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Library for efficient similarity search and clustering dense vectors
Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. ...
A collection of implementations of the Paxos and FastPaxos algorithms for solving consensus in a network of unreliable processors. Visit http://libpaxos.sourceforge.net/ for more informations
Channel is a C++ framework for distributed message passing and event dispatching, configurable with its components (msg ids,routing algorithms...) as template parameters. As a namespace shared by peer threads, channel supports scope control and filtering
NOD-MP stands for not another data-mining project. It is educational and scientific software to utilize data mining clustering algorithms through a user-friendly interface.