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Add ANN refinement method #1038

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1 change: 1 addition & 0 deletions cpp/bench/CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -124,6 +124,7 @@ if(BUILD_BENCH)
bench/neighbors/knn/ivf_pq_float_uint32_t.cu
bench/neighbors/knn/ivf_pq_int8_t_int64_t.cu
bench/neighbors/knn/ivf_pq_uint8_t_uint32_t.cu
bench/neighbors/refine.cu
bench/neighbors/selection.cu
bench/main.cpp
OPTIONAL
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122 changes: 122 additions & 0 deletions cpp/bench/neighbors/refine.cu
Original file line number Diff line number Diff line change
@@ -0,0 +1,122 @@
/*
* 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.
*/

#include <common/benchmark.hpp>

#include <raft/random/rng.cuh>

#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>

#if defined RAFT_DISTANCE_COMPILED
#include <raft/distance/specializations.cuh>
#endif

#if defined RAFT_NN_COMPILED
#include <raft/spatial/knn/specializations.cuh>
#endif

#include <rmm/cuda_stream_view.hpp>
#include <rmm/mr/device/per_device_resource.hpp>
#include <rmm/mr/device/pool_memory_resource.hpp>

#include "../../test/neighbors/refine_helper.cuh"

#include <iostream>
#include <sstream>

using namespace raft::neighbors::detail;

namespace raft::bench::neighbors {

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;
}

RefineInputs<int64_t> p;

template <typename DataT, typename DistanceT, typename IdxT>
class RefineAnn : public fixture {
public:
RefineAnn(RefineInputs<IdxT> p) : data(handle_, p) {}

void run_benchmark(::benchmark::State& state) override
{
std::ostringstream label_stream;
label_stream << data.p;
state.SetLabel(label_stream.str());

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);

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);
}

private:
raft::handle_t handle_;
RefineHelper<DataT, DistanceT, IdxT> data;
};

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;
}

using refine_float_int64 = RefineAnn<float, float, int64_t>;
RAFT_BENCH_REGISTER(refine_float_int64, "", getInputs());

using refine_uint8_int64 = RefineAnn<uint8_t, float, int64_t>;
RAFT_BENCH_REGISTER(refine_uint8_int64, "", getInputs());
} // namespace raft::bench::neighbors
232 changes: 232 additions & 0 deletions cpp/include/raft/neighbors/detail/refine.cuh
Original file line number Diff line number Diff line change
@@ -0,0 +1,232 @@
/*
* 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.
*/

#pragma once

#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>

#include <cstdlib>
#include <omp.h>

#include <thrust/sequence.h>

namespace raft::neighbors::detail {

/** 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);

RAFT_EXPECTS(k <= raft::spatial::knn::detail::topk::kMaxCapacity,
"k must be lest than topk::kMaxCapacity (%d).",
raft::spatial::knn::detail::topk::kMaxCapacity);

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.");

RAFT_EXPECTS(indices.extent(1) == k,
"Number of columns in output indices and distances matrices must be equal to k");

RAFT_EXPECTS(queries.extent(1) == dataset.extent(1),
"Number of columns must be equal for dataset and queries");

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));
}

/**
* 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));

common::nvtx::range<common::nvtx::domain::raft> fun_scope(
"neighbors::refine(%zu, %u)", size_t(n_queries), uint32_t(n_candidates));

check_input(dataset.extents(),
queries.extents(),
neighbor_candidates.extents(),
indices.extents(),
distances.extents(),
metric);

// 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());

thrust::sequence(
handle.get_thrust_policy(), fake_coarse_idx.data(), fake_coarse_idx.data() + n_queries);

raft::neighbors::ivf_flat::index<data_t, idx_t> refinement_index(
handle, metric, n_queries, false, dim);

raft::spatial::knn::ivf_flat::detail::fill_refinement_index(handle,
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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.

&refinement_index,
dataset.data_handle(),
neighbor_candidates.data_handle(),
n_queries,
n_candidates);

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());
}

/** Helper structure for naive CPU implementation of refine. */
typedef struct {
uint64_t id;
float distance;
} struct_for_refinement;

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;
}
}

/**
* 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);

switch (metric) {
case raft::distance::DistanceType::L2Expanded: break;
case raft::distance::DistanceType::InnerProduct: break;
default: throw raft::logic_error("Unsopported metric");
}

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();

common::nvtx::range<common::nvtx::domain::raft> fun_scope(
"neighbors::refine_host(%zu, %u)", size_t(numQueries), uint32_t(topK));

#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;
}

qsort(sfr, topK, sizeof(struct_for_refinement), _postprocessing_qsort_compare);

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);
}
}

} // namespace raft::neighbors::detail
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