The assignment component within the academic course 'VU Serverless Computing WS-2023.'
| Purpose | Technology |
|---|---|
| Serverless platform | Openwhisk |
| Object Storage | Minio |
| Coordination / Messaging | Kafka |
| Machine Learning | scikit-learn |
| Local Development Environment | kind ~ Kubernetes in Docker |
- currently the actions need to be manually warmed up before starting training.
- EMNIST instead of MNIST
- add links to the above technologies
Run:
./setup-everything.sh
Optionally change permissions so it is executable:
chomd +x setup-everything.sh
After setup the main-app, it gets served on localhost:5000.
To start training navigate to /learn and optionally pass the arguments with url params: /learn?nclients=10&nrounds=10&nselected=5
Default values are:
- nclients=3
- nselected=3
- nrounds=5
Each round starts nclients and each client gets one split. As soon as the 50 splits get used the splits start getting re-used. After nselected model updates have been received, the round is finished and these are merged and saved as a new global model, which is then used in the next round.
The solution is visualized in the following diagram:
