76 lines
2.0 KiB
Plaintext
76 lines
2.0 KiB
Plaintext
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/**
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* Copyright (c) 2015-present, Facebook, Inc.
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* All rights reserved.
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*
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* This source code is licensed under the CC-by-NC license found in the
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* LICENSE file in the root directory of this source tree.
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*/
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// Copyright 2004-present Facebook. All Rights Reserved.
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#pragma once
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#include "Float16.cuh"
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#include "Select.cuh"
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namespace faiss { namespace gpu {
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template <typename K,
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typename IndexType,
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bool Dir,
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int NumWarpQ,
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int NumThreadQ,
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int ThreadsPerBlock>
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__global__ void warpSelect(Tensor<K, 2, true> in,
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Tensor<K, 2, true> outK,
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Tensor<IndexType, 2, true> outV,
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K initK,
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IndexType initV,
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int k) {
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constexpr int kNumWarps = ThreadsPerBlock / kWarpSize;
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WarpSelect<K, IndexType, Dir, Comparator<K>,
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NumWarpQ, NumThreadQ, ThreadsPerBlock>
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heap(initK, initV, k);
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int warpId = threadIdx.x / kWarpSize;
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int row = blockIdx.x * kNumWarps + warpId;
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if (row >= in.getSize(0)) {
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return;
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}
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K* inStart = in[row].data();
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int i = getLaneId();
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// Whole warps must participate in the selection
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int limit = utils::roundDown(in.getSize(1), kWarpSize);
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for (; i < limit; i += kWarpSize) {
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heap.add(inStart[i], (IndexType) i);
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}
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// Handle non-warp multiple remainder
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if (i < in.getSize(1)) {
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heap.addThreadQ(inStart[i], (IndexType) i);
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}
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heap.reduce();
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heap.writeOut(outK[row].data(),
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outV[row].data(), k);
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}
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void runWarpSelect(Tensor<float, 2, true>& in,
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Tensor<float, 2, true>& outKeys,
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Tensor<int, 2, true>& outIndices,
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bool dir, int k, cudaStream_t stream);
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#ifdef FAISS_USE_FLOAT16
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void runWarpSelect(Tensor<half, 2, true>& in,
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Tensor<half, 2, true>& outKeys,
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Tensor<int, 2, true>& outIndices,
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bool dir, int k, cudaStream_t stream);
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#endif
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} } // namespace
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