brainjs/brain-cluster — explained in plain English
Analysis updated 2026-07-20 · repo last pushed 2018-03-11
Spread a large brain.js training job across multiple machines when one is too slow.
Experiment with how processes pass messages to each other in JavaScript.
Explore distributed neural network training concepts at an early stage.
| brainjs/brain-cluster | 0xpira/sskills | arulsebastin71/smartqueue | |
|---|---|---|---|
| Stars | 25 | 25 | 25 |
| Language | JavaScript | JavaScript | JavaScript |
| Last pushed | 2018-03-11 | — | — |
| Maintenance | Dormant | — | — |
| Setup difficulty | hard | easy | moderate |
| Complexity | 4/5 | 2/5 | 3/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires installing the klyng package globally, running a background beacon service on port 2222, and navigating an incomplete cluster configuration that is still hard-coded to a specific test problem.
Brain-cluster is an experimental add-on for brain.js, a JavaScript library that lets you build and train neural networks in the browser or on a server. Its goal is to let a network learn faster by splitting the training work across multiple processes or even multiple computers, instead of doing it all one step at a time on a single machine. Under the hood it relies on a package called klyng, which acts as a coordinator between the separate processes. You install klyng globally, it runs a small background service (a "beacon") on port 2222, and the processes use it to talk to each other. A machine.json file is meant to describe the cluster setup, though the README notes that file isn't fully wired up yet. For now, the project is hard-coded to train on a specific test problem from brain.js, and most of the scripts are for running examples or stress-testing how much data can move between processes. The main audience is developers already using brain.js who want to experiment with distributed training, for instance, if you're training a model on a large dataset and a single machine is too slow, you'd use this to spread the load. It could also appeal to people curious about how message-passing between processes works in JavaScript. In its current form it's more proof-of-concept than production tool: the cluster configuration isn't fully implemented, and several scripts exist mainly for testing the underlying communication layer rather than doing real training. What's notable is that this is a very early-stage project. The README is candid about what isn't done yet, multi-machine coordination, better integration with brain.js, and actual documentation are all flagged as work in progress. The codebase also reflects an exploratory style: scripts like example and test-sizes were added specifically to probe the limits of klyng because its own documentation was thin. If you're looking for a polished distributed-training framework, this isn't it yet, but it's an honest look at the engineering questions involved in getting there.
Brain-cluster is an experimental add-on for brain.js that speeds up neural network training by splitting the work across multiple processes or computers. It's an early proof-of-concept, not a finished tool.
Mainly JavaScript. The stack also includes JavaScript, brain.js, klyng.
Dormant — no commits in 2+ years (last push 2018-03-11).
No license information is provided in the explanation, so the terms of use are unknown.
Setup difficulty is rated hard, with roughly 1h+ to a first successful run.
Mainly developer.
This repo across BitVibe Labs
double-check against the repo, no cap.