neuronika VS memberlist

Also perhaps comparing to Neuronika.

how does it compare with https://github.com/spearow/juice, https://github.com/neuronika/neuronika and https://github.com/spearow/juice?

Check where and how this struct is used. https://github.com/neuronika/neuronika/blob/variable-rework/neuronika-variable/src/history.rs

Also you can take a look at neuronika.

There is also https://github.com/neuronika/neuronika

I have a question: as the maintainer of [neuronika](https://github.com/neuronika/neuronika), a crate that offers dynamic neural network and auto-differentiation with dynamic graphs, I'm looking at a future possible feature for such framework consisting in the possibility of compiling models, getting thus rid of the "dynamic" part, which is not always needed. This would speed the inference and training times quite a bit.

If you like autograd you will love neuronika

After reading most of the book, I wanted to get my hands dirty. My initial idea was to build a small machine learning framework but I deemed it to be too difficult if not impossible for me at the time. (Now, neuronika would have something to say). When gathering the bibliography for my thesis, I recalled to have stumbled upon a particular algorithm, t-SNE, whom I liked very much. I found the idea behind it to be very clever and elegant (t-SNE it's still one of my favorite algorithms, together with backprop and SOM, I find manifold learning fascinating in general). "So be it", I said, and I began writing a mess of a code, that was basically a translation of the C++ implementation. Boy was it bad.

I use lightweight https://github.com/hashicorp/memberlist to build initial cluster skeleton (find out what are nodes constituting it)

Does https://github.com/hashicorp/memberlist count? It’s a gossip-based eventual consistency protocol based on SWIM.

An equivalent of golang's memberlist would be awesome.

I don't know the engineer that did it but I know what happened. There's a library that a bunch of foundational Amazon services use called DFDD. It uses a gossip protocol to handle service discovery and health checking. The open source equivalent is Hashicorp memberlist. To remove a node from the cluster, you have to send a command to an arbitrary node that says a node is dead.

serf uses memberlist which uses the SWIM failure detection protocol (https://www.cs.cornell.edu/projects/Quicksilver/public_pdfs/SWIM.pdf) with the Lifeguard extensions (https://arxiv.org/pdf/1707.00788.pdf).

https://github.com/hashicorp/memberlist

Fairly idiomatic/clean

This algorithm assumes you're doing that separately using some sort of membership protocol (e.g. SWIM), and you pass in the membership list that you are keeping up to date with that protocol. If you're curious about those, HashiCorp memberlist and HashiCorp Serf are really good to look at. I believe Consul uses those libraries under the hood.