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<div class="title">WarpSelectKernel.cuh</div> </div>
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<div class="contents">
<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/**</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2015-present, Facebook, Inc.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * All rights reserved.</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> *</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> * This source code is licensed under the BSD+Patents license found in the</span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * LICENSE file in the root directory of this source tree.</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment">// Copyright 2004-present Facebook. All Rights Reserved.</span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#pragma once</span></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor"></span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include "Float16.cuh"</span></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include "Select.cuh"</span></div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="keyword">namespace </span>faiss { <span class="keyword">namespace </span>gpu {</div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">template</span> <<span class="keyword">typename</span> K,</div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <span class="keyword">typename</span> IndexType,</div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <span class="keywordtype">bool</span> Dir,</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="keywordtype">int</span> NumWarpQ,</div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <span class="keywordtype">int</span> NumThreadQ,</div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="keywordtype">int</span> ThreadsPerBlock></div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span> __global__ <span class="keywordtype">void</span> warpSelect(Tensor<K, 2, true> in,</div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  Tensor<K, 2, true> outK,</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  Tensor<IndexType, 2, true> outV,</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  K initK,</div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  IndexType initV,</div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keywordtype">int</span> k) {</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  constexpr <span class="keywordtype">int</span> kNumWarps = ThreadsPerBlock / kWarpSize;</div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  WarpSelect<K, IndexType, Dir, Comparator<K>,</div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  NumWarpQ, NumThreadQ, ThreadsPerBlock></div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  heap(initK, initV, k);</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keywordtype">int</span> warpId = threadIdx.x / kWarpSize;</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keywordtype">int</span> row = blockIdx.x * kNumWarps + warpId;</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> </div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keywordflow">if</span> (row >= in.getSize(0)) {</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  }</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> </div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordtype">int</span> i = getLaneId();</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  K* inStart = in[row][i].data();</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="comment">// Whole warps must participate in the selection</span></div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordtype">int</span> limit = utils::roundDown(in.getSize(1), kWarpSize);</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span> </div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keywordflow">for</span> (; i < limit; i += kWarpSize) {</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  heap.add(*inStart, (IndexType) i);</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  inStart += kWarpSize;</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  }</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> </div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="comment">// Handle non-warp multiple remainder</span></div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">if</span> (i < in.getSize(1)) {</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  heap.addThreadQ(*inStart, (IndexType) i);</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  }</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  heap.reduce();</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  heap.writeOut(outK[row].data(),</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  outV[row].data(), k);</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span> }</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="keywordtype">void</span> runWarpSelect(Tensor<float, 2, true>& in,</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  Tensor<float, 2, true>& outKeys,</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  Tensor<int, 2, true>& outIndices,</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordtype">bool</span> dir, <span class="keywordtype">int</span> k, cudaStream_t stream);</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span> </div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="preprocessor"></span><span class="keywordtype">void</span> runWarpSelect(Tensor<half, 2, true>& in,</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  Tensor<half, 2, true>& outKeys,</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  Tensor<int, 2, true>& outIndices,</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keywordtype">bool</span> dir, <span class="keywordtype">int</span> k, cudaStream_t stream);</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="preprocessor"></span></div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span> } } <span class="comment">// namespace</span></div>
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