Difference between revisions of "Analysis AWS"

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== Jupyter Notebook Over a Remote Connection ==
 
== Jupyter Notebook Over a Remote Connection ==
1) Run one terminal to start the notebook:
+
1) Run one terminal to start the notebook and forward the outputs to local web browser:
 
ssh -i AWS.pem -L 8887:localhost:8887 ubuntu@IP_ADDRESS
ssh -Y $USER@$REMOTE_HOST
 
  +
conda activate workshop
cd $FOLDER_WITH_CODE
 
#If necessary: conda activate $CONDA_ENV
 
 
jupyter notebook --no-browser --port=8887
 
jupyter notebook --no-browser --port=8887
   
  +
2) Copy the output of the notebook (see example below) and enter into your web browse (Firefox, Chrome, etc.)
2) Run another terminal to forward the port to your local machine<br>
 
<em>(Replace User and Remote_Host with the appropriate username and ip-address)</em>
 
ssh -i ${PATH}/AWS.pem -L 8887:localhost:8887 ubuntu@IP_ADDRESS_PROVIDED
 
#ssh -N -L localhost:8888:localhost:8887 $USER@$REMOTE_HOST
 
   
3) In Firefox/Chrome/Etc - Log into localhost:8888 <br>
 
This will prompt you for a token<br>
 
 
<br>
 
<br>
4) In the password/token column, copy the token created in the first terminal<br>
+
3) In the password/token column, copy the token created in the first terminal<br>
 
(It should look like the below - only copy the portion after the token= )
 
(It should look like the below - only copy the portion after the token= )
 
http://localhost:8887/?token=####HERE_IS_THE_TOKEN_CODE---COPY_THIS_AND_PASTE_INTO_BROWSER
 
http://localhost:8887/?token=####HERE_IS_THE_TOKEN_CODE---COPY_THIS_AND_PASTE_INTO_BROWSER
  +
   
   

Revision as of 10:21, 1 November 2019

For Workshop members without access to computing resources - Preconfigured Amazon Web Services servers can be used

Accessing compute resources on AWS:

Speak with Jeff Stout to get the current IP address and PEM key
${PATH} is the path to the PEM key provided to you

 ssh -X -i ${PATH}/AWS.pem ubuntu@IP_ADDRESS_PROVIDED

Jupyter Notebook Over a Remote Connection

1) Run one terminal to start the notebook and forward the outputs to local web browser:

 ssh -i AWS.pem -L 8887:localhost:8887  ubuntu@IP_ADDRESS
 conda activate workshop  
 jupyter notebook --no-browser --port=8887

2) Copy the output of the notebook (see example below) and enter into your web browse (Firefox, Chrome, etc.)


3) In the password/token column, copy the token created in the first terminal
(It should look like the below - only copy the portion after the token= )

 http://localhost:8887/?token=####HERE_IS_THE_TOKEN_CODE---COPY_THIS_AND_PASTE_INTO_BROWSER


Installed software

Human Neocortical Neurosolver

 hnn
 #hnn is installed in the system level python >> may need to conda deactivate first

MNE python, Eelbrain, PyCTF

 conda activate workshop  (This environment has MNE, Eelbrain, and PyCtf installed)

CTF software

 singularity shell /opt/ctf/ctf.img
 $ctf_command
 singularity exec /opt/ctf/ctf.img $ctf_command

SAM version 5

 sam_cov ...
 sam_3d ...

Afni

 afni -dset $MRI_file



  1. Server Config
    1. google > fedora aws > select the AMI number for N.Virginia
    2. In AWS > launch instance > search for AMI number > (Under community) > Launch
      1. https://alt.fedoraproject.org/cloud/
  2. Determine an image (search for fedora in community)
  3. Create a keypair and download the key
    1. The download will be in the form of a .pem file
    2. We will need to distribute this key to the users
  4. Launch the instance
  5. Log into the instance using ssh


  1. Freesurfer
  2. MNE python
  3. pyctf

Done # SAM v5

  1. Afni ###INSTALL ME neurodebian
  2. singularity ? >> CTF (need to use workstation version of fedora) << may need to compile for ubuntu or use 2.6
  3. Eelbrain (conda forge)
  4. Jupyter

Done# Forward sim HNN software

  1. FSL ###Install outside of neurodebian
  2. Brainstorm (compiled)


Matlab Based

  1. Brainstorm
  2. Fieldtrip