File simdlib_emulated.h
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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.
Functions
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inline simd16uint16 min(const simd16uint16 &av, const simd16uint16 &bv)
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inline simd16uint16 max(const simd16uint16 &av, const simd16uint16 &bv)
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inline simd16uint16 combine2x2(const simd16uint16 &a, const simd16uint16 &b)
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inline uint32_t cmp_ge32(const simd16uint16 &d0, const simd16uint16 &d1, const simd16uint16 &thr)
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inline uint32_t cmp_le32(const simd16uint16 &d0, const simd16uint16 &d1, const simd16uint16 &thr)
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inline simd32uint8 uint16_to_uint8_saturate(const simd16uint16 &a, const simd16uint16 &b)
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inline uint32_t get_MSBs(const simd32uint8 &a)
get most significant bit of each byte
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inline simd32uint8 blendv(const simd32uint8 &a, const simd32uint8 &b, const simd32uint8 &mask)
use MSB of each byte of mask to select a byte between a and b
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inline simd8float32 hadd(const simd8float32 &a, const simd8float32 &b)
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inline simd8float32 unpacklo(const simd8float32 &a, const simd8float32 &b)
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inline simd8float32 unpackhi(const simd8float32 &a, const simd8float32 &b)
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inline simd8float32 fmadd(const simd8float32 &a, const simd8float32 &b, const simd8float32 &c)
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struct simd256bit
- #include <simdlib_avx2.h>
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struct simd16uint16 : public faiss::simd256bit, public faiss::simd256bit
- #include <simdlib_avx2.h>
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struct simd32uint8 : public faiss::simd256bit, public faiss::simd256bit
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struct simd8uint32 : public faiss::simd256bit, public faiss::simd256bit
- #include <simdlib_avx2.h>
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struct simd8float32 : public faiss::simd256bit, public faiss::simd256bit
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inline simd16uint16 min(const simd16uint16 &av, const simd16uint16 &bv)