daisy-exact-search 1.0.0

DaiSy: A Library for Scalable Data Series Similarity Search

DaiSy: A Library for Scalable Data Series Similarity Search

DaiSy (DAta series sImilarity sSearch librarY) is a unified library for exact data series similarity search that integrates multiple state-of-the-art algorithms within a single, coherent framework, developed at LIPADE, Université Paris Cit'e. It supports a wide range approaches tailored for different execution environments, including disk-based, in-memory, GPU-accelerated, and distributed scalable similarity search. DaiSy is implemented in C++, while it also offers a convenient Python interface for ease of use and integration with data science workflows.

Supported State-of-the-Art algorithms

We currently support several algorithms for exact similarity search, each optimized for specific use cases and environments. The following table summarizes the key features of each algorithm:

Algorithm	Description
Bruteforce	Naive parallel similarity search implementation
Lower Bound Bruteforce	Optimized bruteforce with lower bounding for the distance calculations
MESSI	In-memory parallel similarity search
PARIS	Disk-based parallel similarity search
SING	GPU-accelerated in-memory parallel similarity search
Odyssey	Distributed and parallel in-memory similarity search

Quickstart

Dependencies

• Operating System: Linux, macOS, or Windows
• C++ Compiler: C++14 or higher (GCC 6+, Clang 3.4+, MSVC 2015+)
• CMake: Version 3.15 or higher

Optionally,

• Python: 3.10-3.12
• MPI: Required for Odyssey distributed computing algorithm
• CUDA: Required for SING GPU acceleration algorithm

Installation

To download DaiSy, use:

git clone https://github.com/MChatzakis/daisy.git

cd daisy
git submodule update --init --recursive

Based on the available hardware, you can specify the below arguments to enable/disable features.

Flag	Description	Default	Dependencies
BUILD_PYTHON	Enable Python bindings	ON	Python 3.10+
BUILD_BENCHMARK	Build benchmarking tools	ON	GoogleBenchmark
BUILD_TESTS	Build test suite	ON	GoogleTest
BUILD_DEMO	Build demonstration applications	ON	Core library
ODYSSEY_MPI	Enable MPI for distributed computing	ON	OpenMPI/MPICH
SING_CUDA	Enable CUDA for GPU acceleration	ON	CUDA Toolkit
DEBUG_MSG	Enable debug output	OFF	None

To compile:

mkdir build && cd build

cmake ..
make

Enable Python

python3.12 -m venv DaiSy_env

source DaiSy_env/bin/activate 
pip install -r requirements_DaiSy.txt

Example Usage

We provide several usage examples in both C++ and Python under demos/, demonstrating how to utilize the library for various similarity search tasks.

About

DaiSy is developed by the diNo research group at LIPADE, Université Paris Cité. It is provided with no warranty, and we encourage contributions from the community to enhance its capabilities and performance. For questions, issues, or contributions, please open an issue or submit a pull request on GitHub. DaiSy licensed under the MIT License.