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Add ANN refinement method #1038
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bea492c
Add ANN refinement method
tfeher c866cac
Adressing review comments
tfeher ec9b415
Merge remote-tracking branch 'origin/branch-22.12' into fea_ann_refine2
tfeher 8943b94
Correct innerproduct distance for host
tfeher c727287
Fix style and spelling
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/* | ||
* Copyright (c) 2022, NVIDIA CORPORATION. | ||
* | ||
* Licensed under the Apache License, Version 2.0 (the "License"); | ||
* you may not use this file except in compliance with the License. | ||
* You may obtain a copy of the License at | ||
* | ||
* http://www.apache.org/licenses/LICENSE-2.0 | ||
* | ||
* Unless required by applicable law or agreed to in writing, software | ||
* distributed under the License is distributed on an "AS IS" BASIS, | ||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
* See the License for the specific language governing permissions and | ||
* limitations under the License. | ||
*/ | ||
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#include <common/benchmark.hpp> | ||
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#include <raft/random/rng.cuh> | ||
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#include <raft/core/device_mdspan.hpp> | ||
#include <raft/core/handle.hpp> | ||
#include <raft/distance/distance_types.hpp> | ||
#include <raft/neighbors/detail/refine.cuh> | ||
#include <raft/neighbors/refine.cuh> | ||
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#if defined RAFT_DISTANCE_COMPILED | ||
#include <raft/distance/specializations.cuh> | ||
#endif | ||
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#if defined RAFT_NN_COMPILED | ||
#include <raft/spatial/knn/specializations.cuh> | ||
#endif | ||
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#include <rmm/cuda_stream_view.hpp> | ||
#include <rmm/mr/device/per_device_resource.hpp> | ||
#include <rmm/mr/device/pool_memory_resource.hpp> | ||
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#include "../../test/neighbors/refine_helper.cuh" | ||
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#include <iostream> | ||
#include <sstream> | ||
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using namespace raft::neighbors::detail; | ||
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namespace raft::bench::neighbors { | ||
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template <typename IdxT> | ||
inline auto operator<<(std::ostream& os, const RefineInputs<IdxT>& p) -> std::ostream& | ||
{ | ||
os << p.n_rows << "#" << p.dim << "#" << p.n_queries << "#" << p.k0 << "#" << p.k << "#" | ||
<< (p.host_data ? "host" : "device"); | ||
return os; | ||
} | ||
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RefineInputs<int64_t> p; | ||
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template <typename DataT, typename DistanceT, typename IdxT> | ||
class RefineAnn : public fixture { | ||
public: | ||
RefineAnn(RefineInputs<IdxT> p) : data(handle_, p) {} | ||
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void run_benchmark(::benchmark::State& state) override | ||
{ | ||
std::ostringstream label_stream; | ||
label_stream << data.p; | ||
state.SetLabel(label_stream.str()); | ||
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auto old_mr = rmm::mr::get_current_device_resource(); | ||
rmm::mr::pool_memory_resource<rmm::mr::device_memory_resource> pool_mr(old_mr); | ||
rmm::mr::set_current_device_resource(&pool_mr); | ||
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if (data.p.host_data) { | ||
loop_on_state(state, [this]() { | ||
raft::neighbors::refine<IdxT, DataT, DistanceT, IdxT>(handle_, | ||
data.dataset_host.view(), | ||
data.queries_host.view(), | ||
data.candidates_host.view(), | ||
data.refined_indices_host.view(), | ||
data.refined_distances_host.view(), | ||
data.p.metric); | ||
}); | ||
} else { | ||
loop_on_state(state, [&]() { | ||
raft::neighbors::refine<IdxT, DataT, DistanceT, IdxT>(handle_, | ||
data.dataset.view(), | ||
data.queries.view(), | ||
data.candidates.view(), | ||
data.refined_indices.view(), | ||
data.refined_distances.view(), | ||
data.p.metric); | ||
}); | ||
} | ||
rmm::mr::set_current_device_resource(old_mr); | ||
} | ||
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private: | ||
raft::handle_t handle_; | ||
RefineHelper<DataT, DistanceT, IdxT> data; | ||
}; | ||
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std::vector<RefineInputs<int64_t>> getInputs() | ||
{ | ||
std::vector<RefineInputs<int64_t>> out; | ||
raft::distance::DistanceType metric = raft::distance::DistanceType::L2Expanded; | ||
for (bool host_data : {true, false}) { | ||
for (int64_t n_queries : {1000, 10000}) { | ||
for (int64_t dim : {128, 512}) { | ||
out.push_back(RefineInputs<int64_t>{n_queries, 2000000, dim, 32, 128, metric, host_data}); | ||
out.push_back(RefineInputs<int64_t>{n_queries, 2000000, dim, 10, 40, metric, host_data}); | ||
} | ||
} | ||
} | ||
return out; | ||
} | ||
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using refine_float_int64 = RefineAnn<float, float, int64_t>; | ||
RAFT_BENCH_REGISTER(refine_float_int64, "", getInputs()); | ||
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using refine_uint8_int64 = RefineAnn<uint8_t, float, int64_t>; | ||
RAFT_BENCH_REGISTER(refine_uint8_int64, "", getInputs()); | ||
} // namespace raft::bench::neighbors |
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/* | ||
* Copyright (c) 2022, NVIDIA CORPORATION. | ||
* | ||
* Licensed under the Apache License, Version 2.0 (the "License"); | ||
* you may not use this file except in compliance with the License. | ||
* You may obtain a copy of the License at | ||
* | ||
* http://www.apache.org/licenses/LICENSE-2.0 | ||
* | ||
* Unless required by applicable law or agreed to in writing, software | ||
* distributed under the License is distributed on an "AS IS" BASIS, | ||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
* See the License for the specific language governing permissions and | ||
* limitations under the License. | ||
*/ | ||
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#pragma once | ||
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#include <raft/core/device_mdarray.hpp> | ||
#include <raft/core/handle.hpp> | ||
#include <raft/core/host_mdspan.hpp> | ||
#include <raft/core/nvtx.hpp> | ||
#include <raft/spatial/knn/detail/ann_utils.cuh> | ||
#include <raft/spatial/knn/detail/ivf_flat_build.cuh> | ||
#include <raft/spatial/knn/detail/ivf_flat_search.cuh> | ||
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#include <cstdlib> | ||
#include <omp.h> | ||
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#include <thrust/sequence.h> | ||
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namespace raft::neighbors::detail { | ||
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/** Checks whether the input data extents are compatible. */ | ||
template <typename extents_t> | ||
void check_input(extents_t dataset, | ||
extents_t queries, | ||
extents_t candidates, | ||
extents_t indices, | ||
extents_t distances, | ||
distance::DistanceType metric) | ||
{ | ||
auto n_queries = queries.extent(0); | ||
auto k = distances.extent(1); | ||
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RAFT_EXPECTS(k <= raft::spatial::knn::detail::topk::kMaxCapacity, | ||
"k must be lest than topk::kMaxCapacity (%d).", | ||
raft::spatial::knn::detail::topk::kMaxCapacity); | ||
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RAFT_EXPECTS(indices.extent(0) == n_queries && distances.extent(0) == n_queries && | ||
candidates.extent(0) == n_queries, | ||
"Number of rows in output indices and distances matrices must equal number of rows " | ||
"in search matrix."); | ||
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RAFT_EXPECTS(indices.extent(1) == k, | ||
"Number of columns in output indices and distances matrices must be equal to k"); | ||
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RAFT_EXPECTS(queries.extent(1) == dataset.extent(1), | ||
"Number of columns must be equal for dataset and queries"); | ||
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RAFT_EXPECTS(candidates.extent(1) >= k, | ||
"Number of neighbor candidates must not be smaller than k (%d vs %d)", | ||
static_cast<int>(candidates.extent(1)), | ||
static_cast<int>(k)); | ||
} | ||
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/** | ||
* See raft::neighbors::refine for docs. | ||
*/ | ||
template <typename idx_t, typename data_t, typename distance_t, typename matrix_idx> | ||
void refine_device(raft::handle_t const& handle, | ||
raft::device_matrix_view<const data_t, matrix_idx, row_major> dataset, | ||
raft::device_matrix_view<const data_t, matrix_idx, row_major> queries, | ||
raft::device_matrix_view<const idx_t, matrix_idx, row_major> neighbor_candidates, | ||
raft::device_matrix_view<idx_t, matrix_idx, row_major> indices, | ||
raft::device_matrix_view<distance_t, matrix_idx, row_major> distances, | ||
distance::DistanceType metric = distance::DistanceType::L2Unexpanded) | ||
{ | ||
matrix_idx n_candidates = neighbor_candidates.extent(1); | ||
matrix_idx n_queries = queries.extent(0); | ||
matrix_idx dim = dataset.extent(1); | ||
uint32_t k = static_cast<uint32_t>(indices.extent(1)); | ||
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common::nvtx::range<common::nvtx::domain::raft> fun_scope( | ||
"neighbors::refine(%zu, %u)", size_t(n_queries), uint32_t(n_candidates)); | ||
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check_input(dataset.extents(), | ||
queries.extents(), | ||
neighbor_candidates.extents(), | ||
indices.extents(), | ||
distances.extents(), | ||
metric); | ||
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// The refinement search can be mapped to an IVF flat search: | ||
// - We consider that the candidate vectors form a cluster, separately for each query. | ||
// - In other words, the n_queries * n_candidates vectors form n_queries clusters, each with | ||
// n_candidates elements. | ||
// - We consider that the coarse level search is already performed and assigned a single cluster | ||
// to search for each query (the cluster formed from the corresponding candidates). | ||
// - We run IVF flat search with n_probes=1 to select the best k elements of the candidates. | ||
rmm::device_uvector<uint32_t> fake_coarse_idx(n_queries, handle.get_stream()); | ||
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thrust::sequence( | ||
handle.get_thrust_policy(), fake_coarse_idx.data(), fake_coarse_idx.data() + n_queries); | ||
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raft::neighbors::ivf_flat::index<data_t, idx_t> refinement_index( | ||
handle, metric, n_queries, false, dim); | ||
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raft::spatial::knn::ivf_flat::detail::fill_refinement_index(handle, | ||
&refinement_index, | ||
dataset.data_handle(), | ||
neighbor_candidates.data_handle(), | ||
n_queries, | ||
n_candidates); | ||
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uint32_t grid_dim_x = 1; | ||
raft::spatial::knn::ivf_flat::detail::ivfflat_interleaved_scan< | ||
data_t, | ||
typename raft::spatial::knn::detail::utils::config<data_t>::value_t, | ||
idx_t>(refinement_index, | ||
queries.data_handle(), | ||
fake_coarse_idx.data(), | ||
static_cast<uint32_t>(n_queries), | ||
refinement_index.metric(), | ||
1, | ||
k, | ||
raft::spatial::knn::ivf_flat::detail::is_min_close(metric), | ||
indices.data_handle(), | ||
distances.data_handle(), | ||
grid_dim_x, | ||
handle.get_stream()); | ||
} | ||
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/** Helper structure for naive CPU implementation of refine. */ | ||
typedef struct { | ||
uint64_t id; | ||
float distance; | ||
} struct_for_refinement; | ||
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int _postprocessing_qsort_compare(const void* v1, const void* v2) | ||
{ | ||
// sort in ascending order | ||
if (((struct_for_refinement*)v1)->distance > ((struct_for_refinement*)v2)->distance) { | ||
return 1; | ||
} else if (((struct_for_refinement*)v1)->distance < ((struct_for_refinement*)v2)->distance) { | ||
return -1; | ||
} else { | ||
return 0; | ||
} | ||
} | ||
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/** | ||
* Naive CPU implementation of refine operation | ||
* | ||
* All pointers are expected to be accessible on the host. | ||
*/ | ||
template <typename idx_t, typename data_t, typename distance_t, typename matrix_idx> | ||
void refine_host(raft::host_matrix_view<const data_t, matrix_idx, row_major> dataset, | ||
raft::host_matrix_view<const data_t, matrix_idx, row_major> queries, | ||
raft::host_matrix_view<const idx_t, matrix_idx, row_major> neighbor_candidates, | ||
raft::host_matrix_view<idx_t, matrix_idx, row_major> indices, | ||
raft::host_matrix_view<distance_t, matrix_idx, row_major> distances, | ||
distance::DistanceType metric = distance::DistanceType::L2Unexpanded) | ||
{ | ||
check_input(dataset.extents(), | ||
queries.extents(), | ||
neighbor_candidates.extents(), | ||
indices.extents(), | ||
distances.extents(), | ||
metric); | ||
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switch (metric) { | ||
case raft::distance::DistanceType::L2Expanded: break; | ||
case raft::distance::DistanceType::InnerProduct: break; | ||
default: throw raft::logic_error("Unsopported metric"); | ||
} | ||
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size_t numDataset = dataset.extent(0); | ||
size_t numQueries = queries.extent(0); | ||
size_t dimDataset = dataset.extent(1); | ||
const data_t* dataset_ptr = dataset.data_handle(); | ||
const data_t* queries_ptr = queries.data_handle(); | ||
const idx_t* neighbors = neighbor_candidates.data_handle(); | ||
idx_t topK = neighbor_candidates.extent(1); | ||
idx_t refinedTopK = indices.extent(1); | ||
idx_t* refinedNeighbors = indices.data_handle(); | ||
distance_t* refinedDistances = distances.data_handle(); | ||
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common::nvtx::range<common::nvtx::domain::raft> fun_scope( | ||
"neighbors::refine_host(%zu, %u)", size_t(numQueries), uint32_t(topK)); | ||
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#pragma omp parallel | ||
{ | ||
struct_for_refinement* sfr = | ||
(struct_for_refinement*)malloc(sizeof(struct_for_refinement) * topK); | ||
for (size_t i = omp_get_thread_num(); i < numQueries; i += omp_get_num_threads()) { | ||
// compute distance with original dataset vectors | ||
const data_t* cur_query = queries_ptr + ((uint64_t)dimDataset * i); | ||
for (size_t j = 0; j < (size_t)topK; j++) { | ||
idx_t id = neighbors[j + (topK * i)]; | ||
const data_t* cur_dataset = dataset_ptr + ((uint64_t)dimDataset * id); | ||
float distance = 0.0; | ||
for (size_t k = 0; k < (size_t)dimDataset; k++) { | ||
float val_q = (float)(cur_query[k]); | ||
float val_d = (float)(cur_dataset[k]); | ||
if (metric == raft::distance::DistanceType::InnerProduct) { | ||
distance += -val_q * val_d; // Negate because we sort in scending order. | ||
} else { | ||
distance += (val_q - val_d) * (val_q - val_d); | ||
} | ||
} | ||
sfr[j].id = id; | ||
sfr[j].distance = distance; | ||
} | ||
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qsort(sfr, topK, sizeof(struct_for_refinement), _postprocessing_qsort_compare); | ||
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for (size_t j = 0; j < (size_t)refinedTopK; j++) { | ||
refinedNeighbors[j + (refinedTopK * i)] = sfr[j].id; | ||
if (refinedDistances == NULL) continue; | ||
if (metric == raft::distance::DistanceType::InnerProduct) { | ||
refinedDistances[j + (refinedTopK * i)] = -sfr[j].distance; | ||
} else { | ||
refinedDistances[j + (refinedTopK * i)] = -sfr[j].distance; | ||
} | ||
} | ||
} | ||
free(sfr); | ||
} | ||
} | ||
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} // namespace raft::neighbors::detail |
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Just a little note: I'm hoping to remove the raft::spatial::knn namespace altogether in 23.02 and officially move all the detail headers over to raft::neighbors. Hopefully we can get all the deprecated files removed as well.