v0.4.0

*Add genetic algorithm option via pyGAD
*CDK will now use all available subnets
*CDK security group updated to enable internode communication when running tasks that use distributed computing.
*New json input option “ec2_multinode_count” that tells Batch to provision and hook up more ec2s for a given job
*Both gpu_count and ec2_multinode_count will accept lists for benchmarking a variety of node counts and gpu counts
*Always passing an environmental variable into the container now with number of expected nodes: EXPECTED_NODES=N
*Updated IAM so that jobs can review what is available in an s3 bucket before pulling
*Added exponential backoff to both job submission and job status querying
*SLURM job creation was setup and tested with ParallelCluster if we have a workflow that switches away from AWS Batch. We haven’t written instructions yet, so this isn’t fully exposed
*Added a reload button into the optimization streamlit
*Turned off Ray with awswrangler as this appears to have resulted in lock ups if actual jobs also wanted to use Ray for distributed computing
*When using a custom metric with ec2 instance type optimization, this now should appear in the streamlit drop down options
*Add a new -r command line argument that will reload the json info and then reprocess all of the log files for the ec2data.csv.