel(CLIm2ColKernel &amp;k)</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160;{</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; cl::NDRange lws_hint = k.lws_hint();</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target = k.get_target();</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160;</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; <span class="comment">// Local work size optimized for the 11x11 AlexNet convolution on Bifrost.</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute.xhtml#a1da498e9b2c2d24883087f62c6bbe75d">gpu_target_is_in</a>(gpu_target,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6">GPUTarget::G71</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc">GPUTarget::G72</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3aa46ce37da51477a1af33a8810e0ed04d">GPUTarget::G76</a>,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a0a2d4856ae75ec5a7b78851f6e5875f0">GPUTarget::G51</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afc99dd3bc5650c5116886eefd3d18988">GPUTarget::G51BIG</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a9d0acedfece9dfaf5cc3e63bfbeecf2f">GPUTarget::G51LIT</a>,</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a3731064380218cfc2b9613d2b6293cfb">GPUTarget::G52</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a4b3e9b93a7e833f9d7ab01d4cf9f7837">GPUTarget::G52LIT</a>)</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; &amp;&amp; k._kernel_dims.width == 11)</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; {</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; <span class="keyword">const</span> <span class="keywordtype">bool</span> is_square_kernel = (k._kernel_dims.width == k._kernel_dims.height);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; <span class="keywordflow">if</span>(!is_square_kernel &amp;&amp; k._kernel_dims.width &gt; 1 &amp;&amp; !k._conv_info.has_padding())</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; {</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; lws_hint = cl::NDRange(1, 1, 1);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; }</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; }</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; k.set_lws_hint(lws_hint);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160;}</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160;</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160;<span class="keywordtype">void</span> tune_depthwise_im2col_kernel(CLDepthwiseIm2ColKernel &amp;k)</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160;{</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; cl::NDRange lws_hint = k.lws_hint();</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target = k.get_target();</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160;</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; <span class="comment">// Configure the local work size for Bifrost with a value obtained</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; <span class="comment">// via exhaustive autotuning for the MobileNets tensor shapes.</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute.xhtml#a1da498e9b2c2d24883087f62c6bbe75d">gpu_target_is_in</a>(gpu_target,</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6">GPUTarget::G71</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc">GPUTarget::G72</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3aa46ce37da51477a1af33a8810e0ed04d">GPUTarget::G76</a>,</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a0a2d4856ae75ec5a7b78851f6e5875f0">GPUTarget::G51</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afc99dd3bc5650c5116886eefd3d18988">GPUTarget::G51BIG</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a9d0acedfece9dfaf5cc3e63bfbeecf2f">GPUTarget::G51LIT</a>,</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a3731064380218cfc2b9613d2b6293cfb">GPUTarget::G52</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a4b3e9b93a7e833f9d7ab01d4cf9f7837">GPUTarget::G52LIT</a>))</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; {</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160; lws_hint = cl::NDRange(1, 2, 1);</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160; }</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160;</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>&#160; k.set_lws_hint(lws_hint);</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160;}</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160;</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160;<span class="keywordtype">void</span> tune_gemv_kernel(CLGEMMMatrixVectorMultiplyKernel &amp;k)</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160;{</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; cl::NDRange lws_hint = k.lws_hint();</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target = k.get_target();</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160;</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; <span class="comment">// Configure the local work size for Bifrost with a value obtained</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; <span class="comment">// via exhaustive autotuning for the MobileNets tensor shapes.</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute.xhtml#a1da498e9b2c2d24883087f62c6bbe75d">gpu_target_is_in</a>(gpu_target,</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6">GPUTarget::G71</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc">GPUTarget::G72</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3aa46ce37da51477a1af33a8810e0ed04d">GPUTarget::G76</a>,</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a0a2d4856ae75ec5a7b78851f6e5875f0">GPUTarget::G51</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afc99dd3bc5650c5116886eefd3d18988">GPUTarget::G51BIG</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a9d0acedfece9dfaf5cc3e63bfbeecf2f">GPUTarget::G51LIT</a>,</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a3731064380218cfc2b9613d2b6293cfb">GPUTarget::G52</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a4b3e9b93a7e833f9d7ab01d4cf9f7837">GPUTarget::G52LIT</a>))</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160; {</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160; lws_hint = cl::NDRange(1, 1, 1);</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160; }</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160;</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; k.set_lws_hint(lws_hint);</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160;}</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160;</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160;<span class="keywordtype">void</span> tune_gemm_kernel(CLGEMMMatrixMultiplyKernel &amp;k)</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160;{</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; cl::NDRange lws_hint = k.lws_hint();</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target = k.get_target();</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160;</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; <span class="comment">// Configure LWS hint</span></div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; <span class="keywordflow">switch</span>(gpu_target)</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; {</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6">GPUTarget::G71</a>:</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc">GPUTarget::G72</a>:</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a0a2d4856ae75ec5a7b78851f6e5875f0">GPUTarget::G51</a>:</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afc99dd3bc5650c5116886eefd3d18988">GPUTarget::G51BIG</a>:</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a9d0acedfece9dfaf5cc3e63bfbeecf2f">GPUTarget::G51LIT</a>:</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a3731064380218cfc2b9613d2b6293cfb">GPUTarget::G52</a>:</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a4b3e9b93a7e833f9d7ab01d4cf9f7837">GPUTarget::G52LIT</a>:</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3aa46ce37da51477a1af33a8810e0ed04d">GPUTarget::G76</a>:</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; <span class="keywordflow">if</span>(k._input1-&gt;info()-&gt;dimension(1) == 24)</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; {</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; <span class="comment">// LWS optimized for the 11x11 AlexNet convolution on Bifrost.</span></div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; lws_hint = cl::NDRange(2, 2);</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; }</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(k._output-&gt;info()-&gt;dimension(1) == 196)</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160; {</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160; lws_hint = cl::NDRange(1, 7);</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160; }</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160; {</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160; lws_hint = cl::NDRange(8, 8);</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; }</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; <span class="keywordflow">default</span>:</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; lws_hint = cl::NullRange;</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; }</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160;</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; k.set_lws_hint(lws_hint);</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160;}</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160;<span class="keywordtype">void</span> tune_pooling_kernel(CLPoolingLayerKernel &amp;k)</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160;{</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; cl::NDRange lws_hint = k.lws_hint();</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target = k.get_target();</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160;</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; <span class="comment">// Configure the local work size (hint) from the first two dimensions of the global work size.</span></div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; <span class="comment">// On Bifrost, this works for up to 35x35xC filters, for which the pooling_layer_3_optimized</span></div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; <span class="comment">// kernel is launched with gws=(9, 33, C). In any case, the hint will be ignored if it is</span></div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; <span class="comment">// invalid (e.g. exceeds the maximum workgroup size that the kernel can be launched with).</span></div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; <span class="keywordflow">if</span>(k._input-&gt;info()-&gt;data_layout() == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>)</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; {</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160; <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute.xhtml#a1da498e9b2c2d24883087f62c6bbe75d">gpu_target_is_in</a>(gpu_target,</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6">GPUTarget::G71</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc">GPUTarget::G72</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3aa46ce37da51477a1af33a8810e0ed04d">GPUTarget::G76</a>,</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a0a2d4856ae75ec5a7b78851f6e5875f0">GPUTarget::G51</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afc99dd3bc5650c5116886eefd3d18988">GPUTarget::G51BIG</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a9d0acedfece9dfaf5cc3e63bfbeecf2f">GPUTarget::G51LIT</a>,</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a3731064380218cfc2b9613d2b6293cfb">GPUTarget::G52</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a4b3e9b93a7e833f9d7ab01d4cf9f7837">GPUTarget::G52LIT</a>))</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; {</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; cl::NDRange gws = <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6c01790e4e3f22f70f69002f0cb1b913">ICLKernel::gws_from_window</a>(k.window());</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; lws_hint = cl::NDRange(gws[0], gws[1], 1);</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; }</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; }</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160;</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; k.set_lws_hint(lws_hint);</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160;}</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160;</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160;<span class="keywordtype">void</span> tune_scale_kernel(CLScaleKernel &amp;k)</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160;{</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; cl::NDRange lws_hint = k.lws_hint();</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target = k.get_target();</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dt = k.input()-&gt;info()-&gt;data_type();</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a966a9c417ce5e94dca08d9b5e745c0c9">InterpolationPolicy</a> interpolation = k._interpolationPolicy;</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160;</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160; <span class="comment">// Configure the local work size for Bifrost, interpolation (bilinear) and datatype F32.</span></div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160; <span class="comment">// The value are obtained via exhaustive autotuning.</span></div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>&#160; <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute.xhtml#a1da498e9b2c2d24883087f62c6bbe75d">gpu_target_is_in</a>(gpu_target, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6">GPUTarget::G71</a>, <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc">GPUTarget::G72</a>) &amp;&amp; (dt == <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>) &amp;&amp; (interpolation == <a class="code" href="namespacearm__compute.xhtml#a966a9c417ce5e94dca08d9b5e745c0c9aad6fddf718ad19b063e02fdd7e8e3e65">InterpolationPolicy::BILINEAR</a>))</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160; {</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160; <span class="keyword">auto</span> dim_0 = k.output()-&gt;info()-&gt;dimension(0);</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160; <span class="keywordflow">if</span>(dim_0 == 480)</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; {</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160; lws_hint = cl::NDRange(2, 1);</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; }</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(dim_0 == 3120)</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; {</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; lws_hint = cl::NDRange(2, 8);</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; }</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(dim_0 == 4160)</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; {</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160; lws_hint = cl::NDRange(4, 8);</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; }</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; k.set_lws_hint(lws_hint);</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160; }</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160;}</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160;} <span class="comment">// namespace</span></div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160;</div><div class="line"><a name="l00300"></a><span class="lineno"><a class="line" href="classarm__compute_1_1tuners_1_1_bifrost_tuner.xhtml#a52f755d664bbdcb9346cdf5cc4a7e958"> 300</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1tuners_1_1_bifrost_tuner.xhtml#a52f755d664bbdcb9346cdf5cc4a7e958">BifrostTuner::tune_kernel_static</a>(<a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml">ICLKernel</a> &amp;kernel)</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160;{</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160; <span class="keywordflow">if</span>(dynamic_cast&lt;CLDirectConvolutionLayerKernel *&gt;(&amp;kernel) != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160; {</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160; tune_direct_convolution_kernel(*utils::cast::polymorphic_downcast&lt;CLDirectConvolutionLayerKernel *&gt;(&amp;kernel));</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160; }</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(dynamic_cast&lt;CLCol2ImKernel *&gt;(&amp;kernel) != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; {</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160; tune_col2im_kernel(*utils::cast::polymorphic_downcast&lt;CLCol2ImKernel *&gt;(&amp;kernel));</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; }</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(dynamic_cast&lt;CLIm2ColKernel *&gt;(&amp;kernel) != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160; {</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160; tune_im2col_kernel(*utils::cast::polymorphic_downcast&lt;CLIm2ColKernel *&gt;(&amp;kernel));</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160; }</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(dynamic_cast&lt;CLDepthwiseIm2ColKernel *&gt;(&amp;kernel) != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160; {</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160; tune_depthwise_im2col_kernel(*utils::cast::polymorphic_downcast&lt;CLDepthwiseIm2ColKernel *&gt;(&amp;kernel));</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160; }</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(dynamic_cast&lt;CLGEMMMatrixVectorMultiplyKernel *&gt;(&amp;kernel) != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160; {</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160; tune_gemv_kernel(*utils::cast::polymorphic_downcast&lt;CLGEMMMatrixVectorMultiplyKernel *&gt;(&amp;kernel));</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160; }</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(dynamic_cast&lt;CLGEMMMatrixMultiplyKernel *&gt;(&amp;kernel) != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160; {</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>&#160; tune_gemm_kernel(*utils::cast::polymorphic_downcast&lt;CLGEMMMatrixMultiplyKernel *&gt;(&amp;kernel));</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>&#160; }</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(dynamic_cast&lt;CLPoolingLayerKernel *&gt;(&amp;kernel) != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>&#160; {</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160; tune_pooling_kernel(*utils::cast::polymorphic_downcast&lt;CLPoolingLayerKernel *&gt;(&amp;kernel));</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>&#160; }</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(dynamic_cast&lt;CLScaleKernel *&gt;(&amp;kernel) != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160; {</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160; tune_scale_kernel(*utils::cast::polymorphic_downcast&lt;CLScaleKernel *&gt;(&amp;kernel));</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160; }</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160;}</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160;</div><div class="line"><a name="l00336"></a><span class="lineno"><a class="line" href="classarm__compute_1_1tuners_1_1_bifrost_tuner.xhtml#af073b532560e2105dd22d381f5888ce7"> 336</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1tuners_1_1_bifrost_tuner.xhtml#af073b532560e2105dd22d381f5888ce7">BifrostTuner::tune_kernel_dynamic</a>(<a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml">ICLKernel</a> &amp;kernel)</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160;{</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(kernel);</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160;}</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160;} <span class="comment">// namespace tuners</span></div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160;} <span class="comment">// namespace arm_compute</span></div><div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a6c01790e4e3f22f70f69002f0cb1b913"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6c01790e4e3f22f70f69002f0cb1b913">arm_compute::ICLKernel::gws_from_window</a></div><div class="ttdeci">static cl::NDRange gws_from_window(const Window &amp;window)</div><div class="ttdoc">Get the global work size given an execution window.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8cpp_source.xhtml#l00141">ICLKernel.cpp:141</a></div></div>
<div class="ttc" id="_c_l_kernels_8h_xhtml"><div class="ttname"><a href="_c_l_kernels_8h.xhtml">CLKernels.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a966a9c417ce5e94dca08d9b5e745c0c9"><div class="ttname"><a href="namespacearm__compute.xhtml#a966a9c417ce5e94dca08d9b5e745c0c9">arm_compute::InterpolationPolicy</a></div><div class="ttdeci">InterpolationPolicy</div><div class="ttdoc">Interpolation method.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00356">Types.h:356</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3aa46ce37da51477a1af33a8810e0ed04d"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3aa46ce37da51477a1af33a8810e0ed04d">arm_compute::GPUTarget::G76</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3a4b3e9b93a7e833f9d7ab01d4cf9f7837"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a4b3e9b93a7e833f9d7ab01d4cf9f7837">arm_compute::GPUTarget::G52LIT</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a79515d904f73cf1711207de1b2aa6ac6">arm_compute::GPUTarget::G71</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel</div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a966a9c417ce5e94dca08d9b5e745c0c9aad6fddf718ad19b063e02fdd7e8e3e65"><div class="ttname"><a href="namespacearm__compute.xhtml#a966a9c417ce5e94dca08d9b5e745c0c9aad6fddf718ad19b063e02fdd7e8e3e65">arm_compute::InterpolationPolicy::BILINEAR</a></div><div class="ttdoc">Output values are defined by bilinear interpolation between the pixels.</div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3a9d0acedfece9dfaf5cc3e63bfbeecf2f"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a9d0acedfece9dfaf5cc3e63bfbeecf2f">arm_compute::GPUTarget::G51LIT</a></div></div>
<div class="ttc" id="core_2_c_l_2_c_l_helpers_8h_xhtml"><div class="ttname"><a href="core_2_c_l_2_c_l_helpers_8h.xhtml">CLHelpers.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml">arm_compute::ICLKernel</a></div><div class="ttdoc">Common interface for all the OpenCL kernels.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00043">ICLKernel.h:43</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">Copyright (c) 2017-2018 ARM Limited.</div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div>
<div class="ttc" id="_cast_8h_xhtml"><div class="ttname"><a href="_cast_8h.xhtml">Cast.h</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ae8f0126f051c787279a8c9ee3c3a5d55"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ae8f0126f051c787279a8c9ee3c3a5d55">arm_compute::test::validation::weights_shape</a></div><div class="ttdeci">weights_shape</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00160">Error.h:160</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3ab2ac2aea42c95ccc70260ceeb02ec4fc">arm_compute::GPUTarget::G72</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::DataLayout::NCHW</a></div><div class="ttdoc">Num samples, channels, height, width.</div></div>
<div class="ttc" id="_bifrost_tuner_8h_xhtml"><div class="ttname"><a href="_bifrost_tuner_8h.xhtml">BifrostTuner.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1tuners_1_1_bifrost_tuner_xhtml_af073b532560e2105dd22d381f5888ce7"><div class="ttname"><a href="classarm__compute_1_1tuners_1_1_bifrost_tuner.xhtml#af073b532560e2105dd22d381f5888ce7">arm_compute::tuners::BifrostTuner::tune_kernel_dynamic</a></div><div class="ttdeci">void tune_kernel_dynamic(ICLKernel &amp;kernel) override</div><div class="ttdoc">Tune OpenCL kernel dynamically.</div><div class="ttdef"><b>Definition:</b> <a href="_bifrost_tuner_8cpp_source.xhtml#l00336">BifrostTuner.cpp:336</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">arm_compute::GPUTarget</a></div><div class="ttdeci">GPUTarget</div><div class="ttdoc">Available GPU Targets.</div><div class="ttdef"><b>Definition:</b> <a href="_g_p_u_target_8h_source.xhtml#l00034">GPUTarget.h:34</a></div></div>
<div class="ttc" id="classarm__compute_1_1tuners_1_1_bifrost_tuner_xhtml_a52f755d664bbdcb9346cdf5cc4a7e958"><div class="ttname"><a href="classarm__compute_1_1tuners_1_1_bifrost_tuner.xhtml#a52f755d664bbdcb9346cdf5cc4a7e958">arm_compute::tuners::BifrostTuner::tune_kernel_static</a></div><div class="ttdeci">void tune_kernel_static(ICLKernel &amp;kernel) override</div><div class="ttdoc">Tune OpenCL kernel statically.</div><div class="ttdef"><b>Definition:</b> <a href="_bifrost_tuner_8cpp_source.xhtml#l00300">BifrostTuner.cpp:300</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3afc99dd3bc5650c5116886eefd3d18988"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afc99dd3bc5650c5116886eefd3d18988">arm_compute::GPUTarget::G51BIG</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">arm_compute::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdoc">Available data types.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00074">Types.h:74</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3a3731064380218cfc2b9613d2b6293cfb"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a3731064380218cfc2b9613d2b6293cfb">arm_compute::GPUTarget::G52</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a1da498e9b2c2d24883087f62c6bbe75d"><div class="ttname"><a href="namespacearm__compute.xhtml#a1da498e9b2c2d24883087f62c6bbe75d">arm_compute::gpu_target_is_in</a></div><div class="ttdeci">bool gpu_target_is_in(GPUTarget target_to_check, GPUTarget target, Args... targets)</div><div class="ttdoc">Helper function to check whether a gpu target is equal to the provided targets.</div><div class="ttdef"><b>Definition:</b> <a href="_g_p_u_target_8h_source.xhtml#l00096">GPUTarget.h:96</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3a0a2d4856ae75ec5a7b78851f6e5875f0"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3a0a2d4856ae75ec5a7b78851f6e5875f0">arm_compute::GPUTarget::G51</a></div></div>
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