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PANENE

PANENE (Progressive Approximate k-NEarest NEighbors) is a novel algorithm for the k-nearest neighbor (KNN) problem. In contrast to previous algorithms such as Annoy, FLANN, or many others from this benchmark, PANENE is progressive: it can process multiple mini-batches online while keeping each iteration bounded in time.

PANENE consists of two modules:

  • A progressive k-d tree that allows you to index a batch of data into multiple k-d trees (i.e., a k-d tree forest) and query the neighbors of an arbitrary point
  • A KNN table that allows you to lookup the neighbors of a training point in a constant time

The running time of both modules can be controlled by specifiying the allowed number of operations (i.e., ops). See the examples below.

Installation

The source code was compiled and tested on Ubuntu 16.04 and macOS. The instructions below assume that you are using Ubuntu 16.04. If you are using macOS, please use an appropriate package manager (e.g., brew instead of apt)

Prerequisites:

  • A C++ compiler with OpenMP and C++ 11 support
  • Python 3.6 (we recommend to use Anaconda)
  • CMake

Download the source code:

git clone https://github.com/e-/PANENE.git
cd PANENE

Check if the system has CMake:

cmake

# if you don't have CMake, run the following command:
sudo apt install cmake

Check if the system has g++. Note that PANENE requires the OpenMP support. Most recent compilers support it by default:

g++

# if you don't have g++, run the following command:
sudo apt install g++

Build the source code:

mkdir build
cd build
cmake ..
make

Install PANENE:

sudo make install

Update the shared library links after installation:

sudo ldconfig

Running the Benchmark

Download the glove dataset and generate training and testing data (from the root directory):

cd data
./download.sh glove

Compute the exact neighbors of the testing data (this can take a while):

cp ../build/benchmark/answer .
./answer.sh glove

Run one of benchmarks (kd_tree_benchmark or knn_table_benchmark):

cd ..
cd build/benchmark
./kd_tree_benchmark
cat log.tsv

Compile on Windows

If you are using Windows, the easiest way to use PANENE is compiling it using Visual Studio, since Visual Studio (>= 15) supports CMakeLists.txt

  • Clone the repository
  • Open Visual Studio
  • Click on [File] -> [Open] -> [Folder] and select the directory
  • Find the root CMakeLists.txt in Solution Explorer, right-click it, and select [Cache] -> [Generate Cache]
  • Choose a target executable on the upper toolbar and Run

If you are running benchmarks, you must specify the absolute path of data files. This is because Visual Stduio compiles and runs executables in a temporary folder by default, so you need to specifiy the absolute path to make the executables locate the data.

Please see the main function of benchmark/kd_tree_benchmark.cpp and benchmark/knn_table_benchmark.cpp.