Bruteforce#
The bruteforce method is running the KNN algorithm. It performs an extensive search, and in contrast to ANN methods produces an exact result.
#include <cuvs/neighbors/bruteforce.hpp>
namespace cuvs::neighbors::bruteforce
Index#
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template<typename T, typename DistT = T>
struct index : public cuvs::neighbors::index# - #include <brute_force.hpp>
Brute Force index.
The index stores the dataset and norms for the dataset in device memory.
- Template Parameters:
T – data element type
Public Functions
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index(raft::resources const &res, raft::host_matrix_view<const T, int64_t, raft::row_major> dataset_view, std::optional<raft::device_vector<DistT, int64_t>> &&norms, cuvs::distance::DistanceType metric, DistT metric_arg = 0.0)#
Construct a brute force index from dataset
Constructs a brute force index from a dataset. This lets us precompute norms for the dataset, providing a speed benefit over doing this at query time. This index will copy the host dataset onto the device, and take ownership of any precaculated norms.
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index(raft::resources const &res, raft::device_matrix_view<const T, int64_t, raft::row_major> dataset_view, std::optional<raft::device_vector<DistT, int64_t>> &&norms, cuvs::distance::DistanceType metric, DistT metric_arg = 0.0)#
Construct a brute force index from dataset
Constructs a brute force index from a dataset. This lets us precompute norms for the dataset, providing a speed benefit over doing this at query time. This index will store a non-owning reference to the dataset, but will move any norms supplied.
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index(raft::resources const &res, raft::device_matrix_view<const T, int64_t, raft::row_major> dataset_view, std::optional<raft::device_vector_view<const DistT, int64_t>> norms_view, cuvs::distance::DistanceType metric, DistT metric_arg = 0.0)#
Construct a brute force index from dataset
This class stores a non-owning reference to the dataset and norms. Having precomputed norms gives us a performance advantage at query time.
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index(raft::resources const &res, raft::device_matrix_view<const T, int64_t, raft::col_major> dataset_view, std::optional<raft::device_vector<DistT, int64_t>> &&norms, cuvs::distance::DistanceType metric, DistT metric_arg = 0.0)#
Construct a brute force index from dataset
Constructs a brute force index from a dataset. This lets us precompute norms for the dataset, providing a speed benefit over doing this at query time. This index will store a non-owning reference to the dataset, but will move any norms supplied.
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index(raft::resources const &res, raft::device_matrix_view<const T, int64_t, raft::col_major> dataset_view, std::optional<raft::device_vector_view<const DistT, int64_t>> norms_view, cuvs::distance::DistanceType metric, DistT metric_arg = 0.0)#
Construct a brute force index from dataset
This class stores a non-owning reference to the dataset and norms, with the dataset being supplied on device in a col_major format
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void update_dataset(raft::resources const &res, raft::device_matrix_view<const T, int64_t, raft::row_major> dataset)#
Replace the dataset with a new dataset.
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void update_dataset(raft::resources const &res, raft::host_matrix_view<const T, int64_t, raft::row_major> dataset)#
Replace the dataset with a new dataset.
We create a copy of the dataset on the device. The index manages the lifetime of this copy.
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inline cuvs::distance::DistanceType metric() const noexcept#
Distance metric used for retrieval
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inline size_t size() const noexcept#
Total length of the index (number of vectors).
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inline size_t dim() const noexcept#
Dimensionality of the data.
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inline raft::device_matrix_view<const T, int64_t, raft::row_major> dataset() const noexcept#
Dataset [size, dim]
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inline bool has_norms() const noexcept#
Whether ot not this index has dataset norms
Index build#
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cuvs::neighbors::brute_force::index<float, float> build(raft::resources const &handle, raft::device_matrix_view<const float, int64_t, raft::row_major> dataset, cuvs::distance::DistanceType metric = cuvs::distance::DistanceType::L2Unexpanded, float metric_arg = 0)#
Build the index from the dataset for efficient search.
Usage example:
using namespace cuvs::neighbors; // create and fill the index from a [N, D] dataset auto index = brute_force::build(handle, dataset, metric);
- Parameters:
handle – [in]
dataset – [in] a device pointer to a row-major matrix [n_rows, dim]
metric – [in] cuvs::distance::DistanceType
metric_arg – [in] metric argument
- Returns:
the constructed brute-force index
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cuvs::neighbors::brute_force::index<half, float> build(raft::resources const &handle, raft::device_matrix_view<const half, int64_t, raft::row_major> dataset, cuvs::distance::DistanceType metric = cuvs::distance::DistanceType::L2Unexpanded, float metric_arg = 0)#
Build the index from the dataset for efficient search.
Usage example:
using namespace cuvs::neighbors; // create and fill the index from a [N, D] dataset auto index = brute_force::build(handle, dataset, metric);
- Parameters:
handle – [in]
dataset – [in] a device pointer to a row-major matrix [n_rows, dim]
metric – [in] cuvs::distance::DistanceType
metric_arg – [in] metric argument
- Returns:
the constructed ivf-flat index
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cuvs::neighbors::brute_force::index<float, float> build(raft::resources const &handle, raft::device_matrix_view<const float, int64_t, raft::col_major> dataset, cuvs::distance::DistanceType metric = cuvs::distance::DistanceType::L2Unexpanded, float metric_arg = 0)#
Build the index from the dataset for efficient search.
Usage example:
using namespace cuvs::neighbors; // create and fill the index from a [N, D] dataset auto index = brute_force::build(handle, dataset, metric);
- Parameters:
handle – [in]
dataset – [in] a device pointer to a col-major matrix [n_rows, dim]
metric – [in] cuvs::distance::DistanceType
metric_arg – [in] metric argument
- Returns:
the constructed bruteforce index
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cuvs::neighbors::brute_force::index<half, float> build(raft::resources const &handle, raft::device_matrix_view<const half, int64_t, raft::col_major> dataset, cuvs::distance::DistanceType metric = cuvs::distance::DistanceType::L2Unexpanded, float metric_arg = 0)#
Build the index from the dataset for efficient search.
Usage example:
using namespace cuvs::neighbors; // create and fill the index from a [N, D] dataset auto index = brute_force::build(handle, dataset, metric);
- Parameters:
handle – [in]
dataset – [in] a device pointer to a col-major matrix [n_rows, dim]
metric – [in] cuvs::distance::DistanceType
metric_arg – [in] metric argument
- Returns:
the constructed bruteforce index
Index search#
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void search(raft::resources const &handle, const cuvs::neighbors::brute_force::index<float, float> &index, raft::device_matrix_view<const float, int64_t, raft::row_major> queries, raft::device_matrix_view<int64_t, int64_t, raft::row_major> neighbors, raft::device_matrix_view<float, int64_t, raft::row_major> distances, const cuvs::neighbors::filtering::base_filter &sample_filter = cuvs::neighbors::filtering::none_sample_filter{})#
Search ANN using the constructed index.
See the brute_force::build documentation for a usage example.
Note, this function requires a temporary buffer to store intermediate results between cuda kernel calls, which may lead to undesirable allocations and slowdown. To alleviate the problem, you can pass a pool memory resource or a large enough pre-allocated memory resource to reduce or eliminate entirely allocations happening within
search
:... // Use the same allocator across multiple searches to reduce the number of // cuda memory allocations brute_force::search(handle, index, queries1, out_inds1, out_dists1); brute_force::search(handle, index, queries2, out_inds2, out_dists2); brute_force::search(handle, index, queries3, out_inds3, out_dists3); ...
- Parameters:
handle – [in]
index – [in] brute-force constructed index
queries – [in] a device pointer to a row-major matrix [n_queries, index->dim()]
neighbors – [out] a device pointer to the indices of the neighbors in the source dataset [n_queries, k]
distances – [out] a device pointer to the distances to the selected neighbors [n_queries, k]
sample_filter – [in] An optional device bitmap filter function with a
row-major
layout and the shape of [n_queries, index->size()], which means the filter will use the firstindex->size()
bits to indicate whether queries[0] should compute the distance with dataset.
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void search(raft::resources const &handle, const cuvs::neighbors::brute_force::index<half, float> &index, raft::device_matrix_view<const half, int64_t, raft::row_major> queries, raft::device_matrix_view<int64_t, int64_t, raft::row_major> neighbors, raft::device_matrix_view<float, int64_t, raft::row_major> distances, const cuvs::neighbors::filtering::base_filter &sample_filter = cuvs::neighbors::filtering::none_sample_filter{})#
Search ANN using the constructed index.
See the brute_force::build documentation for a usage example.
Note, this function requires a temporary buffer to store intermediate results between cuda kernel calls, which may lead to undesirable allocations and slowdown. To alleviate the problem, you can pass a pool memory resource or a large enough pre-allocated memory resource to reduce or eliminate entirely allocations happening within
search
:... // Use the same allocator across multiple searches to reduce the number of // cuda memory allocations brute_force::search(handle, index, queries1, out_inds1, out_dists1); brute_force::search(handle, index, queries2, out_inds2, out_dists2); brute_force::search(handle, index, queries3, out_inds3, out_dists3); ...
- Parameters:
handle – [in]
index – [in] ivf-flat constructed index
queries – [in] a device pointer to a row-major matrix [n_queries, index->dim()]
neighbors – [out] a device pointer to the indices of the neighbors in the source dataset [n_queries, k]
distances – [out] a device pointer to the distances to the selected neighbors [n_queries, k]
sample_filter – [in] a optional device bitmap filter function that greenlights samples for a given
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void search(raft::resources const &handle, const cuvs::neighbors::brute_force::index<float, float> &index, raft::device_matrix_view<const float, int64_t, raft::col_major> queries, raft::device_matrix_view<int64_t, int64_t, raft::row_major> neighbors, raft::device_matrix_view<float, int64_t, raft::row_major> distances, const cuvs::neighbors::filtering::base_filter &sample_filter = cuvs::neighbors::filtering::none_sample_filter{})#
Search ANN using the constructed index.
See the brute_force::build documentation for a usage example.
- Parameters:
handle – [in]
index – [in] bruteforce constructed index
queries – [in] a device pointer to a col-major matrix [n_queries, index->dim()]
neighbors – [out] a device pointer to the indices of the neighbors in the source dataset [n_queries, k]
distances – [out] a device pointer to the distances to the selected neighbors [n_queries, k]
sample_filter – [in] an optional device bitmap filter function that greenlights samples for a given query
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void search(raft::resources const &handle, const cuvs::neighbors::brute_force::index<half, float> &index, raft::device_matrix_view<const half, int64_t, raft::col_major> queries, raft::device_matrix_view<int64_t, int64_t, raft::row_major> neighbors, raft::device_matrix_view<float, int64_t, raft::row_major> distances, const cuvs::neighbors::filtering::base_filter &sample_filter = cuvs::neighbors::filtering::none_sample_filter{})#
Search ANN using the constructed index.
See the brute_force::build documentation for a usage example.
- Parameters:
handle – [in]
index – [in] bruteforce constructed index
queries – [in] a device pointer to a col-major matrix [n_queries, index->dim()]
neighbors – [out] a device pointer to the indices of the neighbors in the source dataset [n_queries, k]
distances – [out] a device pointer to the distances to the selected neighbors [n_queries, k]
sample_filter – [in] an optional device bitmap filter function that greenlights samples for a given query