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| <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.html">src</a></li><li class="navelem"><a class="el" href="dir_fdedb0aba14d44ce9d99bc100e026e6a.html">common</a></li> </ul> |
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| <a href="cuda__utils_8h.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"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more contributor license agreements. See the NOTICE file</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * distributed with this work for additional information</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> * regarding copyright ownership. The ASF licenses this file</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * to you under the Apache License, Version 2.0 (the</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> * "License"); you may not use this file except in compliance</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> * with the License. You may obtain a copy of the License at</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"> * http://www.apache.org/licenses/LICENSE-2.0</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> *</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> * Unless required by applicable law or agreed to in writing,</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> * software distributed under the License is distributed on an</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> * KIND, either express or implied. See the License for the</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * specific language governing permissions and limitations</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"> * under the License.</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> */</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#ifndef MXNET_COMMON_CUDA_UTILS_H_</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#define MXNET_COMMON_CUDA_UTILS_H_</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include <dmlc/logging.h></span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include <dmlc/parameter.h></span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include <dmlc/optional.h></span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include <mshadow/base.h></span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#ifdef __JETBRAINS_IDE__</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#define __CUDACC__ 1</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="preprocessor">#define __host__</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#define __device__</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="preprocessor">#define __global__</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="preprocessor">#define __forceinline__</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#define __shared__</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> __syncthreads() {}</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> __threadfence_block() {}</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="keyword">template</span><<span class="keyword">class</span> T> <span class="keyword">inline</span> T __clz(<span class="keyword">const</span> T val) { <span class="keywordflow">return</span> val; }</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="keyword">struct </span>__cuda_fake_struct { <span class="keywordtype">int</span> x; <span class="keywordtype">int</span> y; <span class="keywordtype">int</span> z; };</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="keyword">extern</span> __cuda_fake_struct blockDim;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="keyword">extern</span> __cuda_fake_struct threadIdx;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="keyword">extern</span> __cuda_fake_struct blockIdx;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> </div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="preprocessor">#if MXNET_USE_CUDA</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="preprocessor">#include <cuda_runtime.h></span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="preprocessor">#include <cublas_v2.h></span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="preprocessor">#include <curand.h></span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> </div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="keyword">namespace </span><a class="code" href="namespacemxnet.html">mxnet</a> {</div><div class="line"><a name="l00056"></a><span class="lineno"><a class="line" href="namespacemxnet_1_1common.html"> 56</a></span> <span class="keyword">namespace </span>common {</div><div class="line"><a name="l00058"></a><span class="lineno"><a class="line" href="namespacemxnet_1_1common_1_1cuda.html"> 58</a></span> <span class="keyword">namespace </span>cuda {</div><div class="line"><a name="l00064"></a><span class="lineno"><a class="line" href="namespacemxnet_1_1common_1_1cuda.html#a9feee613a4f16a954dd68e55345a72ac"> 64</a></span> <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="namespacemxnet_1_1common_1_1cuda.html#a9feee613a4f16a954dd68e55345a72ac">CublasGetErrorString</a>(cublasStatus_t error) {</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="keywordflow">switch</span> (error) {</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="keywordflow">case</span> CUBLAS_STATUS_SUCCESS:</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUBLAS_STATUS_SUCCESS"</span>;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="keywordflow">case</span> CUBLAS_STATUS_NOT_INITIALIZED:</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUBLAS_STATUS_NOT_INITIALIZED"</span>;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="keywordflow">case</span> CUBLAS_STATUS_ALLOC_FAILED:</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUBLAS_STATUS_ALLOC_FAILED"</span>;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="keywordflow">case</span> CUBLAS_STATUS_INVALID_VALUE:</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUBLAS_STATUS_INVALID_VALUE"</span>;</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="keywordflow">case</span> CUBLAS_STATUS_ARCH_MISMATCH:</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUBLAS_STATUS_ARCH_MISMATCH"</span>;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="keywordflow">case</span> CUBLAS_STATUS_MAPPING_ERROR:</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUBLAS_STATUS_MAPPING_ERROR"</span>;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="keywordflow">case</span> CUBLAS_STATUS_EXECUTION_FAILED:</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUBLAS_STATUS_EXECUTION_FAILED"</span>;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="keywordflow">case</span> CUBLAS_STATUS_INTERNAL_ERROR:</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUBLAS_STATUS_INTERNAL_ERROR"</span>;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="keywordflow">case</span> CUBLAS_STATUS_NOT_SUPPORTED:</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUBLAS_STATUS_NOT_SUPPORTED"</span>;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="keywordflow">default</span>:</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="keywordflow">break</span>;</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> }</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="keywordflow">return</span> <span class="stringliteral">"Unknown cuBLAS status"</span>;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> }</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div><div class="line"><a name="l00095"></a><span class="lineno"><a class="line" href="namespacemxnet_1_1common_1_1cuda.html#abf9bcb4cb696e9ae61b818510dac39c8"> 95</a></span> <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="namespacemxnet_1_1common_1_1cuda.html#abf9bcb4cb696e9ae61b818510dac39c8">CusolverGetErrorString</a>(cusolverStatus_t error) {</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="keywordflow">switch</span> (error) {</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="keywordflow">case</span> CUSOLVER_STATUS_SUCCESS:</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUSOLVER_STATUS_SUCCESS"</span>;</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="keywordflow">case</span> CUSOLVER_STATUS_NOT_INITIALIZED:</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUSOLVER_STATUS_NOT_INITIALIZED"</span>;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="keywordflow">case</span> CUSOLVER_STATUS_ALLOC_FAILED:</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUSOLVER_STATUS_ALLOC_FAILED"</span>;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="keywordflow">case</span> CUSOLVER_STATUS_INVALID_VALUE:</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUSOLVER_STATUS_INVALID_VALUE"</span>;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="keywordflow">case</span> CUSOLVER_STATUS_ARCH_MISMATCH:</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUSOLVER_STATUS_ARCH_MISMATCH"</span>;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="keywordflow">case</span> CUSOLVER_STATUS_EXECUTION_FAILED:</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUSOLVER_STATUS_EXECUTION_FAILED"</span>;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="keywordflow">case</span> CUSOLVER_STATUS_INTERNAL_ERROR:</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUSOLVER_STATUS_INTERNAL_ERROR"</span>;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="keywordflow">case</span> CUSOLVER_STATUS_MATRIX_TYPE_NOT_SUPPORTED:</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="keywordflow">return</span> <span class="stringliteral">"CUSOLVER_STATUS_MATRIX_TYPE_NOT_SUPPORTED"</span>;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="keywordflow">default</span>:</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="keywordflow">break</span>;</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> }</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="keywordflow">return</span> <span class="stringliteral">"Unknown cuSOLVER status"</span>;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> }</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div><div class="line"><a name="l00124"></a><span class="lineno"><a class="line" href="namespacemxnet_1_1common_1_1cuda.html#a97c06b2f4d26445a7386b0f54fae1feb"> 124</a></span> <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="namespacemxnet_1_1common_1_1cuda.html#a97c06b2f4d26445a7386b0f54fae1feb">CurandGetErrorString</a>(curandStatus_t status) {</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="keywordflow">switch</span> (status) {</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="keywordflow">case</span> CURAND_STATUS_SUCCESS:</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_SUCCESS"</span>;</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="keywordflow">case</span> CURAND_STATUS_VERSION_MISMATCH:</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_VERSION_MISMATCH"</span>;</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="keywordflow">case</span> CURAND_STATUS_NOT_INITIALIZED:</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_NOT_INITIALIZED"</span>;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> <span class="keywordflow">case</span> CURAND_STATUS_ALLOCATION_FAILED:</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_ALLOCATION_FAILED"</span>;</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="keywordflow">case</span> CURAND_STATUS_TYPE_ERROR:</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_TYPE_ERROR"</span>;</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="keywordflow">case</span> CURAND_STATUS_OUT_OF_RANGE:</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_OUT_OF_RANGE"</span>;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="keywordflow">case</span> CURAND_STATUS_LENGTH_NOT_MULTIPLE:</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_LENGTH_NOT_MULTIPLE"</span>;</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="keywordflow">case</span> CURAND_STATUS_DOUBLE_PRECISION_REQUIRED:</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_DOUBLE_PRECISION_REQUIRED"</span>;</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="keywordflow">case</span> CURAND_STATUS_LAUNCH_FAILURE:</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_LAUNCH_FAILURE"</span>;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="keywordflow">case</span> CURAND_STATUS_PREEXISTING_FAILURE:</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_PREEXISTING_FAILURE"</span>;</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> <span class="keywordflow">case</span> CURAND_STATUS_INITIALIZATION_FAILED:</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_INITIALIZATION_FAILED"</span>;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="keywordflow">case</span> CURAND_STATUS_ARCH_MISMATCH:</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_ARCH_MISMATCH"</span>;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> <span class="keywordflow">case</span> CURAND_STATUS_INTERNAL_ERROR:</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> <span class="keywordflow">return</span> <span class="stringliteral">"CURAND_STATUS_INTERNAL_ERROR"</span>;</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> }</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> <span class="keywordflow">return</span> <span class="stringliteral">"Unknown cuRAND status"</span>;</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> }</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> </div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="keyword">template</span> <<span class="keyword">typename</span> DType></div><div class="line"><a name="l00157"></a><span class="lineno"><a class="line" href="namespacemxnet_1_1common_1_1cuda.html#a6f3ee04eb382c57e10916108db3efd80"> 157</a></span> <span class="keyword">inline</span> DType __device__ <a class="code" href="namespacemxnet_1_1common_1_1cuda.html#a6f3ee04eb382c57e10916108db3efd80">CudaMax</a>(DType a, DType b) {</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> <span class="keywordflow">return</span> a > b ? a : b;</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> }</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="keyword">template</span> <<span class="keyword">typename</span> DType></div><div class="line"><a name="l00162"></a><span class="lineno"><a class="line" href="namespacemxnet_1_1common_1_1cuda.html#a03888f252f813f6d052ae84bf8801498"> 162</a></span> <span class="keyword">inline</span> DType __device__ <a class="code" href="namespacemxnet_1_1common_1_1cuda.html#a03888f252f813f6d052ae84bf8801498">CudaMin</a>(DType a, DType b) {</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> <span class="keywordflow">return</span> a < b ? a : b;</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> }</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> </div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> } <span class="comment">// namespace cuda</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> } <span class="comment">// namespace common</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> } <span class="comment">// namespace mxnet</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> </div><div class="line"><a name="l00174"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#afc69a418242c5b851993bc2307b1c897"> 174</a></span> <span class="preprocessor">#define CHECK_CUDA_ERROR(msg) \</span></div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> <span class="preprocessor"> cudaError_t e = cudaGetLastError(); \</span></div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> <span class="preprocessor"> CHECK_EQ(e, cudaSuccess) << (msg) << " CUDA: " << cudaGetErrorString(e); \</span></div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> <span class="preprocessor"> }</span></div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div><div class="line"><a name="l00186"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#a06cc7d24ca66505e69f5ad40009f5e8d"> 186</a></span> <span class="preprocessor">#define CUDA_CALL(func) \</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> <span class="preprocessor"> cudaError_t e = (func); \</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> <span class="preprocessor"> CHECK(e == cudaSuccess || e == cudaErrorCudartUnloading) \</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> <span class="preprocessor"> << "CUDA: " << cudaGetErrorString(e); \</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> <span class="preprocessor"> }</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> </div><div class="line"><a name="l00199"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#a685d7ca3c9370ff471665abcacdeb381"> 199</a></span> <span class="preprocessor">#define CUBLAS_CALL(func) \</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> <span class="preprocessor"> cublasStatus_t e = (func); \</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> <span class="preprocessor"> CHECK_EQ(e, CUBLAS_STATUS_SUCCESS) \</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span> <span class="preprocessor"> << "cuBLAS: " << common::cuda::CublasGetErrorString(e); \</span></div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> <span class="preprocessor"> }</span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> </div><div class="line"><a name="l00212"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#ab38940ff6950f84102baa4573675b670"> 212</a></span> <span class="preprocessor">#define CUSOLVER_CALL(func) \</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> <span class="preprocessor"> cusolverStatus_t e = (func); \</span></div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> <span class="preprocessor"> CHECK_EQ(e, CUSOLVER_STATUS_SUCCESS) \</span></div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> <span class="preprocessor"> << "cuSolver: " << common::cuda::CusolverGetErrorString(e); \</span></div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> <span class="preprocessor"> }</span></div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> </div><div class="line"><a name="l00225"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#a82d7233550780a8c186e79c24aed8406"> 225</a></span> <span class="preprocessor">#define CURAND_CALL(func) \</span></div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> <span class="preprocessor"> curandStatus_t e = (func); \</span></div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> <span class="preprocessor"> CHECK_EQ(e, CURAND_STATUS_SUCCESS) \</span></div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> <span class="preprocessor"> << "cuRAND: " << common::cuda::CurandGetErrorString(e); \</span></div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> <span class="preprocessor"> }</span></div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> </div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> <span class="preprocessor">#if !defined(_MSC_VER)</span></div><div class="line"><a name="l00233"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#a685e3713856baaafb1d4edea43725c83"> 233</a></span> <span class="preprocessor">#define CUDA_UNROLL _Pragma("unroll")</span></div><div class="line"><a name="l00234"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#addb314f15d765a2ba72ae37dab23c03b"> 234</a></span> <span class="preprocessor">#define CUDA_NOUNROLL _Pragma("nounroll")</span></div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> <span class="preprocessor">#define CUDA_UNROLL</span></div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> <span class="preprocessor">#define CUDA_NOUNROLL</span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> </div><div class="line"><a name="l00245"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#aa79f548df23452162de37663f171e99d"> 245</a></span> <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="cuda__utils_8h.html#aa79f548df23452162de37663f171e99d">ComputeCapabilityMajor</a>(<span class="keywordtype">int</span> device_id) {</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> <span class="keywordtype">int</span> major = 0;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> <a class="code" href="cuda__utils_8h.html#a06cc7d24ca66505e69f5ad40009f5e8d">CUDA_CALL</a>(cudaDeviceGetAttribute(&major,</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> cudaDevAttrComputeCapabilityMajor, device_id));</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> <span class="keywordflow">return</span> major;</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> }</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> </div><div class="line"><a name="l00257"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#a7c16e8770e4f399cabed1fc231ffd9b6"> 257</a></span> <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="cuda__utils_8h.html#a7c16e8770e4f399cabed1fc231ffd9b6">ComputeCapabilityMinor</a>(<span class="keywordtype">int</span> device_id) {</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> <span class="keywordtype">int</span> minor = 0;</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> <a class="code" href="cuda__utils_8h.html#a06cc7d24ca66505e69f5ad40009f5e8d">CUDA_CALL</a>(cudaDeviceGetAttribute(&minor,</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> cudaDevAttrComputeCapabilityMinor, device_id));</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> <span class="keywordflow">return</span> minor;</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span> }</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> </div><div class="line"><a name="l00269"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#a9779e3ad0efd0faec7fbe431c0db896d"> 269</a></span> <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="cuda__utils_8h.html#a9779e3ad0efd0faec7fbe431c0db896d">SMArch</a>(<span class="keywordtype">int</span> device_id) {</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span> <span class="keyword">auto</span> major = <a class="code" href="cuda__utils_8h.html#aa79f548df23452162de37663f171e99d">ComputeCapabilityMajor</a>(device_id);</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> <span class="keyword">auto</span> minor = <a class="code" href="cuda__utils_8h.html#a7c16e8770e4f399cabed1fc231ffd9b6">ComputeCapabilityMinor</a>(device_id);</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> <span class="keywordflow">return</span> 10 * major + minor;</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> }</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> </div><div class="line"><a name="l00280"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#afb4268417c1d8886a39142c85c8f188f"> 280</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="cuda__utils_8h.html#afb4268417c1d8886a39142c85c8f188f">SupportsFloat16Compute</a>(<span class="keywordtype">int</span> device_id) {</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> <span class="comment">// Kepler and most Maxwell GPUs do not support fp16 compute</span></div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> <span class="keywordtype">int</span> computeCapabilityMajor = <a class="code" href="cuda__utils_8h.html#aa79f548df23452162de37663f171e99d">ComputeCapabilityMajor</a>(device_id);</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span> <span class="keywordtype">int</span> computeCapabilityMinor = <a class="code" href="cuda__utils_8h.html#a7c16e8770e4f399cabed1fc231ffd9b6">ComputeCapabilityMinor</a>(device_id);</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> <span class="keywordflow">return</span> (computeCapabilityMajor > 5) ||</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> (computeCapabilityMajor == 5 && computeCapabilityMinor >= 3);</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> }</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> </div><div class="line"><a name="l00293"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#af7e22ce6d80d61e8ca37df23880ff1a9"> 293</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="cuda__utils_8h.html#af7e22ce6d80d61e8ca37df23880ff1a9">SupportsTensorCore</a>(<span class="keywordtype">int</span> device_id) {</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> <span class="comment">// Volta (sm_70) supports TensorCore algos</span></div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> <span class="keywordtype">int</span> computeCapabilityMajor = <a class="code" href="cuda__utils_8h.html#aa79f548df23452162de37663f171e99d">ComputeCapabilityMajor</a>(device_id);</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span> <span class="keywordflow">return</span> (computeCapabilityMajor >= 7);</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> }</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> <span class="comment">// The policy if the user hasn't set the environment variable MXNET_CUDA_ALLOW_TENSOR_CORE</span></div><div class="line"><a name="l00300"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#aa7ba00b841d6b7ba443b0e58dac9ab88"> 300</a></span> <span class="preprocessor">#define MXNET_CUDA_ALLOW_TENSOR_CORE_DEFAULT true</span></div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> </div><div class="line"><a name="l00306"></a><span class="lineno"><a class="line" href="cuda__utils_8h.html#a464dee13053e3b0b1006c6307069196c"> 306</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="cuda__utils_8h.html#a464dee13053e3b0b1006c6307069196c">GetEnvAllowTensorCore</a>() {</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> <span class="comment">// Use of optional<bool> here permits: "0", "1", "true" and "false" to all be legal.</span></div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="keywordtype">bool</span> default_value = <a class="code" href="cuda__utils_8h.html#aa7ba00b841d6b7ba443b0e58dac9ab88">MXNET_CUDA_ALLOW_TENSOR_CORE_DEFAULT</a>;</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> <span class="keywordflow">return</span> dmlc::GetEnv(<span class="stringliteral">"MXNET_CUDA_ALLOW_TENSOR_CORE"</span>,</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> dmlc::optional<bool>(default_value)).value();</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> }</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> <span class="preprocessor">#endif // MXNET_USE_CUDA</span></div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span> </div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> <span class="preprocessor">#if MXNET_USE_CUDNN</span></div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> </div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> <span class="preprocessor">#include <cudnn.h></span></div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> </div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="preprocessor">#define CUDNN_CALL(func) \</span></div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> <span class="preprocessor"> { \</span></div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> <span class="preprocessor"> cudnnStatus_t e = (func); \</span></div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> <span class="preprocessor"> CHECK_EQ(e, CUDNN_STATUS_SUCCESS) << "cuDNN: " << cudnnGetErrorString(e); \</span></div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span> <span class="preprocessor"> }</span></div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> </div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> <span class="keyword">inline</span> <span class="keywordtype">int</span> MaxForwardAlgos(cudnnHandle_t cudnn_handle) {</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> <span class="preprocessor">#if CUDNN_MAJOR >= 7</span></div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span> <span class="keywordtype">int</span> max_algos = 0;</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> CUDNN_CALL(cudnnGetConvolutionForwardAlgorithmMaxCount(cudnn_handle, &max_algos));</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span> <span class="keywordflow">return</span> max_algos;</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> <span class="keywordflow">return</span> 10;</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> }</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span> </div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span> <span class="keyword">inline</span> <span class="keywordtype">int</span> MaxBackwardFilterAlgos(cudnnHandle_t cudnn_handle) {</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> <span class="preprocessor">#if CUDNN_MAJOR >= 7</span></div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span> <span class="keywordtype">int</span> max_algos = 0;</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> CUDNN_CALL(cudnnGetConvolutionBackwardFilterAlgorithmMaxCount(cudnn_handle, &max_algos));</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span> <span class="keywordflow">return</span> max_algos;</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span> <span class="keywordflow">return</span> 10;</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> }</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span> </div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span> <span class="keyword">inline</span> <span class="keywordtype">int</span> MaxBackwardDataAlgos(cudnnHandle_t cudnn_handle) {</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span> <span class="preprocessor">#if CUDNN_MAJOR >= 7</span></div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span> <span class="keywordtype">int</span> max_algos = 0;</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> CUDNN_CALL(cudnnGetConvolutionBackwardDataAlgorithmMaxCount(cudnn_handle, &max_algos));</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span> <span class="keywordflow">return</span> max_algos;</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span> <span class="keywordflow">return</span> 10;</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> }</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span> </div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span> <span class="preprocessor">#endif // MXNET_USE_CUDNN</span></div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span> </div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> <span class="comment">// Overload atomicAdd to work for floats on all architectures</span></div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> <span class="preprocessor">#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ < 600</span></div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> <span class="comment">// From CUDA Programming Guide</span></div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> <span class="keyword">static</span> <span class="keyword">inline</span> __device__ <span class="keywordtype">void</span> atomicAdd(<span class="keywordtype">double</span> *address, <span class="keywordtype">double</span> val) {</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">long</span> <span class="keywordtype">long</span>* address_as_ull = <span class="comment">// NOLINT(*)</span></div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> <span class="keyword">reinterpret_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">long</span> <span class="keywordtype">long</span>*<span class="keyword">></span>(address); <span class="comment">// NOLINT(*)</span></div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">long</span> <span class="keywordtype">long</span> old = *address_as_ull; <span class="comment">// NOLINT(*)</span></div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">long</span> <span class="keywordtype">long</span> assumed; <span class="comment">// NOLINT(*)</span></div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> </div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span> <span class="keywordflow">do</span> {</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> assumed = old;</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span> old = atomicCAS(address_as_ull, assumed,</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span> __double_as_longlong(val +</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span> __longlong_as_double(assumed)));</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> </div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span> <span class="comment">// Note: uses integer comparison to avoid hang in case of NaN (since NaN != NaN)</span></div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> } <span class="keywordflow">while</span> (assumed != old);</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span> }</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span> </div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span> <span class="comment">// Overload atomicAdd for half precision</span></div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span> <span class="comment">// Taken from:</span></div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span> <span class="comment">// https://github.com/torch/cutorch/blob/master/lib/THC/THCAtomics.cuh</span></div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span> <span class="preprocessor">#if defined(__CUDA_ARCH__)</span></div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> <span class="keyword">static</span> <span class="keyword">inline</span> __device__ <span class="keywordtype">void</span> atomicAdd(mshadow::half::half_t *address,</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span> mshadow::half::half_t val) {</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *address_as_ui =</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span> <span class="keyword">reinterpret_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *<span class="keyword">></span>(<span class="keyword">reinterpret_cast<</span><span class="keywordtype">char</span> *<span class="keyword">></span>(address) -</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span> (reinterpret_cast<size_t>(address) & 2));</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> old = *address_as_ui;</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> assumed;</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span> </div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span> <span class="keywordflow">do</span> {</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span> assumed = old;</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span> mshadow::half::half_t hsum;</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span> hsum.half_ =</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span> <span class="keyword">reinterpret_cast<</span><span class="keywordtype">size_t</span><span class="keyword">></span>(address) & 2 ? (old >> 16) : (old & 0xffff);</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span> hsum += val;</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span> old = <span class="keyword">reinterpret_cast<</span><span class="keywordtype">size_t</span><span class="keyword">></span>(address) & 2</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span> ? (old & 0xffff) | (hsum.half_ << 16)</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span> : (old & 0xffff0000) | hsum.half_;</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span> old = atomicCAS(address_as_ui, assumed, old);</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span> } <span class="keywordflow">while</span> (assumed != old);</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span> }</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span> </div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span> <span class="keyword">template</span> <<span class="keyword">typename</span> DType></div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span> __device__ <span class="keyword">inline</span> DType ldg(<span class="keyword">const</span> DType* address) {</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span> <span class="preprocessor">#if __CUDA_ARCH__ >= 350</span></div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span> <span class="keywordflow">return</span> __ldg(address);</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span> <span class="keywordflow">return</span> *address;</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span> }</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span> </div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span> <span class="preprocessor">#endif // MXNET_COMMON_CUDA_UTILS_H_</span></div><div class="ttc" id="cuda__utils_8h_html_aa79f548df23452162de37663f171e99d"><div class="ttname"><a href="cuda__utils_8h.html#aa79f548df23452162de37663f171e99d">ComputeCapabilityMajor</a></div><div class="ttdeci">int ComputeCapabilityMajor(int device_id)</div><div class="ttdoc">Determine major version number of the gpu&#39;s cuda compute architecture. </div><div class="ttdef"><b>Definition:</b> cuda_utils.h:245</div></div> |
| <div class="ttc" id="namespacemxnet_html"><div class="ttname"><a href="namespacemxnet.html">mxnet</a></div><div class="ttdoc">namespace of mxnet </div><div class="ttdef"><b>Definition:</b> base.h:126</div></div> |
| <div class="ttc" id="cuda__utils_8h_html_a464dee13053e3b0b1006c6307069196c"><div class="ttname"><a href="cuda__utils_8h.html#a464dee13053e3b0b1006c6307069196c">GetEnvAllowTensorCore</a></div><div class="ttdeci">bool GetEnvAllowTensorCore()</div><div class="ttdoc">Returns global policy for TensorCore algo use. </div><div class="ttdef"><b>Definition:</b> cuda_utils.h:306</div></div> |
| <div class="ttc" id="cuda__utils_8h_html_a9779e3ad0efd0faec7fbe431c0db896d"><div class="ttname"><a href="cuda__utils_8h.html#a9779e3ad0efd0faec7fbe431c0db896d">SMArch</a></div><div class="ttdeci">int SMArch(int device_id)</div><div class="ttdoc">Return the integer SM architecture (e.g. Volta = 70). </div><div class="ttdef"><b>Definition:</b> cuda_utils.h:269</div></div> |
| <div class="ttc" id="namespacemxnet_1_1common_1_1cuda_html_a03888f252f813f6d052ae84bf8801498"><div class="ttname"><a href="namespacemxnet_1_1common_1_1cuda.html#a03888f252f813f6d052ae84bf8801498">mxnet::common::cuda::CudaMin</a></div><div class="ttdeci">DType __device__ CudaMin(DType a, DType b)</div><div class="ttdef"><b>Definition:</b> cuda_utils.h:162</div></div> |
| <div class="ttc" id="cuda__utils_8h_html_afb4268417c1d8886a39142c85c8f188f"><div class="ttname"><a href="cuda__utils_8h.html#afb4268417c1d8886a39142c85c8f188f">SupportsFloat16Compute</a></div><div class="ttdeci">bool SupportsFloat16Compute(int device_id)</div><div class="ttdoc">Determine whether a cuda-capable gpu&#39;s architecture supports float16 math. </div><div class="ttdef"><b>Definition:</b> cuda_utils.h:280</div></div> |
| <div class="ttc" id="namespacemxnet_1_1common_1_1cuda_html_a6f3ee04eb382c57e10916108db3efd80"><div class="ttname"><a href="namespacemxnet_1_1common_1_1cuda.html#a6f3ee04eb382c57e10916108db3efd80">mxnet::common::cuda::CudaMax</a></div><div class="ttdeci">DType __device__ CudaMax(DType a, DType b)</div><div class="ttdef"><b>Definition:</b> cuda_utils.h:157</div></div> |
| <div class="ttc" id="cuda__utils_8h_html_af7e22ce6d80d61e8ca37df23880ff1a9"><div class="ttname"><a href="cuda__utils_8h.html#af7e22ce6d80d61e8ca37df23880ff1a9">SupportsTensorCore</a></div><div class="ttdeci">bool SupportsTensorCore(int device_id)</div><div class="ttdoc">Determine whether a cuda-capable gpu&#39;s architecture supports Tensor Core math. </div><div class="ttdef"><b>Definition:</b> cuda_utils.h:293</div></div> |
| <div class="ttc" id="namespacemxnet_1_1common_1_1cuda_html_abf9bcb4cb696e9ae61b818510dac39c8"><div class="ttname"><a href="namespacemxnet_1_1common_1_1cuda.html#abf9bcb4cb696e9ae61b818510dac39c8">mxnet::common::cuda::CusolverGetErrorString</a></div><div class="ttdeci">const char * CusolverGetErrorString(cusolverStatus_t error)</div><div class="ttdoc">Get string representation of cuSOLVER errors. </div><div class="ttdef"><b>Definition:</b> cuda_utils.h:95</div></div> |
| <div class="ttc" id="cuda__utils_8h_html_aa7ba00b841d6b7ba443b0e58dac9ab88"><div class="ttname"><a href="cuda__utils_8h.html#aa7ba00b841d6b7ba443b0e58dac9ab88">MXNET_CUDA_ALLOW_TENSOR_CORE_DEFAULT</a></div><div class="ttdeci">#define MXNET_CUDA_ALLOW_TENSOR_CORE_DEFAULT</div><div class="ttdef"><b>Definition:</b> cuda_utils.h:300</div></div> |
| <div class="ttc" id="namespacemxnet_1_1common_1_1cuda_html_a97c06b2f4d26445a7386b0f54fae1feb"><div class="ttname"><a href="namespacemxnet_1_1common_1_1cuda.html#a97c06b2f4d26445a7386b0f54fae1feb">mxnet::common::cuda::CurandGetErrorString</a></div><div class="ttdeci">const char * CurandGetErrorString(curandStatus_t status)</div><div class="ttdoc">Get string representation of cuRAND errors. </div><div class="ttdef"><b>Definition:</b> cuda_utils.h:124</div></div> |
| <div class="ttc" id="cuda__utils_8h_html_a7c16e8770e4f399cabed1fc231ffd9b6"><div class="ttname"><a href="cuda__utils_8h.html#a7c16e8770e4f399cabed1fc231ffd9b6">ComputeCapabilityMinor</a></div><div class="ttdeci">int ComputeCapabilityMinor(int device_id)</div><div class="ttdoc">Determine minor version number of the gpu&#39;s cuda compute architecture. </div><div class="ttdef"><b>Definition:</b> cuda_utils.h:257</div></div> |
| <div class="ttc" id="cuda__utils_8h_html_a06cc7d24ca66505e69f5ad40009f5e8d"><div class="ttname"><a href="cuda__utils_8h.html#a06cc7d24ca66505e69f5ad40009f5e8d">CUDA_CALL</a></div><div class="ttdeci">#define CUDA_CALL(func)</div><div class="ttdoc">Protected CUDA call. </div><div class="ttdef"><b>Definition:</b> cuda_utils.h:186</div></div> |
| <div class="ttc" id="namespacemxnet_1_1common_1_1cuda_html_a9feee613a4f16a954dd68e55345a72ac"><div class="ttname"><a href="namespacemxnet_1_1common_1_1cuda.html#a9feee613a4f16a954dd68e55345a72ac">mxnet::common::cuda::CublasGetErrorString</a></div><div class="ttdeci">const char * CublasGetErrorString(cublasStatus_t error)</div><div class="ttdoc">Get string representation of cuBLAS errors. </div><div class="ttdef"><b>Definition:</b> cuda_utils.h:64</div></div> |
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