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About Cypress
Cypress is Tulane's newest HPC cluster, offered by Technology Services for use by the Tulane research community. It is a 124-node cluster, with each node providing dual 10-core 2.8 GHz Intel Xeon E5-2680 v2 CPUs, 64 GB of RAM, and dual Xeon Phi 7120P coprocessors. Nodes are interconnected on a 40 Gigabit Ethernet network using a single Dell Z9500 Ethernet Fabric Switch.
Getting an account
All accounts must be part of a project. A Tulane faculty member (the PI, principal investigator) may create a project for members of his/her research group. Please send an email to: hpcadmin (at) tulane.edu for details.
Logging in to Cypress after your account is created
Cypress provides two login nodes:
cypress1.tulane.edu cypress2.tulane.edu
You will need a secure shell (SSH) client to log in. Your username and password will be the same as that for your Tulane user account. To reset your password, visit:
Note that this will also change your password for your e-mail and Single Sign On applications.
Storage: home directory
Your home directory on Cypress is intended to store customized source code, binaries, scripts, analyzed results, manuscripts, and other small but important files. This directory is limited to 10 GB (10,000 MB), and is backed up. To view your current quota and usage, run the command:
quota -f /home
Storage: Lustre filesystem
Cypress has a 699 TB Lustre filesystem available for use by active jobs, and for sharing large files for active jobs within a research group. The Lustre filesystem has 2 Object Storage Servers (OSSs) which provide file I/O for 24 Object Storage Targets (OSTs). The Lustre filesystem is available to compute nodes via the 40 Gigabit Ethernet network. The default stripe count is set to 1.
Allocations on this filesystem are provided per project/research group. Each group is given a space allocation of 1 TB and an inode allocation of 1 million (i.e. up to 1 million files or directories) on the Lustre filesystem. If you need additional disk space to run your computations, your PI may request a quota adjustment. To request a quota adjustment, please provide details and an estimate of the disk space used/required by your computations. Allocations are based on demonstrated need and available resources.
The Lustre filesystem is not for bulk or archival storage of data. The filesystem is configured for redundancy and hardware fault tolerance, but is not backed up. If you require space for bulk / archival storage, please contact us, and we will take a look at the available options.
Your group's Lustre project directory will be at:
/lustre/project/<your-group-name>
"your-group-name" is your Linux group name, as returned by the command "id -gn". Your group is free to organize your project directory as desired, but it is recommended to create separate subfolders for different sets of data, or for different groups of simulations.
To view your group's current usage and quota, run the command:
lfs quota -g `id -gn` /lustre
To view your own usage, you can run:
lfs quota -u `id -un` /lustre
Software on Cypress
Software on Cypress is organized using the Environment Modules (modules) package. The modules command is "module". To see the available software, run:
module avail
To load a specific package for use, you can run "module add", for example:
module add intel-psxe
to load Intel Parallel Studio.
Specialized software requirements
- Gaussian 09—Use of the Gaussian 09 software requires you to be in the gaussian group. Contact us to have your account added.
SLURM (resource manager)
Cypress uses SLURM to manage job submission. For general information and documentation, see the SLURM website:
http://slurm.schedmd.com/documentation.html
A slurm QOS (quality of service) is similar to a queue in other resource managers (e.g. TORQUE). Cypress has several QOSs available for jobs. Each QOS has limits on the requestable resources, as shown below:
| QOS limits | |||
|---|---|---|---|
| QOS name | maximum job size (node-hours) | maximum walltime per job | maximum nodes per user |
| interactive | N/A | 4 hours | 1 |
| normal | N/A | 24 hours | 12 |
| long | 168 | 168 hours | 8 |
The "normal" QOS is intended for users running parallel programs. This is the preferred type of usage to best take advantage of Cypess's parallel processing capability. Each user is limited to simultaneous usage of 12 nodes (240 cores) over all his/her jobs.
The "long" QOS is intended for jobs which are not very parallel, but have longer runtime. Each job has a job-size limit of 168 node-hours, calculated as the number of nodes requested multiplied by number of hours requested. For example a job submitted to the long QOS may request 1 node for 7 days, or 2 nodes for 3.5 days. You are limited to 8 nodes across all your jobs in this QOS. So, for example, you may run up to 8 jobs each using 1 node and running for 7 days.
The "interactive" QOS is intended to be used for testing SLURM script submission, and is limited to 1 node and 4 hours.
Other QOS's on the system are for staff testing use only.
Requesting memory for your job
Our standard nodes on Cypress will allow you to use up to 64 GB of memory per node. This should be sufficient for many types of jobs, and you do not need to do anything if your job uses less than this amount of memory. If your jobs require more memory to run, use the --mem option of sbatch to request a larger amount of memory. To request 128 GB nodes for your job, put the following in your sbatch script:
#SBATCH --mem=128000
or, to request 256 GB memory nodes, use the following:
#SBATCH --mem=256000
We have a limited number of the larger memory nodes, so please only request a larger amount of memory if your job requires it. You can ask SLURM for an estimate of the amount of memory used by jobs you have previously run using sacct -j <jobid> -o maxvmsize . For example:
$ sacct -j 2660 -o maxvmsize
MaxVMSize
----------
39172520K
This shows that job 2660 allocated close to 40 GB of memory.
Citation / Acknowledgment
We would greatly appreciate acknowledgment in papers, posters, presentations, or reports resulting from the use of Tulane HPC resources. We suggest something similar to the following:
"This research was supported in part using high performance computing (HPC) resources and services provided by Technology Services at Tulane University, New Orleans, LA."
We would also appreciate informing us of any publications resulting from use of Tulane HPC resources. This information is important for acquiring funding for new resources.
Getting help / Contact us
Contact us by email at: hpcadmin (at) tulane.edu
