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I'm working on a project right now where I'm trying to implement the NEAT (Neuroevolution of Augmenting Topologies) methodology to a neural network. This has already been done many times over and there have even been updated revisions to the methodology over the past several years in several languages, so I'm not producing anything new at the moment. My little "twist" to the methodology is to attempt a distributed implementation (preferably through MapReduce jobs, although MPI is also a possible choice). I'm wondering if anyone has ever come across a "good" model of a distributed ANN? I've tried a few different Google searches, but have come up with nothing of value.

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MapReduce has commonly been affiliated with cloud computing and large-scale datasets. Widely deployment and application at industry associations have thrust this programming framework to the forefront of cloud computing and data processing application domain. For more information regarding the same, refer to the following link: https://pdfs.semanticscholar.org/f36c/f57212c748599e8e9cbac6c63d0b46386b60.pdf

For MPI you could check this paper Parallel implementations of feed-forward neural network using MPI and C# on the .NET platform: http://laspp.fri.uni-lj.si/uros/docs/icannga2005u.pdf

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