Distributed-CNN

Architecture diagram

Instructions for deployment

if using aws academy:

• Update the ~/.aws/credentials file to up-to-date version for the current session

• the main implementation is a pytorch-based distributed Convolutional-Neural-Net which runs on the amount of ec2 instances defined by the environmental variable WORLD_SIZE(which is the only user-parameters provided for tunning)

  # Setup the environment
  
  # Extremely important, defines the number of ec2 instances to be made / the number of containers that we train the model on  
  
  export WORLD_SIZE=(int) # 1-5 is ideal as setting it too high would reach cpu request limit 
  
  chmod -R u+x scripts
  
  # Inside "fabfile.env", change these variables to:
  ssh_key_path = "PATHTOKEY/KEYNAME.pem"
  key_name = "KEYNAME"
  
  
  # Set up the swarm clusters
  fab start # May take a while to pull the docker file
  fab setupmaster 
  
  # Note: This step can be skipped if world size = 1
  fab setupworkers
  
  # Finally
  fab distributejobs

• to see performance/output of the training process (after all the commands above has been run):

  # rank0 being the name for the master node where the swarm manager resides
  fab ec2ssh rank0
  docker attach rank0