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