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WarpSelectKernel.cuh
1 /**
2 * Copyright (c) 2015-present, Facebook, Inc.
3 * All rights reserved.
4 *
5 * This source code is licensed under the BSD+Patents 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 #pragma once
11
12 #include "Float16.cuh"
13 #include "Select.cuh"
14
15 namespace faiss { namespace gpu {
16
17 template <typename K,
18 typename IndexType,
19 bool Dir,
20 int NumWarpQ,
21 int NumThreadQ,
22 int ThreadsPerBlock>
23 __global__ void warpSelect(Tensor<K, 2, true> in,
24 Tensor<K, 2, true> outK,
25 Tensor<IndexType, 2, true> outV,
26 K initK,
27 IndexType initV,
28 int k) {
29 constexpr int kNumWarps = ThreadsPerBlock / kWarpSize;
30
31 WarpSelect<K, IndexType, Dir, Comparator<K>,
32 NumWarpQ, NumThreadQ, ThreadsPerBlock>
33 heap(initK, initV, k);
34
35 int warpId = threadIdx.x / kWarpSize;
36 int row = blockIdx.x * kNumWarps + warpId;
37
38 if (row >= in.getSize(0)) {
39 return;
40 }
41
42 int i = getLaneId();
43 K* inStart = in[row][i].data();
44
45 // Whole warps must participate in the selection
46 int limit = utils::roundDown(in.getSize(1), kWarpSize);
47
48 for (; i < limit; i += kWarpSize) {
49 heap.add(*inStart, (IndexType) i);
50 inStart += kWarpSize;
51 }
52
53 // Handle non-warp multiple remainder
54 if (i < in.getSize(1)) {
55 heap.addThreadQ(*inStart, (IndexType) i);
56 }
57
58 heap.reduce();
59 heap.writeOut(outK[row].data(),
60 outV[row].data(), k);
61 }
62
63 void runWarpSelect(Tensor<float, 2, true>& in,
64 Tensor<float, 2, true>& outKeys,
65 Tensor<int, 2, true>& outIndices,
66 bool dir, int k, cudaStream_t stream);
67
68 #ifdef FAISS_USE_FLOAT16
69 void runWarpSelect(Tensor<half, 2, true>& in,
70 Tensor<half, 2, true>& outKeys,
71 Tensor<int, 2, true>& outIndices,
72 bool dir, int k, cudaStream_t stream);
73 #endif
74
75 } } // namespace