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Notice
This guide assumes you To gain access to the SCU BRB nodes, you must have a valid SCU account and CWIDCWID and lab account. Please contact SCU@med.cornell.edu to request access.
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Access SCU Cluster - BRB
The following gateway nodes They can be reached from within WCM tagged IP devices as well as through VPN once configured. Please contact SCU@med.cornell.edu to request VPN access to the SCU Cluster-login machines.
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.
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New SCU users
Configure SSH Keys
SSH key configuration allows users to enter and traverse the BRB infrastructure without entering passwords at each step. The following will create an SSH keypair and authorize its use.
Local Workstation to SCU Cluster
From your local Mac or Linux workstation, enter the following within the infrastructure.terminal
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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.
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cd[local@my_workstation ~]$ cat ~/.ssh/ cat id_rsa.pub >> ~/.ssh/authorized_keys |
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While your public key in id_rsa.pub can be shared freely, your private key in id_rsa must be kept secret. If another person gains access to this file, they will be able to impersonate you thereby accessing all of your files. Do not ever copy or move your private key from your ~/.ssh folder or set permissions so that other users can access this file. Permissions on this file should always be "chmod 600," set my ssh-keygen, which means only accessible by the owner. Do not change permissions on the private key. |
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Keys Within SCU Infrastructure
Repeat above steps on one of the SCU login nodes
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[cwid@scu-login02 ~]$ 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.
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[cwid@scu-login02 ~]$ cat id_rsa.pub >> authorized_keys |
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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
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srun --pty -n1 --mem=8G -p cryo-cpu /bin/bash -i |
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.
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Athena Notice
The filesystem accessible from the scuBRB cluster, “scu-login*” gateways, as well as scu“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 structure structures from one cluster to the other. Please consider this when managing data between the two clusters.
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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.
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[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 Python Packages Within Conda Environment: Eg. Jupyter-notebook
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Conda will create a virtual Python environment for easy installations and idempotency.
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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
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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.
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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 has been previously, with the exceptions being that the hostnames server names and credentials must be updated. Please contact SCU@med.cornell.edu for more information.
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