BMI maintains a Linux-based computational cluster that is accessible from outside the Cincinnati Children's network. The cluster currently has over 700 processing cores and is heterogeneous with both large-memory SMPs as well as low-cost processing nodes.
Accessing the cluster
The cluster is Linux-based and the preferred method of access is either SSH or NX.
Instructions to access the HPC login node via SSH:
- If you are in the CCHMC network or connected to CCHMC VPN - ssh firstname.lastname@example.org
- If you are outside of CCHMC network
Instructions to access the HPC login node via NX:
- Configure your NX client to connect to nx.research.cchmc.org
- Follow the rest of the configuration explained here.
To request access to the cluster, please send an email to Cluster Support.
CCHMC employees: After your access is enabled, you should be able to login to the cluster with your network credentials.
External users: Please use the username/password that was sent back to you via email to login to the cluster.
All users have a default disk (home directory) quota of 100 GB and a job walltime quota of 10000 hours per quarter, which is free. The quota of your home directory is fixed, and cannot be changed. To increase the walltime, please send an email to Cluster Support.
This cluster can be used for interactive and batch processing of computationally intensive tasks. In particular, in can be used to perform
- protein-protein and protein-ligand docking using AutoDock, NAMD and other protocols
- protein secondary structure prediction, membrane domain prediction and other protein structure prediction and visualization problems using SABLE, MINNOU and other servers
- microarray analysis using tools such as GeneSpring, RMAExpress or BioConductor (R)
- genome-wide association studies using plink or the Wake Forest analysis suite
- other memory-intensive or processor-intensive statistical analyses using R
- Genomics using GATK, Bowtie, Tophat etc.
- many other applications
All nodes run 64-bit CentOS Linux.
Cluster batch system is currently managed by LSF resource manager and scheduler. You can get some examples of submitting jobs using LSF here. Please read the job scheduling policies page for recent policy changes.
You can obtain snapshot and historical information about the load on the cluster.
Help and support
For technical support, software installation, etc., please contact the Research IT Support.