* [Caml-list] ANN: parallpairs
@ 2017-02-08 6:30 Eray Ozkural
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From: Eray Ozkural @ 2017-02-08 6:30 UTC (permalink / raw)
To: Caml List
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---> https://github.com/examachine/parallpairs
Parallel all-pairs similarity search algorithms in OCaml
If you use this code, please cite the following paper. It is currently
under review at IJPP.
https://arxiv.org/abs/1402.3010
1-D and 2-D Parallel Algorithms for All-Pairs Similarity Problem
Eray Özkural, Cevdet Aykanat (Submitted on 13 Feb 2014)
All-pairs similarity problem asks to find all vector pairs in a set of
vectors the similarities of which surpass a given similarity threshold, and
it is a computational kernel in data mining and information retrieval for
several tasks. We investigate the parallelization of a recent fast
sequential algorithm. We propose effective 1-D and 2-D data distribution
strategies that preserve the essential optimizations in the fast algorithm.
1-D parallel algorithms distribute either dimensions or vectors, whereas
the 2-D parallel algorithm distributes data both ways. Additional
contributions to the 1-D vertical distribution include a local pruning
strategy to reduce the number of candidates, a recursive pruning algorithm,
and block processing to reduce imbalance. The parallel algorithms were
programmed in OCaml which affords much convenience. Our experiments
indicate that the performance depends on the dataset, therefore a variety
of parallelizations is useful.
The code is quite interesting, as it shows how to effectively use OCaml for
MPI code. There is a bunch of well-written parallel functional code that I
will extract from this codebase and release separately. You need the latest
ocamlmpi release as that contains the patches I made to make this code work.
This code is released under AGPL-3.0. Please do not ask me to release it
under BSD license. If you need a commercial license, you should purchase it.
Happy hacking!
Eray Ozkural, PhD
--
Eray Ozkural, PhD. Computer Scientist
Founder, Gok Us Sibernetik Ar&Ge Ltd.
http://groups.yahoo.com/group/ai-philosophy
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