You can connect to Satori through
- a web portal, or
- plain ssh from a terminal or a terminal client like PuTTY (https://www.putty.org).
To use the web portal
- Navigate to https://satori-portal.mit.edu in your favorite web browser.
- Select the Globus Auth button.
- When redirected to globus, authenticate via Massachusetts Institute of Technology.
- When successfully logged in, you will be redirected back to Satori Portal!
you can then launch Jupyter notebook environments running on GPUs
- Select "Jupyter Notebook" from the "Interactive Apps" dropdown in the top navbar. You can also select "My Interactive Sessions".
- At the prompt to launch a Jupyter notebook, select the "Anaconda 2019.10 PowerAI [Experimental]" option in the "Choose Anaconda Environment" section.
- Enter (in hours) how long you would like the app to run for.
- Click launch, wait for app to begin running on a compute node and finally, select "Connect to Jupyter"!
the web portal also has sub-menus for
- a terminal on the front-end node (Clusters menu)
- a running job monitoring window (Jobs menu). This is also has a batch job preparation form, but it is malfunction at the moment!
- a file browsing and transfer client (Files menu)
- Login to Satori cluster is done via SSHv2 as follow:
scp <local-file.py> [email protected]:
As general rules:
- satori-login-001.mit.edu - should be used for submiting training jobs and related activities
- satori-login-002.mit.edu - should be used for transfering large files/datasets and compiling software requiring nvcc, gcc, XL compiler etc
- if one login-node will not be available try the second one
- don’t run large computations on the login nodes
In case you want to work with Jupyter Notebooks but cannot use the https://satori-portal.mit.edu portal, you will need to forward Jupyter HTTP ports to your own workstation via SSHv2 tunneling. This can be done like this: (Note FQDN == Fully Qualified Domain Name like nodeXXXX for the node you are running on (E.g. node0014)
ssh -L 10001:<compute_node_FQDN>:10001 [email protected]
jupyter notebook --ip=<compute_node_FQDN> --port=10001
if you do this, remember to activate whatever conda enviroment you wish to use before starting jupyter
e.g
conda activate wmlce-1.6.2