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0df3f646fc
various bugfixes from github issues kmean with some frozen centroids GPU better tiling for large flat datasets default AVX for vector ops
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517 lines
79 KiB
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<li class="navelem"><a class="el" href="dir_6b3ae6988449b0834e9596fad5d75199.html">gpu</a></li><li class="navelem"><a class="el" href="dir_49d1182a3b8dfb62757c53ae905481ad.html">impl</a></li> </ul>
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<div class="title">IVFFlat.cu</div> </div>
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<div class="contents">
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/**</span></div>
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<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2015-present, Facebook, Inc.</span></div>
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<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * All rights reserved.</span></div>
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<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> *</span></div>
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<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>
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<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>
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<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> */</span></div>
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<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div>
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<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment">// Copyright 2004-present Facebook. All Rights Reserved.</span></div>
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<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div>
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<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include "IVFFlat.cuh"</span></div>
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<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include "../GpuResources.h"</span></div>
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<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include "FlatIndex.cuh"</span></div>
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<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include "InvertedListAppend.cuh"</span></div>
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<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include "IVFFlatScan.cuh"</span></div>
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<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include "RemapIndices.h"</span></div>
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<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include "../utils/CopyUtils.cuh"</span></div>
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<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include "../utils/DeviceDefs.cuh"</span></div>
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<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include "../utils/DeviceUtils.h"</span></div>
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<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include "../utils/Float16.cuh"</span></div>
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<div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include "../utils/HostTensor.cuh"</span></div>
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<div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="preprocessor">#include "../utils/Transpose.cuh"</span></div>
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<div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="preprocessor">#include <limits></span></div>
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<div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include <thrust/host_vector.h></span></div>
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<div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include <unordered_map></span></div>
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<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div>
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<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="keyword">namespace </span>faiss { <span class="keyword">namespace </span>gpu {</div>
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<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div>
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<div class="line"><a name="l00029"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFFlat.html#a7ae83f107abf31feeb78cd5633806e5d"> 29</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFFlat.html#a7ae83f107abf31feeb78cd5633806e5d">IVFFlat::IVFFlat</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html">GpuResources</a>* resources,</div>
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<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html">FlatIndex</a>* quantizer,</div>
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<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keywordtype">bool</span> l2Distance,</div>
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<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keywordtype">bool</span> useFloat16,</div>
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<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  IndicesOptions indicesOptions,</div>
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<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  MemorySpace space) :</div>
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<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html">IVFBase</a>(resources,</div>
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<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  quantizer,</div>
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<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> #ifdef FAISS_USE_FLOAT16</div>
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<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  useFloat16 ?</div>
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<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  sizeof(half) * quantizer->getDim()</div>
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<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  : sizeof(float) * quantizer->getDim(),</div>
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<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> #else</div>
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<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  sizeof(float) * quantizer->getDim(),</div>
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<div class="line"><a name="l00043"></a><span class="lineno"> 43</span> #endif</div>
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<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  indicesOptions,</div>
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<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  space),</div>
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<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  l2Distance_(l2Distance),</div>
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<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  useFloat16_(useFloat16) {</div>
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<div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="preprocessor">#ifndef FAISS_USE_FLOAT16</span></div>
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<div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="preprocessor"></span> FAISS_ASSERT_MSG(!useFloat16, <span class="stringliteral">"float16 unsupported"</span>);</div>
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<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  useFloat16_ = <span class="keyword">false</span>;</div>
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<div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="preprocessor">#endif</span></div>
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<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="preprocessor"></span>}</div>
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<div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div>
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<div class="line"><a name="l00054"></a><span class="lineno"> 54</span> IVFFlat::~IVFFlat() {</div>
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<div class="line"><a name="l00055"></a><span class="lineno"> 55</span> }</div>
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<div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div>
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<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00058"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFFlat.html#a0bedde6dcb7c2f10f277461b97486f52"> 58</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFFlat.html#a0bedde6dcb7c2f10f277461b97486f52">IVFFlat::addCodeVectorsFromCpu</a>(<span class="keywordtype">int</span> listId,</div>
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<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">const</span> <span class="keywordtype">float</span>* vecs,</div>
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<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keyword">const</span> <span class="keywordtype">long</span>* indices,</div>
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<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordtype">size_t</span> numVecs) {</div>
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<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="comment">// This list must already exist</span></div>
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<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  FAISS_ASSERT(listId < <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">deviceListData_</a>.size());</div>
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<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keyword">auto</span> stream = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>();</div>
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<div class="line"><a name="l00065"></a><span class="lineno"> 65</span> </div>
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<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="comment">// If there's nothing to add, then there's nothing we have to do</span></div>
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<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keywordflow">if</span> (numVecs == 0) {</div>
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<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keywordflow">return</span>;</div>
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<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  }</div>
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<div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div>
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<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordtype">size_t</span> lengthInBytes = numVecs * <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>;</div>
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<div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div>
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<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keyword">auto</span>& listData = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">deviceListData_</a>[listId];</div>
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<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">auto</span> prevData = listData->data();</div>
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<div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div>
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<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="comment">// We only have int32 length representations on the GPU per each</span></div>
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<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="comment">// list; the length is in sizeof(char)</span></div>
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<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  FAISS_ASSERT(listData->size() + lengthInBytes <=</div>
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<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  (size_t) std::numeric_limits<int>::max());</div>
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<div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div>
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<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordflow">if</span> (useFloat16_) {</div>
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<div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
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<div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="preprocessor"></span> <span class="comment">// We have to convert data to the half format.</span></div>
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<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="comment">// Make sure the source data is on our device first; it is not</span></div>
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<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="comment">// guaranteed before function entry to avoid unnecessary h2d copies</span></div>
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<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keyword">auto</span> floatData =</div>
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<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  toDevice<float, 1>(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>,</div>
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<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  getCurrentDevice(),</div>
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<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  (<span class="keywordtype">float</span>*) vecs,</div>
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<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  stream,</div>
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<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  {(int) numVecs * <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#aba3e3cfa469e5187f2d553fff10e0250">dim_</a>});</div>
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<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keyword">auto</span> halfData = toHalf<1>(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>, stream, floatData);</div>
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<div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div>
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<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  listData->append((<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>*) halfData.data(),</div>
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<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  lengthInBytes,</div>
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<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  stream,</div>
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<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keyword">true</span> <span class="comment">/* exact reserved size */</span>);</div>
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<div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="preprocessor">#endif</span></div>
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<div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="preprocessor"></span> } <span class="keywordflow">else</span> {</div>
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<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  listData->append((<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>*) vecs,</div>
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<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  lengthInBytes,</div>
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<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  stream,</div>
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<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keyword">true</span> <span class="comment">/* exact reserved size */</span>);</div>
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<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  }</div>
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<div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div>
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<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="comment">// Handle the indices as well</span></div>
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<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a5027720549de98f4e609d6339099df35">addIndicesFromCpu_</a>(listId, indices, numVecs);</div>
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<div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div>
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<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="comment">// This list address may have changed due to vector resizing, but</span></div>
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<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="comment">// only bother updating it on the device if it has changed</span></div>
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<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keywordflow">if</span> (prevData != listData->data()) {</div>
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|
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a96240a08b42bd1913e2286d7d514fc56">deviceListDataPointers_</a>[listId] = listData->data();</div>
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<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  }</div>
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<div class="line"><a name="l00114"></a><span class="lineno"> 114</span> </div>
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<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="comment">// And our size has changed too</span></div>
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<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keywordtype">int</span> listLength = listData->size() / <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>;</div>
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<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a3a1c2031a4763f7d55bc8a400c63af66">deviceListLengths_</a>[listId] = listLength;</div>
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<div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div>
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<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="comment">// We update this as well, since the multi-pass algorithm uses it</span></div>
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<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">maxListLength_</a> = std::max(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">maxListLength_</a>, listLength);</div>
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<div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div>
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<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="comment">// device_vector add is potentially happening on a different stream</span></div>
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|
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="comment">// than our default stream</span></div>
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<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keywordflow">if</span> (stream != 0) {</div>
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<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  streamWait({stream}, {0});</div>
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<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  }</div>
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<div class="line"><a name="l00127"></a><span class="lineno"> 127</span> }</div>
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<div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div>
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<div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="keywordtype">int</span></div>
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<div class="line"><a name="l00130"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFFlat.html#af20f96b6ad754664796c8a4e7f83ed3a"> 130</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFFlat.html#af20f96b6ad754664796c8a4e7f83ed3a">IVFFlat::classifyAndAddVectors</a>(<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& vecs,</div>
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<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<long, 1, true></a>& indices) {</div>
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<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  FAISS_ASSERT(vecs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0) == indices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0));</div>
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<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  FAISS_ASSERT(vecs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(1) == <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#aba3e3cfa469e5187f2d553fff10e0250">dim_</a>);</div>
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|
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div>
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|
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keyword">auto</span>& mem = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a1dda2dc3db1bd62cde6657c5cdbfb6e1">getMemoryManagerCurrentDevice</a>();</div>
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|
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keyword">auto</span> stream = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>();</div>
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|
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span> </div>
|
|
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="comment">// Number of valid vectors that we actually add; we return this</span></div>
|
|
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keywordtype">int</span> numAdded = 0;</div>
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|
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div>
|
|
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="comment">// We don't actually need this</span></div>
|
|
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 2, true></a> listDistance(mem, {vecs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), 1}, stream);</div>
|
|
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="comment">// We use this</span></div>
|
|
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<int, 2, true></a> listIds2d(mem, {vecs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), 1}, stream);</div>
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|
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="keyword">auto</span> listIds = listIds2d.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a74dbc09519c9c14479b2d18f2e5042e8">view</a><1>({vecs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0)});</div>
|
|
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span> </div>
|
|
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">quantizer_</a>->query(vecs, 1, listDistance, listIds2d, <span class="keyword">false</span>);</div>
|
|
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div>
|
|
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="comment">// Copy the lists that we wish to append to back to the CPU</span></div>
|
|
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="comment">// FIXME: really this can be into pinned memory and a true async</span></div>
|
|
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="comment">// copy on a different stream; we can start the copy early, but it's</span></div>
|
|
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="comment">// tiny</span></div>
|
|
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<int, 1, true></a> listIdsHost(listIds, stream);</div>
|
|
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span> </div>
|
|
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="comment">// Now we add the encoded vectors to the individual lists</span></div>
|
|
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="comment">// First, make sure that there is space available for adding the new</span></div>
|
|
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="comment">// encoded vectors and indices</span></div>
|
|
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span> </div>
|
|
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="comment">// list id -> # being added</span></div>
|
|
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  std::unordered_map<int, int> assignCounts;</div>
|
|
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span> </div>
|
|
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="comment">// vector id -> offset in list</span></div>
|
|
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="comment">// (we already have vector id -> list id in listIds)</span></div>
|
|
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<int, 1, true></a> listOffsetHost({listIdsHost.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0)});</div>
|
|
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span> </div>
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<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < listIds.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0); ++i) {</div>
|
|
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keywordtype">int</span> listId = listIdsHost[i];</div>
|
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<div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div>
|
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<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="comment">// Add vector could be invalid (contains NaNs etc)</span></div>
|
|
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="keywordflow">if</span> (listId < 0) {</div>
|
|
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  listOffsetHost[i] = -1;</div>
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|
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keywordflow">continue</span>;</div>
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<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  }</div>
|
|
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span> </div>
|
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<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  FAISS_ASSERT(listId < <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#accc4d96c14643e5f471220cb1e92ac70">numLists_</a>);</div>
|
|
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  ++numAdded;</div>
|
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<div class="line"><a name="l00177"></a><span class="lineno"> 177</span> </div>
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<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keywordtype">int</span> offset = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">deviceListData_</a>[listId]->size() / <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>;</div>
|
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<div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div>
|
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<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keyword">auto</span> it = assignCounts.find(listId);</div>
|
|
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keywordflow">if</span> (it != assignCounts.end()) {</div>
|
|
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  offset += it->second;</div>
|
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<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  it->second++;</div>
|
|
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  } <span class="keywordflow">else</span> {</div>
|
|
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  assignCounts[listId] = 1;</div>
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<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  }</div>
|
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<div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div>
|
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<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  listOffsetHost[i] = offset;</div>
|
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<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  }</div>
|
|
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span> </div>
|
|
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="comment">// If we didn't add anything (all invalid vectors), no need to</span></div>
|
|
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="comment">// continue</span></div>
|
|
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="keywordflow">if</span> (numAdded == 0) {</div>
|
|
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="keywordflow">return</span> 0;</div>
|
|
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  }</div>
|
|
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div>
|
|
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="comment">// We need to resize the data structures for the inverted lists on</span></div>
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<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="comment">// the GPUs, which means that they might need reallocation, which</span></div>
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|
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="comment">// means that their base address may change. Figure out the new base</span></div>
|
|
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="comment">// addresses, and update those in a batch on the device</span></div>
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<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  {</div>
|
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<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& counts : assignCounts) {</div>
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|
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keyword">auto</span>& data = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">deviceListData_</a>[counts.first];</div>
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<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  data->resize(data->size() + counts.second * <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>,</div>
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<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  stream);</div>
|
|
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keywordtype">int</span> newNumVecs = (int) (data->size() / <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>);</div>
|
|
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span> </div>
|
|
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keyword">auto</span>& indices = deviceListIndices_[counts.first];</div>
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|
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keywordflow">if</span> ((<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_32_BIT) ||</div>
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<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  (<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_64_BIT)) {</div>
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<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="keywordtype">size_t</span> indexSize =</div>
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|
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  (<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_32_BIT) ? <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>) : <span class="keyword">sizeof</span>(long);</div>
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<div class="line"><a name="l00213"></a><span class="lineno"> 213</span> </div>
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<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  indices->resize(indices->size() + counts.second * indexSize, stream);</div>
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|
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_CPU) {</div>
|
|
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="comment">// indices are stored on the CPU side</span></div>
|
|
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  FAISS_ASSERT(counts.first < <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a53f3c382a79b7f89630a85dfbc3a1fed">listOffsetToUserIndex_</a>.size());</div>
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<div class="line"><a name="l00218"></a><span class="lineno"> 218</span> </div>
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<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keyword">auto</span>& userIndices = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a53f3c382a79b7f89630a85dfbc3a1fed">listOffsetToUserIndex_</a>[counts.first];</div>
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<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  userIndices.resize(newNumVecs);</div>
|
|
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  } <span class="keywordflow">else</span> {</div>
|
|
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <span class="comment">// indices are not stored on the GPU or CPU side</span></div>
|
|
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  FAISS_ASSERT(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_IVF);</div>
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|
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  }</div>
|
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<div class="line"><a name="l00225"></a><span class="lineno"> 225</span> </div>
|
|
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <span class="comment">// This is used by the multi-pass query to decide how much scratch</span></div>
|
|
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="comment">// space to allocate for intermediate results</span></div>
|
|
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">maxListLength_</a> = std::max(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">maxListLength_</a>, newNumVecs);</div>
|
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<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  }</div>
|
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<div class="line"><a name="l00230"></a><span class="lineno"> 230</span> </div>
|
|
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="comment">// Update all pointers to the lists on the device that may have</span></div>
|
|
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="comment">// changed</span></div>
|
|
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  {</div>
|
|
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  std::vector<int> listIds(assignCounts.size());</div>
|
|
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keywordtype">int</span> i = 0;</div>
|
|
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& counts : assignCounts) {</div>
|
|
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  listIds[i++] = counts.first;</div>
|
|
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  }</div>
|
|
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span> </div>
|
|
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#acc695610c9513952b8d234dc0db78e5c">updateDeviceListInfo_</a>(listIds, stream);</div>
|
|
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  }</div>
|
|
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  }</div>
|
|
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span> </div>
|
|
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <span class="comment">// If we're maintaining the indices on the CPU side, update our</span></div>
|
|
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <span class="comment">// map. We already resized our map above.</span></div>
|
|
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="keywordflow">if</span> (<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_CPU) {</div>
|
|
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="comment">// We need to maintain the indices on the CPU side</span></div>
|
|
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<long, 1, true></a> hostIndices(indices, stream);</div>
|
|
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div>
|
|
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < hostIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0); ++i) {</div>
|
|
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="keywordtype">int</span> listId = listIdsHost[i];</div>
|
|
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span> </div>
|
|
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="comment">// Add vector could be invalid (contains NaNs etc)</span></div>
|
|
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keywordflow">if</span> (listId < 0) {</div>
|
|
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keywordflow">continue</span>;</div>
|
|
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  }</div>
|
|
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span> </div>
|
|
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keywordtype">int</span> offset = listOffsetHost[i];</div>
|
|
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span> </div>
|
|
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  FAISS_ASSERT(listId < <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a53f3c382a79b7f89630a85dfbc3a1fed">listOffsetToUserIndex_</a>.size());</div>
|
|
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keyword">auto</span>& userIndices = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a53f3c382a79b7f89630a85dfbc3a1fed">listOffsetToUserIndex_</a>[listId];</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>  FAISS_ASSERT(offset < userIndices.size());</div>
|
|
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  userIndices[offset] = hostIndices[i];</div>
|
|
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  }</div>
|
|
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  }</div>
|
|
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span> </div>
|
|
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <span class="comment">// We similarly need to actually append the new vectors</span></div>
|
|
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  {</div>
|
|
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<int, 1, true></a> listOffset(mem, listOffsetHost, stream);</div>
|
|
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span> </div>
|
|
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="comment">// Now, for each list to which a vector is being assigned, write it</span></div>
|
|
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  runIVFFlatInvertedListAppend(listIds,</div>
|
|
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  listOffset,</div>
|
|
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  vecs,</div>
|
|
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  indices,</div>
|
|
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  useFloat16_,</div>
|
|
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a96240a08b42bd1913e2286d7d514fc56">deviceListDataPointers_</a>,</div>
|
|
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a9aedcf0e6a20b908980ae96d73461f4c">deviceListIndexPointers_</a>,</div>
|
|
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a>,</div>
|
|
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  stream);</div>
|
|
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  }</div>
|
|
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span> </div>
|
|
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <span class="keywordflow">return</span> numAdded;</div>
|
|
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span> }</div>
|
|
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div>
|
|
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00288"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFFlat.html#a6652ca90a8a30512104fc909f0a0a6b8"> 288</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFFlat.html#a6652ca90a8a30512104fc909f0a0a6b8">IVFFlat::query</a>(<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& queries,</div>
|
|
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keywordtype">int</span> nprobe,</div>
|
|
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <span class="keywordtype">int</span> k,</div>
|
|
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& outDistances,</div>
|
|
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<long, 2, true></a>& outIndices) {</div>
|
|
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keyword">auto</span>& mem = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a1dda2dc3db1bd62cde6657c5cdbfb6e1">getMemoryManagerCurrentDevice</a>();</div>
|
|
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keyword">auto</span> stream = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>();</div>
|
|
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span> </div>
|
|
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <span class="comment">// Validate these at a top level</span></div>
|
|
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  FAISS_ASSERT(nprobe <= 1024);</div>
|
|
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  FAISS_ASSERT(k <= 1024);</div>
|
|
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  nprobe = std::min(nprobe, <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">quantizer_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a6988df17792dae30f24cc859728777e6">getSize</a>());</div>
|
|
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span> </div>
|
|
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  FAISS_ASSERT(queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(1) == <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#aba3e3cfa469e5187f2d553fff10e0250">dim_</a>);</div>
|
|
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span> </div>
|
|
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  FAISS_ASSERT(outDistances.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0) == queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0));</div>
|
|
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  FAISS_ASSERT(outIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0) == queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0));</div>
|
|
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span> </div>
|
|
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <span class="comment">// Reserve space for the quantized information</span></div>
|
|
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 2, true></a></div>
|
|
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  coarseDistances(mem, {queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), nprobe}, stream);</div>
|
|
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<int, 2, true></a></div>
|
|
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  coarseIndices(mem, {queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), nprobe}, stream);</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="comment">// Find the `nprobe` closest lists; we can use int indices both</span></div>
|
|
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="comment">// internally and externally</span></div>
|
|
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">quantizer_</a>->query(queries,</div>
|
|
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  nprobe,</div>
|
|
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  coarseDistances,</div>
|
|
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  coarseIndices,</div>
|
|
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <span class="keyword">false</span>);</div>
|
|
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span> </div>
|
|
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  runIVFFlatScan(queries,</div>
|
|
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  coarseIndices,</div>
|
|
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a96240a08b42bd1913e2286d7d514fc56">deviceListDataPointers_</a>,</div>
|
|
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a9aedcf0e6a20b908980ae96d73461f4c">deviceListIndexPointers_</a>,</div>
|
|
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a>,</div>
|
|
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a3a1c2031a4763f7d55bc8a400c63af66">deviceListLengths_</a>,</div>
|
|
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">maxListLength_</a>,</div>
|
|
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  k,</div>
|
|
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  l2Distance_,</div>
|
|
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  useFloat16_,</div>
|
|
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  outDistances,</div>
|
|
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  outIndices,</div>
|
|
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>);</div>
|
|
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span> </div>
|
|
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="comment">// If the GPU isn't storing indices (they are on the CPU side), we</span></div>
|
|
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="comment">// need to perform the re-mapping here</span></div>
|
|
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="comment">// FIXME: we might ultimately be calling this function with inputs</span></div>
|
|
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="comment">// from the CPU, these are unnecessary copies</span></div>
|
|
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="keywordflow">if</span> (<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_CPU) {</div>
|
|
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<long, 2, true></a> hostOutIndices(outIndices, stream);</div>
|
|
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span> </div>
|
|
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  ivfOffsetToUserIndex(hostOutIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>(),</div>
|
|
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#accc4d96c14643e5f471220cb1e92ac70">numLists_</a>,</div>
|
|
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  hostOutIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0),</div>
|
|
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  hostOutIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(1),</div>
|
|
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a53f3c382a79b7f89630a85dfbc3a1fed">listOffsetToUserIndex_</a>);</div>
|
|
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span> </div>
|
|
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="comment">// Copy back to GPU, since the input to this function is on the</span></div>
|
|
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="comment">// GPU</span></div>
|
|
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  outIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6dc00c182a92389b74c89ba7fcab40d3">copyFrom</a>(hostOutIndices, stream);</div>
|
|
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  }</div>
|
|
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span> }</div>
|
|
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span> </div>
|
|
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span> std::vector<float></div>
|
|
<div class="line"><a name="l00354"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFFlat.html#a78473b609750b8ec7dfe3d137f50c650"> 354</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFFlat.html#a78473b609750b8ec7dfe3d137f50c650">IVFFlat::getListVectors</a>(<span class="keywordtype">int</span> listId)<span class="keyword"> const </span>{</div>
|
|
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  FAISS_ASSERT(listId < <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">deviceListData_</a>.size());</div>
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<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="keyword">auto</span>& encVecs = *<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">deviceListData_</a>[listId];</div>
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<div class="line"><a name="l00357"></a><span class="lineno"> 357</span> </div>
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<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keyword">auto</span> stream = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>();</div>
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<div class="line"><a name="l00359"></a><span class="lineno"> 359</span> </div>
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<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordflow">if</span> (useFloat16_) {</div>
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<div class="line"><a name="l00361"></a><span class="lineno"> 361</span> <span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
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<div class="line"><a name="l00362"></a><span class="lineno"> 362</span> <span class="preprocessor"></span> <span class="keywordtype">size_t</span> num = encVecs.size() / <span class="keyword">sizeof</span>(half);</div>
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<div class="line"><a name="l00363"></a><span class="lineno"> 363</span> </div>
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<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<half, 1, true></a> devHalf((half*) encVecs.data(), {(int) num});</div>
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<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <span class="keyword">auto</span> devFloat = fromHalf(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>, stream, devHalf);</div>
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<div class="line"><a name="l00366"></a><span class="lineno"> 366</span> </div>
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<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  std::vector<float> out(num);</div>
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<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<float, 1, true></a> hostFloat(out.data(), {(int) num});</div>
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<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  hostFloat.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6dc00c182a92389b74c89ba7fcab40d3">copyFrom</a>(devFloat, stream);</div>
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<div class="line"><a name="l00370"></a><span class="lineno"> 370</span> </div>
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<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="keywordflow">return</span> out;</div>
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<div class="line"><a name="l00372"></a><span class="lineno"> 372</span> <span class="preprocessor">#endif</span></div>
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<div class="line"><a name="l00373"></a><span class="lineno"> 373</span> <span class="preprocessor"></span> }</div>
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<div class="line"><a name="l00374"></a><span class="lineno"> 374</span> </div>
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<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordtype">size_t</span> num = encVecs.size() / <span class="keyword">sizeof</span>(float);</div>
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<div class="line"><a name="l00376"></a><span class="lineno"> 376</span> </div>
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<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 1, true></a> devFloat((<span class="keywordtype">float</span>*) encVecs.data(), {(int) num});</div>
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<div class="line"><a name="l00378"></a><span class="lineno"> 378</span> </div>
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<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  std::vector<float> out(num);</div>
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<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<float, 1, true></a> hostFloat(out.data(), {(int) num});</div>
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<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  hostFloat.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6dc00c182a92389b74c89ba7fcab40d3">copyFrom</a>(devFloat, stream);</div>
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<div class="line"><a name="l00382"></a><span class="lineno"> 382</span> </div>
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<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keywordflow">return</span> out;</div>
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<div class="line"><a name="l00384"></a><span class="lineno"> 384</span> }</div>
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<div class="line"><a name="l00385"></a><span class="lineno"> 385</span> </div>
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<div class="line"><a name="l00386"></a><span class="lineno"> 386</span> } } <span class="comment">// namespace</span></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_accc4d96c14643e5f471220cb1e92ac70"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#accc4d96c14643e5f471220cb1e92ac70">faiss::gpu::IVFBase::numLists_</a></div><div class="ttdeci">const int numLists_</div><div class="ttdoc">Number of inverted lists we maintain. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00091">IVFBase.cuh:91</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_ae25ea0901fb628844868413f51c85bda"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">faiss::gpu::IVFBase::maxListLength_</a></div><div class="ttdeci">int maxListLength_</div><div class="ttdoc">Maximum list length seen. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00115">IVFBase.cuh:115</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuResources_html_aa0354aa570c24e17a9f8a6a45b153ed2"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">faiss::gpu::GpuResources::getDefaultStreamCurrentDevice</a></div><div class="ttdeci">cudaStream_t getDefaultStreamCurrentDevice()</div><div class="ttdoc">Calls getDefaultStream with the current device. </div><div class="ttdef"><b>Definition:</b> <a href="GpuResources_8cpp_source.html#l00025">GpuResources.cpp:25</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1FlatIndex_html_a6988df17792dae30f24cc859728777e6"><div class="ttname"><a href="classfaiss_1_1gpu_1_1FlatIndex.html#a6988df17792dae30f24cc859728777e6">faiss::gpu::FlatIndex::getSize</a></div><div class="ttdeci">int getSize() const </div><div class="ttdoc">Returns the number of vectors we contain. </div><div class="ttdef"><b>Definition:</b> <a href="FlatIndex_8cu_source.html#l00047">FlatIndex.cu:47</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a53f3c382a79b7f89630a85dfbc3a1fed"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a53f3c382a79b7f89630a85dfbc3a1fed">faiss::gpu::IVFBase::listOffsetToUserIndex_</a></div><div class="ttdeci">std::vector< std::vector< long > > listOffsetToUserIndex_</div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00127">IVFBase.cuh:127</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1FlatIndex_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1FlatIndex.html">faiss::gpu::FlatIndex</a></div><div class="ttdoc">Holder of GPU resources for a particular flat index. </div><div class="ttdef"><b>Definition:</b> <a href="FlatIndex_8cuh_source.html#l00023">FlatIndex.cuh:23</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a74dbc09519c9c14479b2d18f2e5042e8"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a74dbc09519c9c14479b2d18f2e5042e8">faiss::gpu::Tensor::view</a></div><div class="ttdeci">__host__ __device__ Tensor< T, SubDim, InnerContig, IndexT, PtrTraits > view(DataPtrType at)</div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00598">Tensor-inl.cuh:598</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html">faiss::gpu::IVFBase</a></div><div class="ttdoc">Base inverted list functionality for IVFFlat and IVFPQ. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00027">IVFBase.cuh:27</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuResources_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuResources.html">faiss::gpu::GpuResources</a></div><div class="ttdef"><b>Definition:</b> <a href="GpuResources_8h_source.html#l00023">GpuResources.h:23</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFFlat_html_a7ae83f107abf31feeb78cd5633806e5d"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFFlat.html#a7ae83f107abf31feeb78cd5633806e5d">faiss::gpu::IVFFlat::IVFFlat</a></div><div class="ttdeci">IVFFlat(GpuResources *resources, FlatIndex *quantizer, bool l2Distance, bool useFloat16, IndicesOptions indicesOptions, MemorySpace space)</div><div class="ttdoc">Construct from a quantizer that has elemen. </div><div class="ttdef"><b>Definition:</b> <a href="IVFFlat_8cu_source.html#l00029">IVFFlat.cu:29</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a3a1c2031a4763f7d55bc8a400c63af66"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a3a1c2031a4763f7d55bc8a400c63af66">faiss::gpu::IVFBase::deviceListLengths_</a></div><div class="ttdeci">thrust::device_vector< int > deviceListLengths_</div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00112">IVFBase.cuh:112</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a9aedcf0e6a20b908980ae96d73461f4c"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a9aedcf0e6a20b908980ae96d73461f4c">faiss::gpu::IVFBase::deviceListIndexPointers_</a></div><div class="ttdeci">thrust::device_vector< void * > deviceListIndexPointers_</div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00108">IVFBase.cuh:108</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFFlat_html_af20f96b6ad754664796c8a4e7f83ed3a"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFFlat.html#af20f96b6ad754664796c8a4e7f83ed3a">faiss::gpu::IVFFlat::classifyAndAddVectors</a></div><div class="ttdeci">int classifyAndAddVectors(Tensor< float, 2, true > &vecs, Tensor< long, 1, true > &indices)</div><div class="ttdef"><b>Definition:</b> <a href="IVFFlat_8cu_source.html#l00130">IVFFlat.cu:130</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuResources_html_a1dda2dc3db1bd62cde6657c5cdbfb6e1"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuResources.html#a1dda2dc3db1bd62cde6657c5cdbfb6e1">faiss::gpu::GpuResources::getMemoryManagerCurrentDevice</a></div><div class="ttdeci">DeviceMemory & getMemoryManagerCurrentDevice()</div><div class="ttdoc">Calls getMemoryManager for the current device. </div><div class="ttdef"><b>Definition:</b> <a href="GpuResources_8cpp_source.html#l00035">GpuResources.cpp:35</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a6dc00c182a92389b74c89ba7fcab40d3"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a6dc00c182a92389b74c89ba7fcab40d3">faiss::gpu::Tensor::copyFrom</a></div><div class="ttdeci">__host__ void copyFrom(Tensor< T, Dim, InnerContig, IndexT, PtrTraits > &t, cudaStream_t stream)</div><div class="ttdoc">Copies a tensor into ourselves; sizes must match. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00101">Tensor-inl.cuh:101</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a878114abdba07c9cf7735f9c0ed594c3"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">faiss::gpu::IVFBase::quantizer_</a></div><div class="ttdeci">FlatIndex * quantizer_</div><div class="ttdoc">Quantizer object. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00085">IVFBase.cuh:85</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a6699c311648457f257afa340c61f417c"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">faiss::gpu::Tensor::getSize</a></div><div class="ttdeci">__host__ __device__ IndexT getSize(int i) const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00226">Tensor.cuh:226</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a96240a08b42bd1913e2286d7d514fc56"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a96240a08b42bd1913e2286d7d514fc56">faiss::gpu::IVFBase::deviceListDataPointers_</a></div><div class="ttdeci">thrust::device_vector< void * > deviceListDataPointers_</div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00104">IVFBase.cuh:104</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a50411ce4d0fa32ef715e3321b6e33212"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">faiss::gpu::Tensor::data</a></div><div class="ttdeci">__host__ __device__ DataPtrType data()</div><div class="ttdoc">Returns a raw pointer to the start of our data. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00178">Tensor.cuh:178</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a05e6400358ec1f529a67209d3f24cc63"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">faiss::gpu::IVFBase::resources_</a></div><div class="ttdeci">GpuResources * resources_</div><div class="ttdoc">Collection of GPU resources that we use. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00082">IVFBase.cuh:82</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html">faiss::gpu::Tensor</a></div><div class="ttdoc">Our tensor type. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00030">Tensor.cuh:30</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFFlat_html_a0bedde6dcb7c2f10f277461b97486f52"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFFlat.html#a0bedde6dcb7c2f10f277461b97486f52">faiss::gpu::IVFFlat::addCodeVectorsFromCpu</a></div><div class="ttdeci">void addCodeVectorsFromCpu(int listId, const float *vecs, const long *indices, size_t numVecs)</div><div class="ttdef"><b>Definition:</b> <a href="IVFFlat_8cu_source.html#l00058">IVFFlat.cu:58</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a319568b832518392fed33ea4f8bfc613"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">faiss::gpu::IVFBase::bytesPerVector_</a></div><div class="ttdeci">const int bytesPerVector_</div><div class="ttdoc">Number of bytes per vector in the list. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00094">IVFBase.cuh:94</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFFlat_html_a6652ca90a8a30512104fc909f0a0a6b8"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFFlat.html#a6652ca90a8a30512104fc909f0a0a6b8">faiss::gpu::IVFFlat::query</a></div><div class="ttdeci">void query(Tensor< float, 2, true > &queries, int nprobe, int k, Tensor< float, 2, true > &outDistances, Tensor< long, 2, true > &outIndices)</div><div class="ttdef"><b>Definition:</b> <a href="IVFFlat_8cu_source.html#l00288">IVFFlat.cu:288</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFFlat_html_a78473b609750b8ec7dfe3d137f50c650"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFFlat.html#a78473b609750b8ec7dfe3d137f50c650">faiss::gpu::IVFFlat::getListVectors</a></div><div class="ttdeci">std::vector< float > getListVectors(int listId) const </div><div class="ttdoc">Return the vectors of a particular list back to the CPU. </div><div class="ttdef"><b>Definition:</b> <a href="IVFFlat_8cu_source.html#l00354">IVFFlat.cu:354</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_acc695610c9513952b8d234dc0db78e5c"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#acc695610c9513952b8d234dc0db78e5c">faiss::gpu::IVFBase::updateDeviceListInfo_</a></div><div class="ttdeci">void updateDeviceListInfo_(cudaStream_t stream)</div><div class="ttdoc">Update all device-side list pointer and size information. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cu_source.html#l00138">IVFBase.cu:138</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_afb6d10e23d6448c10f472b9234e0bcab"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">faiss::gpu::IVFBase::indicesOptions_</a></div><div class="ttdeci">const IndicesOptions indicesOptions_</div><div class="ttdoc">How are user indices stored on the GPU? </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00097">IVFBase.cuh:97</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1HostTensor_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1HostTensor.html">faiss::gpu::HostTensor</a></div><div class="ttdef"><b>Definition:</b> <a href="HostTensor_8cuh_source.html#l00022">HostTensor.cuh:22</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a2facc7285107de1f24d3471cbcf15f26"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">faiss::gpu::IVFBase::deviceListData_</a></div><div class="ttdeci">std::vector< std::unique_ptr< DeviceVector< unsigned char > > > deviceListData_</div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00121">IVFBase.cuh:121</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1DeviceTensor_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1DeviceTensor.html">faiss::gpu::DeviceTensor< float, 2, true ></a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_aba3e3cfa469e5187f2d553fff10e0250"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#aba3e3cfa469e5187f2d553fff10e0250">faiss::gpu::IVFBase::dim_</a></div><div class="ttdeci">const int dim_</div><div class="ttdoc">Expected dimensionality of the vectors. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00088">IVFBase.cuh:88</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a5027720549de98f4e609d6339099df35"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a5027720549de98f4e609d6339099df35">faiss::gpu::IVFBase::addIndicesFromCpu_</a></div><div class="ttdeci">void addIndicesFromCpu_(int listId, const long *indices, size_t numVecs)</div><div class="ttdoc">Shared function to copy indices from CPU to GPU. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cu_source.html#l00245">IVFBase.cu:245</a></div></div>
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