Updated NeuronRain FAQ - https://neuronrain-documentation.readthedocs…

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index.rst

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 **Is NeuronRain production deployment ready? Is it scalable?**
 
-Presently complete GitHub and SourceForge repositories for NeuronRain are contributed (committed, designed and quality assured) by a single person without any funding (K.Srinivasan - http://sites.google.com/site/kuja27) with no team or commercial entity involved in it. This requires considerable time and effort to write a bug-free code. Though functionalities are tested sufficiently there could be untested code paths. Automated unit testing framework has not been integrated yet. Note of caution: though significant code has gone in both GitHub and Sourceforge repositories there is still a lot to be done in terms of cleaning, documentation, standards, QA etc., So it is upto the end-user to decide. There are no scalability benchmarks as of now though some AsFer Spark Cloud implementations - Recursive Gloss Overlap Intrinsic Merit, Computational Geometric Factorization - and Approximate Least Squares SAT Solver have been benchmarked on single node cluster. VIRGO system calls-kernel modules transport has been tested on a 2 node cluster. Presently, NeuronRain is almost like a beta version, though source codes in GitHub and SourceForge are release tagged periodically for checkpoint snapshot. Deployments on large clouds for academic research are encouraged (e.g VIRGO system calls/drivers and kernel analytics for IoT, Spark Recursive Gloss Overlap Interview Intrinsic Merit, Graph Tensor Neuron Network Recursive Lambda Function Growth Intrinsic Merit, Spark Computational Geometric Factorization on large clusters-specifically Bitonic Sort and Local Segment Binary Search, Approximate least squares CNF SAT solver for millions of variables and clauses). Production/Commercial deployments are subject to caveats and licensing terms mentioned in this FAQ.
+Presently complete GitHub and SourceForge repositories for NeuronRain are contributed (committed, designed and quality assured) by a single person without any funding (K.Srinivasan - http://sites.google.com/site/kuja27) with no team or commercial entity involved in it. This requires considerable time and effort to write a bug-free code. Though functionalities are tested sufficiently there could be untested code paths. Automated unit testing framework has not been integrated yet. Note of caution: though significant code has gone in both GitHub and Sourceforge repositories there is still a lot to be done in terms of cleaning, documentation, standards, QA etc., So it is upto the end-user to decide. There are no scalability benchmarks as of now though some AsFer Spark Cloud implementations - Recursive Gloss Overlap Intrinsic Merit, Computational Geometric Factorization - and Approximate Least Squares SAT Solver have been benchmarked on single node cluster. VIRGO system calls-kernel modules transport has been tested on a 2 node cluster. Presently, NeuronRain is almost like a beta version, though source codes in GitHub and SourceForge are release tagged periodically for checkpoint snapshot (Most recent release version: 18.10.06). Deployments on large clouds for academic research are encouraged (e.g VIRGO system calls/drivers and kernel analytics for IoT, Spark Recursive Gloss Overlap Interview Intrinsic Merit, Graph Tensor Neuron Network Recursive Lambda Function Growth Intrinsic Merit, Spark Computational Geometric Factorization on large clusters-specifically Bitonic Sort and Local Segment Binary Search, Approximate least squares CNF SAT solver for millions of variables and clauses). Production/Commercial deployments are subject to caveats and licensing terms mentioned in this FAQ.
 
 **Are there any demonstrative tutorial usecases/examples on how NeuronRain VIRGO system calls and drivers work?**