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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. It...
Fault tolerant, POSIX-compliant, Net Distributed Storage / File System
...It spreads data over several physical servers which are visible to the user as one resource. For standard file operations MooseFS mounted with FUSE acts as other Unix-alike file systems:
* A hierarchical structure (directory tree)
* Stores POSIX file attributes (permissions, last access and modification times)
Supports special files (block and character devices, pipes and sockets)
* Symbolic links (file names pointing to target files, not necessarily on MooseFS) and hard links (different names of files which refer to the same data on MooseFS)
* Access to the file system can be limited based on IP address and/or password
MooseFS on GitHub:
https://github.com/moosefs/moosefs
Packages repository, download:
https://moosefs.com/download
Documentation:
https://moosefs.com/support
Recent changes:
https://github.com/moosefs/moosefs/blob/master/NEWS
As of now, you can get Ehcache only from ehcache.org or Maven central.
A simple, fast, thread safe, standards based cache for Java, and provides memory and disk stores and distributed operation for clusters. ehcache is widely used in such open source projects as Hibernate and Spring. Terracotta offers enterprise edition