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server
setup
README.md
link.py
ps.sh
pull.sh
restart.sh
run.sh
start.sh
stop.sh

README.md

Running on GCP

This configuration is for running on the Google Cloud Platform. All steps here assume that the Cloud SDK is already installed (for macOS this may e.g. be done using Homebrew: brew cask install google-cloud-sdk).

Setup

Script gcp-create.sh provides an easy way to create four GCP instances to be used with this configuration; simply run it from the setup directory.

To later remove everything again run gcp-destroy.sh from the setup directory.

Starting and Stopping

Right after setup all instances should be stopped, but scripts start.sh, stop.sh, and restart.sh provides easy ways of managing their state. Run them from the gcp directory.

start.sh will take care of linking the four instances together and starting a TensorFlow server on each in a screen.

Running

The run.sh script provides a way to run a program on the four instances. Symlink to it from the spdz directory and run it from there, e.g.:

spdz $ ./run.sh logistic-regression-simple/prediction.py

This script will copy the specified file to the input provider, run it, and pull back TensorBoard results to /tmp/tensorboard. Run tensorboard --logdir=/tmp/tensorboard on the local host to view them.

Other

Script ps.sh can be used to verify that a server is running on each instance. Script pull.sh will update the GitHub repository on each instance.