GpuIndexFlat.h

/**
 * Copyright (c) 2015-present, Facebook, Inc.
 * All rights reserved.
 *
 * This source code is licensed under the CC-by-NC license found in the
 * LICENSE file in the root directory of this source tree.
 */

// Copyright 2004-present Facebook. All Rights Reserved.

#pragma once

#include "GpuIndex.h"

namespace faiss {

struct IndexFlat;
struct IndexFlatL2;
struct IndexFlatIP;

}

namespace faiss { namespace gpu {

struct FlatIndex;

/// Wrapper around the GPU implementation that looks like
/// faiss::IndexFlat; copies over centroid data from a given
/// faiss::IndexFlat
class GpuIndexFlat : public GpuIndex {
 public:
  /// Construct from a pre-existing faiss::IndexFlat instance, copying
  /// data over to the given GPU
  GpuIndexFlat(GpuResources* resources,
               int device,
               bool useFloat16,
               const faiss::IndexFlat* index);

  /// Construct an empty instance that can be added to
  GpuIndexFlat(GpuResources* resources,
               int device,
               int dims,
               bool useFloat16,
               faiss::MetricType metric);

  ~GpuIndexFlat() override;

  /// Set the minimum data size for searches (in MiB) for which we use
  /// CPU -> GPU paging
  void setMinPagingSize(size_t size);

  /// Returns the current minimum data size for paged searches
  size_t getMinPagingSize() const;

  /// Do we store vectors and perform math in float16?
  bool getUseFloat16() const;

  /// Initialize ourselves from the given CPU index; will overwrite
  /// all data in ourselves
  void copyFrom(const faiss::IndexFlat* index);

  /// Copy ourselves to the given CPU index; will overwrite all data
  /// in the index instance
  void copyTo(faiss::IndexFlat* index) const;

  /// Returns the number of vectors we contain
  size_t getNumVecs() const;

  /// Clears all vectors from this index
  void reset() override;

  /// This index is not trained, so this does nothing
  void train(Index::idx_t n, const float* x) override;

  /// `x` can be resident on the CPU or any GPU; the proper copies are
  /// performed
  void add(Index::idx_t n, const float* x) override;

  /// `x`, `distances` and `labels` can be resident on the CPU or any
  /// GPU; copies are performed as needed
  void search(faiss::Index::idx_t n,
              const float* x,
              faiss::Index::idx_t k,
              float* distances,
              faiss::Index::idx_t* labels) const override;

  /// Reconstruction methods; prefer the batch reconstruct as it will
  /// be more efficient
  void reconstruct(faiss::Index::idx_t key, float* out) const override;

  /// Batch reconstruction method
  void reconstruct_n(faiss::Index::idx_t i0,
                     faiss::Index::idx_t num,
                     float* out) const override;

  void set_typename() override;

  /// For internal access
  inline FlatIndex* getGpuData() { return data_; }

 protected:
  /// Called from search when the input data is on the CPU;
  /// potentially allows for pinned memory usage
  void searchFromCpuPaged_(int n,
                           const float* x,
                           int k,
                           float* outDistancesData,
                           int* outIndicesData) const;

  void searchNonPaged_(int n,
                       const float* x,
                       int k,
                       float* outDistancesData,
                       int* outIndicesData) const;

 protected:
  /// Size above which we page copies from the CPU to GPU
  size_t minPagedSize_;

  /// Whether or not we store our vectors in float32 or float16
  const bool useFloat16_;

  /// Holds our GPU data containing the list of vectors
  FlatIndex* data_;
};

/// Wrapper around the GPU implementation that looks like
/// faiss::IndexFlatL2; copies over centroid data from a given
/// faiss::IndexFlat
class GpuIndexFlatL2 : public GpuIndexFlat {
 public:
  /// Construct from a pre-existing faiss::IndexFlatL2 instance, copying
  /// data over to the given GPU
  GpuIndexFlatL2(GpuResources* resources,
                 int device,
                 bool useFloat16,
                 faiss::IndexFlatL2* index);

  /// Construct an empty instance that can be added to
  GpuIndexFlatL2(GpuResources* resources,
                 int device,
                 int dims,
                 bool useFloat16);

  /// Initialize ourselves from the given CPU index; will overwrite
  /// all data in ourselves
  void copyFrom(faiss::IndexFlatL2* index);

  /// Copy ourselves to the given CPU index; will overwrite all data
  /// in the index instance
  void copyTo(faiss::IndexFlatL2* index);
};

/// Wrapper around the GPU implementation that looks like
/// faiss::IndexFlatIP; copies over centroid data from a given
/// faiss::IndexFlat
class GpuIndexFlatIP : public GpuIndexFlat {
 public:
  /// Construct from a pre-existing faiss::IndexFlatIP instance, copying
  /// data over to the given GPU
  GpuIndexFlatIP(GpuResources* resources,
                 int device,
                 bool useFloat16,
                 faiss::IndexFlatIP* index);

  /// Construct an empty instance that can be added to
  GpuIndexFlatIP(GpuResources* resources,
                 int device,
                 int dims,
                 bool useFloat16);

  /// Initialize ourselves from the given CPU index; will overwrite
  /// all data in ourselves
  void copyFrom(faiss::IndexFlatIP* index);

  /// Copy ourselves to the given CPU index; will overwrite all data
  /// in the index instance
  void copyTo(faiss::IndexFlatIP* index);
};

} } // namespace