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GpuDistance.h
/**
* Copyright (c) 2015-present, Facebook, Inc.
* All rights reserved.
*
* This source code is licensed under the BSD+Patents license found in the
* LICENSE file in the root directory of this source tree.
*/
#pragma once
#include "../Index.h"
namespace faiss { namespace gpu {
class GpuResources;
/// A wrapper for gpu/impl/Distance.cuh to expose direct brute-force k-nearest
/// neighbor searches on an externally-provided region of memory (e.g., from a
/// pytorch tensor).
/// The data (vectors, queries, outDistances, outIndices) can be resident on the
/// GPU or the CPU, but all calculations are performed on the GPU. If the result
/// buffers are on the CPU, results will be copied back when done.
///
/// All GPU computation is performed on the current CUDA device, and ordered
/// with respect to resources->getDefaultStreamCurrentDevice().
///
/// For each vector in `queries`, searches all of `vectors` to find its k
/// nearest neighbors with respect to the given metric
void bruteForceKnn(GpuResources* resources,
faiss::MetricType metric,
// A region of memory size numVectors x dims, with dims
// innermost
const float* vectors,
int numVectors,
// A region of memory size numQueries x dims, with dims
// innermost
const float* queries,
int numQueries,
int dims,
int k,
// A region of memory size numQueries x k, with k
// innermost
float* outDistances,
// A region of memory size numQueries x k, with k
// innermost
faiss::Index::idx_t* outIndices);
} } // namespace
faiss::Index::idx_t
long idx_t
all indices are this type
Definition: Index.h:64
faiss::MetricType
MetricType
Some algorithms support both an inner product version and a L2 search version.
Definition: Index.h:45