/fs6-cloud

Run FreeSurfer 6.0 in the cloud

Primary LanguageShellBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

How to run FreeSurfer 6.0 in the cloud

This guide describes how to run FreeSurfer 6.0 inside a docker container on AWS batch.

NOTE: A FreeSurfer 7.1.1 container is now available! The commands below should work by changing corticometrics/fs6-aws to corticometrics/fs7-aws when running the commands below. The new container hasn't been tested as thoroughly, so please leave an issue if you notice anything strange!

Setup

The built containers live here. You can pull it using

docker pull corticometrics/fs6-aws:latest

This will trigger a 5.8Gb download

Using the fs6-aws container

The entrypoint for the corticometrics/fs6-aws container will perform some pre- and post-processing steps, depending on certain environment variables.

The FS_KEY environment variable

If FS_KEY is set. The string is decoded from base64, and written to the file $FREESURFER_HOME/license.txt. This occurs before the commands passed to the container are executed.

Most of FreeSurfer will not work if this key is not set. Liceneses are distributed for free by the FreeSurfer team. You can apply for one here.

Once you have your license, use the output of the following command to set the FS_KEY variable:

cat $FREESURFER_HOME/license.txt | base64 -w 0

The FS_SUB_NAME environment variable

This environment varibale is only used in conjunction with FS_SUB_S3_IN and FS_SUB_S3_OUT (see below)

The FS_SUB_S3_IN environment variable

If this variable and FS_SUB_NAME are set. The container will attempt to recursivly copy the contents of ${FS_SUB_S3_IN}/${FS_SUB_NAME} to ${SUBJECTS_DIR}/${FS_SUB_NAME} (SUBJECTS_DIR is set to /subjects by the docker container). This occurs before the commands passed to the container are executed.

If either FS_SUB_S3_IN or FS_SUB_NAME is not defined, this action wont be performed. So, alternatively, you could mount a docker-volume or an external directory to /subjects to get your subject data into the container.

The FS_SUB_S3_OUT environment variable

If this variable and FS_SUB_NAME are set. The container will attempt to recursivly copy the contents of ${SUBJECTS_DIR}/${FS_SUB_NAME} to ${FS_SUB_S3_OUT}/${FS_SUB_NAME} (SUBJECTS_DIR is set to /subjects by the docker container). This occurs after the commands passed to the container are executed.

If either FS_SUB_S3_OUT or FS_SUB_NAME is not defined, this action wont be performed.

Access to AWS services

The container also accepts standard AWS access key environment variables (AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY) to grant access to AWS services. This is useful to give the container S3 acess for testing locally. See Creating an IAM User in Your AWS Account. A typical set of permissions to read/write from an S3 bucket might look like:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "AllowUserToSeeBucketListInTheConsole",
            "Action": [
                "s3:GetBucketLocation",
                "s3:ListAllMyBuckets"
            ],
            "Effect": "Allow",
            "Resource": [
                "arn:aws:s3:::*"
            ]
        },
        {
            "Effect": "Allow",
            "Action": [
                "s3:ListBucket"
            ],
            "Resource": [
                "arn:aws:s3:::the-name-of-my-bucket"
            ]
        },
        {
            "Effect": "Allow",
            "Action": [
                "s3:PutObject",
                "s3:GetObject",
                "s3:DeleteObject"
            ],
            "Resource": [
                "arn:aws:s3:::the-name-of-my-bucket/*"
            ]
        }
    ]
}

The environment variables AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY can also be used when running the container through AWS Batch, however this is not best-practice (since secret keys may be recorded in log files). When using AWS batch, it is best practive to configure a role and attach it to the container when launching. See IAM Roles for Tasks for more info.

Example usage

Launch the container locally, drop into a bash shell.

docker run -it --rm \
  corticometrics/fs6-aws:latest \
  /bin/bash

This doesn't have a FreeSurfer license or any subject data, so it's not particularily interesting. You can confirm that FreeSurfer wont work by trying something like:

mri_convert /freesurfer/subjects/sample-001.mgz ~/test.nii.gz

Launch the container locally with a license, drop into a bash shell.

docker run -it --rm \
  -e FS_KEY='xxx' \
  corticometrics/fs6-aws:latest \
  /bin/bash

Replace xxx with the output of cat $FREESURFER_HOME/license.txt|base64. You can get a license.txt file for free here

You can confirm that FreeSurfer works by trying something like:

mri_convert /freesurfer/subjects/sample-001.mgz ~/test.nii.gz

Launch the container locally with a FreeSurfer license and mount the subject data from a local drive; drop into a bash shell.

docker run -it --rm \
  -e FS_KEY='xxx' \
  -v /path/to/my/subject_data:/subjects \
  corticometrics/fs6-aws:latest \
  /bin/bash

/path/to/my/subject_data is where your subject data is kept on your local machine. Subject data should always be mapped to /subjects inside the container

You can confirm that your data is available in the container by trying:

ls -lR /subjects

Launch the container locally with a FreeSurfer license and mount the subject data from a local drive; run a recon-all of the subject bert.

docker run -it --rm \
  -e FS_KEY='xxx' \
  -v /path/to/my/subject_data:/subjects \
  corticometrics/fs6-aws:latest \
  recon-all -s bert -all -parallel

This assumes the subject bert lives in a standard FreeSurfer subject directory structure under /path/to/my/subject_data. It will take a while to run, so if you want to kill it, from another terminal (outside the container) run docker ps to find the containerID, then run docker kill <containerID>

Launch the container locally with a FreeSurfer license and AWS permissions; Drop into a bash shell.

docker run -it --rm \
  -e FS_KEY='xxx' \
  -e AWS_ACCESS_KEY_ID='xxx' \
  -e AWS_SECRET_ACCESS_KEY='xxx' \
  corticometrics/fs6-aws /bin/bash

See Creating an IAM User in Your AWS Account to get values for AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY. If you just want to do a quick test, create a user and give it AmazonS3FullAccess but note this is not best practice. See AWS docs for more info. You can test it by trying to run

aws s3 ls

Or try copying data to/from your bucket:

mkdir -p /subjects/bert
aws s3 sync s3://my-bucket/subjects/bert /subjects/bert/
ls -lR /subjects/bert/

See Working with Amazon S3 Buckets on how to create/use S3 bukets.

Launch the container locally with a FreeSurfer license and AWS permissions. Copy over a subject from S3, run recon-all, Copy results back to S3

docker run -it --rm \
  -e FS_KEY='xxx' \
  -e AWS_ACCESS_KEY_ID='xxx' \
  -e AWS_SECRET_ACCESS_KEY='xxx' \
  -e FS_SUB_S3_IN='s3://my-bucket/subjects/' \
  -e FS_SUB_S3_OUT='s3://my-bucket/subjects-fs6-recon/' \
  -e FS_SUB_NAME='bert' \
  corticometrics/fs6-aws \
  recon-all -s bert -all -parallel

This will take a while, so you can kill it from another terminal (outside the container) with docker ps to find the containerID, then run docker kill <containerID>.

If this step works, then you're ready to submit jobs to AWS batch!

References and Inspiration: