Getting Started - SCU BRB

Notice

To gain access to the SCU BRB nodes, you must have a valid SCU account and CWID. Please contact SCU@med.cornell.edu to request access.

Access SCU Cluster - BRB

The following gateway nodes can be reached to access the SCU Cluster.

• scu-login01.med.cornell.edu

• scu-login02.med.cornell.edu

These gateway nodes can be reached from any of the SCU Gateways or nodes. SCU credentials must be used to access the SCU gateways. WCMC (CWID) credentials must be used to access the BRB Cluster.

[user@laptop ~]$ ssh scu_user@aphrodite.med.cornell.edu
scu_user@aphrodite's password: Enter SCU password

[scu_user@aphrodite ~]$ ssh CWID@scu-login01.med.cornell.edu
CWID@scu-login01's password: Enter CWID password

Configure SSH Keys

SSH key configuration allows users to traverse the BRB infrastructure without entering passwords at each step. The following will create an SSH keypair and authorize its use within the infrastructure.

ssh-keygen  

Accept default options at each prompt and an SSH private and public key will be created in your ~/.ssh/ directory. Enter the following commands to authorize its use within the cluster.

cd ~/.ssh/
cat id_rsa.pub >> authorized_keys

More custom key configurations can be done to allow for quicker access to the infrastructure. View SSH key setup for more information, or contact SCU@med.cornell.edu for assistance.

Access Cluster Nodes

Cluster nodes are managed through Slurm. Accessing and running jobs on login nodes or by ssh’ing directly to a node is Strictly forbidden.

In-depth SCU documentation on Slurm can be found here: Using Slurm .

Access to the nodes and slurm commands can be run from scu-login02.med.cornell.edu.

Interactive Session

srun --pty -n1 --mem=8G -p cryo-cpu /bin/bash

For instructions on how to craft a batch submission file or how to access a node with X forwarding support, please view our full documentation here:Using Slurm.

Athena Notice

The filesystem accessible from the BRB cluster, “scu-login*” gateways, as well as “scu-node*” nodes, will have access to a filesystem that is named athena; however, this filesystem is separate and distinct from the athena that is accessible from Aphrodite, Pascal, Curie, etc. This was done to allow easier migrations and preserve the paths and filesystem structures from one cluster to the other. Please consider this when managing data between the two clusters.

Softwares and Programs

Spack

Spack is the SCU package manager and is accessible from all nodes within the SCU infrastructure.

For more information on Spack, view our documentation here: Spack. Note: The “Spack Introduction and Environment Setup” portion is not required when on the BRB network. Within the SCU BRB network, no setup is needed. Once logged onto a node, all spack commands and options will be available.

Modules

Packages that are installed on the SCU network drive, rather than in spack will be distributed as modules. These modules, once loaded, will perform all variable setups needed to properly run the program in question.

The following will display all available modules:

[rma3001@scu-node001 ~]$ module avail 

------------------------------------------------------------------------------------------- /software/apps/modulefiles --------------------------------------------------------------------------------------------
pyem             relion/3.1.0/cpu relion/3.1.0/gpu

To load a package into your environment for use:

[rma3001@scu-node001 ~]$ module load relion/3.1.0/cpu 
# The program is now ready for use
[rma3001@scu-node001 ~]$ relion 

Python Packages

Nodes within the SCU environment support conda and pip installations. Conda and pip allow users to install packages within their own user space. Certain packages may include documentation on installation steps for pip or conda installations. View below for example installations.

Install Jupyter-notebook within Conda Environment

Conda will create a virtual Python environment for easy installations and idempotency.

[rma3001@scu-node001 ~]$ conda create -n jupyter-notebook
[rma3001@scu-node001 ~]$ conda activate jupyter-notebook
[rma3001@scu-node001 ~]$ conda install -c anaconda jupyter

Once the program is installed, access to the environment can be regained through conda activate jupyter-notebook . View Conda User Guide for more in depth tutorials. Or contact SCU@med.cornell.edu for support.

Install Python Packages Using Pip

Pip will install packages within a user’s local python directories. The following will install several commonly used Python programs within a user’s home directory

[rma3001@scu-node001 ~]$ pip3 install --user cython numpy scipy

View Pip Documentation for more information. Or contact SCU@med.cornell.edu for support.

Request a Program

If a required program is not installed in Spack or within our modules, contact SCU@med.cornell.edu. The SCU will determine whether the package can be installed in Spack, as a module, or can provide instructions on how to install the program within your user space.

Cryo-EM

Relion

Relion is now being managed by modules with different installations for CPU or GPU versions.

To load Relion (version 3.1.0 - GPU-optimized) enter module load relion/3.1.0/gpu. View module instructions above for more information about loading and querying modules. For more in-depth Relion documentation, view our Relion documentation here: Relion

CryoSparc

CryoSparc will be accessible in the same way as it was previously, with the exceptions being that the hostnames and credentials must be updated. Please contact SCU@med.cornell.edu for more information.