File GpuIcmEncoder.h

namespace faiss

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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)

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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.

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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.

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The read functions return objects that should be deallocated with delete. All references within these objectes are owned by the object.

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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.

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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
class GpuIcmEncoder : public faiss::lsq::IcmEncoder
#include <GpuIcmEncoder.h>

Perform LSQ encoding on GPU.

Split input vectors to different devices and call IcmEncoderImpl::encode to encode them

Public Functions

GpuIcmEncoder(const LocalSearchQuantizer *lsq, const std::vector<GpuResourcesProvider*> &provs, const std::vector<int> &devices)
~GpuIcmEncoder()
GpuIcmEncoder(const GpuIcmEncoder&) = delete
GpuIcmEncoder &operator=(const GpuIcmEncoder&) = delete
virtual void set_binary_term() override
virtual void encode(int32_t *codes, const float *x, std::mt19937 &gen, size_t n, size_t ils_iters) const override

Encode vectors given codebooks

Parameters:
  • codes – output codes, size n * M

  • x – vectors to encode, size n * d

  • gen – random generator

  • n – number of vectors

  • ils_iters – number of iterations of iterative local search

Private Members

std::unique_ptr<IcmEncoderShards> shards
struct GpuIcmEncoderFactory : public faiss::lsq::IcmEncoderFactory

Public Functions

explicit GpuIcmEncoderFactory(int ngpus = 1)
virtual lsq::IcmEncoder *get(const LocalSearchQuantizer *lsq) override

Public Members

std::vector<GpuResourcesProvider*> provs
std::vector<int> devices