File StackDeviceMemory.h
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namespace faiss
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)
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.
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.
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.
Definition of inverted lists + a few common classes that implement the interface.
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.
In this file are the implementations of extra metrics beyond L2 and inner product
Implements a few neural net layers, mainly to support QINCo
Defines a few objects that apply transformations to a set of vectors Often these are pre-processing steps.
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namespace gpu
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class StackDeviceMemory
- #include <StackDeviceMemory.h>
Device memory manager that provides temporary memory allocations out of a region of memory, for a single device
Public Functions
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StackDeviceMemory(GpuResources *res, int device, size_t allocPerDevice)
Allocate a new region of memory that we manage.
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StackDeviceMemory(int device, void *p, size_t size, bool isOwner)
Manage a region of memory for a particular device, with or without ownership
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~StackDeviceMemory()
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int getDevice() const
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void *allocMemory(cudaStream_t stream, size_t size)
All allocations requested should be a multiple of 16 bytes.
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void deallocMemory(int device, cudaStream_t, size_t size, void *p)
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size_t getSizeAvailable() const
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std::string toString() const
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struct Range
- #include <StackDeviceMemory.h>
Previous allocation ranges and the streams for which synchronization is required
Public Functions
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inline Range(char *s, char *e, cudaStream_t str)
Public Members
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char *start_
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char *end_
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cudaStream_t stream_
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inline Range(char *s, char *e, cudaStream_t str)
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struct Stack
Public Functions
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Stack(GpuResources *res, int device, size_t size)
Constructor that allocates memory via cudaMalloc.
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~Stack()
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size_t getSizeAvailable() const
Returns how much size is available for an allocation without calling cudaMalloc
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char *getAlloc(size_t size, cudaStream_t stream)
Obtains an allocation; all allocations are guaranteed to be 16 byte aligned
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void returnAlloc(char *p, size_t size, cudaStream_t stream)
Returns an allocation.
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std::string toString() const
Returns the stack state.
Public Members
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GpuResources *res_
Our GpuResources object.
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int device_
Device this allocation is on.
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char *alloc_
Where our temporary memory buffer is allocated; we allocate starting 16 bytes into this
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size_t allocSize_
Total size of our allocation.
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char *start_
Our temporary memory region; [start_, end_) is valid.
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char *end_
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char *head_
Stack head within [start, end)
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std::list<Range> lastUsers_
List of previous last users of allocations on our stack, for possible synchronization purposes
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size_t highWaterMemoryUsed_
What’s the high water mark in terms of memory used from the temporary buffer?
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Stack(GpuResources *res, int device, size_t size)
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StackDeviceMemory(GpuResources *res, int device, size_t allocPerDevice)
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class StackDeviceMemory
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namespace gpu