MetisFL: The Open Federated Learning Framework for Scalable, Efficient, and Secure Federated Learning Workflows

MetisFL - The First Open Federated Learning Framework implemented in C++ and Python3.

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Project Installation Steps - Docker

Due to some library inconsistencies that appeared across operating systems (e.g., Centos vs MacOS) we concluded that we
should build a docker image and run the entire project within a container. The Dockerfile(s) contain all required steps.

System prerequisites:

python
docker

To compile and run the project through docker, navigate to the parent directory of the project and then:

Run chmod +x ./configure.sh && ./configure.sh to configure metis fl project.

Note: we run the above command before building the docker image because to configure all project dependencies.
Build docker image for the entire project.
- Ubuntu image (stable, preferable): docker build -t projectmetis_ubuntu_22_04 -f DockerfileUbuntu .
- Ubuntu Dev image (development purposes): docker build -t projectmetis_dev -f DockerfileDev .
- RockyLinux image (not stable): docker build -t projectmetis_rockylinux_8 -f DockerfileRockyLinux .
  Approximate size for any of the following images (using docker): ~9GB (without CUDA), ~12GB (with CUDA)
Build docker CUDA image (only applicable to Ubuntu and RockyLinux images).
- Ubuntu + CUDA cd docker_images/cuda/ubuntu/11.7 && docker build -t projectmetis_ubuntu_22_04_cuda -f Dockerfile .
- RockyLinux + CUDA cd docker_images/cuda/rockylinux/11.3 && docker build -t projectmetis_rockylinux_8_cuda -f Dockerfile .
- Verify docker cuda driver installation as: nvidia-docker run --rm --gpus all projectmetis_ubuntu_22_04_cuda nvidia-smi