File GpuIndexBinaryFlat.h
-
namespace faiss
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree.
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. Implementation of k-means clustering with many variants.
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. IDSelector is intended to define a subset of vectors to handle (for removal or as subset to search)
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. PQ4 SIMD packing and accumulation functions
The basic kernel accumulates nq query vectors with bbs = nb * 2 * 16 vectors and produces an output matrix for that. It is interesting for nq * nb <= 4, otherwise register spilling becomes too large.
The implementation of these functions is spread over 3 cpp files to reduce parallel compile times. Templates are instantiated explicitly.
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. This file contains callbacks for kernels that compute distances.
Throughout the library, vectors are provided as float * pointers. Most algorithms can be optimized when several vectors are processed (added/searched) together in a batch. In this case, they are passed in as a matrix. When n vectors of size d are provided as float * x, component j of vector i is
x[ i * d + j ]
where 0 <= i < n and 0 <= j < d. In other words, matrices are always compact. When specifying the size of the matrix, we call it an n*d matrix, which implies a row-major storage.
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. I/O functions can read/write to a filename, a file handle or to an object that abstracts the medium.
The read functions return objects that should be deallocated with delete. All references within these objectes are owned by the object.
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. Definition of inverted lists + a few common classes that implement the interface.
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. Since IVF (inverted file) indexes are of so much use for large-scale use cases, we group a few functions related to them in this small library. Most functions work both on IndexIVFs and IndexIVFs embedded within an IndexPreTransform.
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. In this file are the implementations of extra metrics beyond L2 and inner product
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. Defines a few objects that apply transformations to a set of vectors Often these are pre-processing steps.
-
namespace gpu
-
struct GpuIndexBinaryFlatConfig : public faiss::gpu::GpuIndexConfig
-
class GpuIndexBinaryFlat : public faiss::IndexBinary
- #include <GpuIndexBinaryFlat.h>
A GPU version of IndexBinaryFlat for brute-force comparison of bit vectors via Hamming distance
Public Functions
-
GpuIndexBinaryFlat(GpuResourcesProvider *resources, const faiss::IndexBinaryFlat *index, GpuIndexBinaryFlatConfig config = GpuIndexBinaryFlatConfig())
Construct from a pre-existing faiss::IndexBinaryFlat instance, copying data over to the given GPU
-
GpuIndexBinaryFlat(GpuResourcesProvider *resources, int dims, GpuIndexBinaryFlatConfig config = GpuIndexBinaryFlatConfig())
Construct an empty instance that can be added to.
-
~GpuIndexBinaryFlat() override
-
int getDevice() const
Returns the device that this index is resident on.
-
std::shared_ptr<GpuResources> getResources()
Returns a reference to our GpuResources object that manages memory, stream and handle resources on the GPU
-
void copyFrom(const faiss::IndexBinaryFlat *index)
Initialize ourselves from the given CPU index; will overwrite all data in ourselves
-
void copyTo(faiss::IndexBinaryFlat *index) const
Copy ourselves to the given CPU index; will overwrite all data in the index instance
-
virtual void add(faiss::idx_t n, const uint8_t *x) override
Add n vectors of dimension d to the index.
Vectors are implicitly assigned labels ntotal .. ntotal + n - 1
- Parameters:
x – input matrix, size n * d / 8
-
virtual void reset() override
Removes all elements from the database.
-
virtual void search(idx_t n, const uint8_t *x, idx_t k, int32_t *distances, faiss::idx_t *labels, const faiss::SearchParameters *params = nullptr) const override
Query n vectors of dimension d to the index.
return at most k vectors. If there are not enough results for a query, the result array is padded with -1s.
- Parameters:
x – input vectors to search, size n * d / 8
labels – output labels of the NNs, size n*k
distances – output pairwise distances, size n*k
Protected Functions
Protected Attributes
-
std::shared_ptr<GpuResources> resources_
Manages streans, cuBLAS handles and scratch memory for devices.
-
const GpuIndexBinaryFlatConfig binaryFlatConfig_
Configuration options.
-
std::unique_ptr<BinaryFlatIndex> data_
Holds our GPU data containing the list of vectors.
-
GpuIndexBinaryFlat(GpuResourcesProvider *resources, const faiss::IndexBinaryFlat *index, GpuIndexBinaryFlatConfig config = GpuIndexBinaryFlatConfig())
-
struct GpuIndexBinaryFlatConfig : public faiss::gpu::GpuIndexConfig
-
namespace gpu