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FlatIndex.cu
1 /**
2 * Copyright (c) 2015-present, Facebook, Inc.
3 * All rights reserved.
4 *
5 * This source code is licensed under the CC-by-NC license found in the
6 * LICENSE file in the root directory of this source tree.
7 */
8
9 // Copyright 2004-present Facebook. All Rights Reserved.
10
11 #include "FlatIndex.cuh"
12 #include "Distance.cuh"
13 #include "L2Norm.cuh"
14 #include "../utils/CopyUtils.cuh"
15 #include "../utils/DeviceUtils.h"
16 #include "../utils/Transpose.cuh"
17
18 namespace faiss { namespace gpu {
19
20 FlatIndex::FlatIndex(GpuResources* res,
21 int dim,
22 bool l2Distance,
23 bool useFloat16,
24 bool useFloat16Accumulator,
25 bool storeTransposed,
26 MemorySpace space) :
27 resources_(res),
28 dim_(dim),
29 useFloat16_(useFloat16),
30 useFloat16Accumulator_(useFloat16Accumulator),
31 storeTransposed_(storeTransposed),
32 l2Distance_(l2Distance),
33 space_(space),
34 num_(0),
35 rawData_(space) {
36 #ifndef FAISS_USE_FLOAT16
37 FAISS_ASSERT(!useFloat16_);
38 #endif
39 }
40
41 bool
42 FlatIndex::getUseFloat16() const {
43 return useFloat16_;
44 }
45
46 /// Returns the number of vectors we contain
47 int FlatIndex::getSize() const {
48 #ifdef FAISS_USE_FLOAT16
49 if (useFloat16_) {
50 return vectorsHalf_.getSize(0);
51 }
52 #endif
53
54 return vectors_.getSize(0);
55 }
56
57 int FlatIndex::getDim() const {
58 #ifdef FAISS_USE_FLOAT16
59 if (useFloat16_) {
60 return vectorsHalf_.getSize(1);
61 }
62 #endif
63
64 return vectors_.getSize(1);
65 }
66
67 void
68 FlatIndex::reserve(size_t numVecs, cudaStream_t stream) {
69 if (useFloat16_) {
70 #ifdef FAISS_USE_FLOAT16
71 rawData_.reserve(numVecs * dim_ * sizeof(half), stream);
72 #endif
73 } else {
74 rawData_.reserve(numVecs * dim_ * sizeof(float), stream);
75 }
76 }
77
78 Tensor<float, 2, true>&
79 FlatIndex::getVectorsFloat32Ref() {
80 return vectors_;
81 }
82
83 #ifdef FAISS_USE_FLOAT16
84 Tensor<half, 2, true>&
85 FlatIndex::getVectorsFloat16Ref() {
86 return vectorsHalf_;
87 }
88 #endif
89
90 DeviceTensor<float, 2, true>
91 FlatIndex::getVectorsFloat32Copy(cudaStream_t stream) {
92 return getVectorsFloat32Copy(0, num_, stream);
93 }
94
95 DeviceTensor<float, 2, true>
96 FlatIndex::getVectorsFloat32Copy(int from, int num, cudaStream_t stream) {
97 DeviceTensor<float, 2, true> vecFloat32({num, dim_}, space_);
98
99 if (useFloat16_) {
100 #ifdef FAISS_USE_FLOAT16
101 runConvertToFloat32(vecFloat32.data(),
102 vectorsHalf_[from].data(),
103 num * dim_, stream);
104 #endif
105 } else {
106 vectors_.copyTo(vecFloat32, stream);
107 }
108
109 return vecFloat32;
110 }
111
112 void
113 FlatIndex::query(Tensor<float, 2, true>& input,
114 int k,
115 Tensor<float, 2, true>& outDistances,
116 Tensor<int, 2, true>& outIndices,
117 bool exactDistance,
118 int tileSize) {
119 auto stream = resources_->getDefaultStreamCurrentDevice();
120 auto& mem = resources_->getMemoryManagerCurrentDevice();
121
122 if (useFloat16_) {
123 // We need to convert to float16
124 #ifdef FAISS_USE_FLOAT16
125 auto inputHalf = toHalf<2>(resources_, stream, input);
126
127 DeviceTensor<half, 2, true> outDistancesHalf(
128 mem, {outDistances.getSize(0), outDistances.getSize(1)}, stream);
129
130 query(inputHalf, k, outDistancesHalf, outIndices, exactDistance, tileSize);
131
132 if (exactDistance) {
133 // Convert outDistances back
134 fromHalf<2>(stream, outDistancesHalf, outDistances);
135 }
136 #endif
137 } else {
138 if (l2Distance_) {
139 runL2Distance(resources_,
140 vectors_,
141 storeTransposed_ ? &vectorsTransposed_ : nullptr,
142 &norms_,
143 input,
144 k,
145 outDistances,
146 outIndices,
147 // FIXME
148 !exactDistance,
149 tileSize);
150 } else {
151 runIPDistance(resources_,
152 vectors_,
153 storeTransposed_ ? &vectorsTransposed_ : nullptr,
154 input,
155 k,
156 outDistances,
157 outIndices,
158 tileSize);
159 }
160 }
161 }
162
163 #ifdef FAISS_USE_FLOAT16
164 void
165 FlatIndex::query(Tensor<half, 2, true>& input,
166 int k,
167 Tensor<half, 2, true>& outDistances,
168 Tensor<int, 2, true>& outIndices,
169 bool exactDistance,
170 int tileSize) {
171 FAISS_ASSERT(useFloat16_);
172
173 if (l2Distance_) {
174 runL2Distance(resources_,
175 vectorsHalf_,
176 storeTransposed_ ? &vectorsHalfTransposed_ : nullptr,
177 &normsHalf_,
178 input,
179 k,
180 outDistances,
181 outIndices,
182 useFloat16Accumulator_,
183 // FIXME
184 !exactDistance,
185 tileSize);
186 } else {
187 runIPDistance(resources_,
188 vectorsHalf_,
189 storeTransposed_ ? &vectorsHalfTransposed_ : nullptr,
190 input,
191 k,
192 outDistances,
193 outIndices,
194 useFloat16Accumulator_,
195 tileSize);
196 }
197 }
198 #endif
199
200 void
201 FlatIndex::add(const float* data, int numVecs, cudaStream_t stream) {
202 if (numVecs == 0) {
203 return;
204 }
205
206 if (useFloat16_) {
207 #ifdef FAISS_USE_FLOAT16
208 // Make sure that `data` is on our device; we'll run the
209 // conversion on our device
210 auto devData = toDevice<float, 2>(resources_,
211 getCurrentDevice(),
212 (float*) data,
213 stream,
214 {numVecs, dim_});
215
216 auto devDataHalf = toHalf<2>(resources_, stream, devData);
217
218 rawData_.append((char*) devDataHalf.data(),
219 devDataHalf.getSizeInBytes(),
220 stream);
221 #endif
222 } else {
223 rawData_.append((char*) data,
224 (size_t) dim_ * numVecs * sizeof(float),
225 stream);
226 }
227
228 num_ += numVecs;
229
230 if (useFloat16_) {
231 #ifdef FAISS_USE_FLOAT16
232 DeviceTensor<half, 2, true> vectorsHalf(
233 (half*) rawData_.data(), {(int) num_, dim_}, space_);
234 vectorsHalf_ = std::move(vectorsHalf);
235 #endif
236 } else {
237 DeviceTensor<float, 2, true> vectors(
238 (float*) rawData_.data(), {(int) num_, dim_}, space_);
239 vectors_ = std::move(vectors);
240 }
241
242 if (storeTransposed_) {
243 if (useFloat16_) {
244 #ifdef FAISS_USE_FLOAT16
245 vectorsHalfTransposed_ =
246 std::move(DeviceTensor<half, 2, true>({dim_, (int) num_}, space_));
247 runTransposeAny(vectorsHalf_, 0, 1, vectorsHalfTransposed_, stream);
248 #endif
249 } else {
250 vectorsTransposed_ =
251 std::move(DeviceTensor<float, 2, true>({dim_, (int) num_}, space_));
252 runTransposeAny(vectors_, 0, 1, vectorsTransposed_, stream);
253 }
254 }
255
256 if (l2Distance_) {
257 // Precompute L2 norms of our database
258 if (useFloat16_) {
259 #ifdef FAISS_USE_FLOAT16
260 DeviceTensor<half, 1, true> normsHalf({(int) num_}, space_);
261 runL2Norm(vectorsHalf_, normsHalf, true, stream);
262 normsHalf_ = std::move(normsHalf);
263 #endif
264 } else {
265 DeviceTensor<float, 1, true> norms({(int) num_}, space_);
266 runL2Norm(vectors_, norms, true, stream);
267 norms_ = std::move(norms);
268 }
269 }
270 }
271
272 void
273 FlatIndex::reset() {
274 rawData_.clear();
275 vectors_ = std::move(DeviceTensor<float, 2, true>());
276 norms_ = std::move(DeviceTensor<float, 1, true>());
277 num_ = 0;
278 }
279
280 } }
faiss::gpu::FlatIndex::getVectorsFloat32Copy
DeviceTensor< float, 2, true > getVectorsFloat32Copy(cudaStream_t stream)
Definition: FlatIndex.cu:91
faiss::gpu::FlatIndex::getSize
int getSize() const
Returns the number of vectors we contain.
Definition: FlatIndex.cu:47
faiss::gpu::Tensor::copyTo
__host__ void copyTo(Tensor< T, Dim, Contig, IndexT, PtrTraits > &t, cudaStream_t stream)
Copies ourselves into a tensor; sizes must match.
Definition: Tensor-inl.cuh:139
faiss::gpu::FlatIndex::reserve
void reserve(size_t numVecs, cudaStream_t stream)
Reserve storage that can contain at least this many vectors.
Definition: FlatIndex.cu:68
faiss::gpu::FlatIndex::add
void add(const float *data, int numVecs, cudaStream_t stream)
Definition: FlatIndex.cu:201
faiss::gpu::Tensor
Our tensor type.
Definition: Tensor.cuh:30
faiss::gpu::Tensor::getSize
__host__ __device__ IndexT getSize(int i) const
Definition: Tensor.cuh:221
faiss::gpu::FlatIndex::getVectorsFloat32Ref
Tensor< float, 2, true > & getVectorsFloat32Ref()
Returns a reference to our vectors currently in use.
Definition: FlatIndex.cu:79
faiss::gpu::FlatIndex::reset
void reset()
Free all storage.
Definition: FlatIndex.cu:273
faiss::gpu::DeviceTensor< float, 2, true >