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Courses

The YCRC Bouchet cluster can be made available for Yale courses with a suitable computational component. The YCRC hosts over a dozen courses on the clusters every semester.

Warning

All course allocations are temporary. All associated accounts and data will be removed one month after the last day of exams for that semester.

For Instructors

If you are interested in using a YCRC cluster in your Yale course, please fill out the course account request form. If at all possible, please let us know of your interest in using a cluster at least two weeks prior to start of classes so we can plan accordingly, even if you have used the cluster in a previous semester.

Submit Course Account Request

Course ID

Your course will be give a specific courseid based on the Yale course catalog number. This courseid will be used in the course account names and web portal.

Course Accounts

All members of a course, including the instructor and TFs will be given temporary course accounts. These accounts take the form of courseid_netid. Course accounts are distinct from any research accounts a course member may already have. As with all cluster access, you must be on the VPN to access the web portal if you are off campus.

All course-related accounts are subject to the same policies and expectation as standard accounts.

Course-specific Web Portal

Your course also has a course-specific web portal, based on Open OnDemand, accessible via the URL (replacing courseid with the id given to your course):

courseid.ycrc.yale.edu

Course members must use the course URL to log in to course accounts on Open OnDemand--the normal cluster portals are not accessible to course accounts. You will then authenticate using your standard NetID (without the courseid prefix) and password.

Warning

If you only have a course participant account, but try to log in through the cluster web portal URL, you will get an error in the browser: 

Error -- can't find user for cpsc424_test
Run 'nginx_stage --help' to see a full list of available command line options.
Use the URL for your course web portal will resolve the problem.

SSH Access

To access your course account via terminal and ssh authentication, connect to the cluster using your course account name. For example:

ssh courseid_netid@bouchet.ycrc.yale.edu

If you already have a permanent researcher account (one that is just your NetID) on one of the clusters, the course account will already be setup with any ssh keys previously uploaded to your researcher account. To add a new key, upload your new key and it will be delivered to all of your accounts within a few minutes.

Course Storage

Courses on the YCRC clusters are typically granted a standard 4TiB project quota and 10TiB of scratch storage, along with 125GiB home directory for each course member. If the course needs additional storage beyond the default 4TiB, please contact us at research.computing@yale.edu.

See our cluster storage documentation for details about the different classifications of storage.

Partitions for Courses

Compute resources for courses are available in the education or education_gpu partitions. You can request these nodes for your jobs using the -p partition_name flag. See our Slurm documentation for more information on submitting jobs. Note you will be sharing these partitions with other courses. If your jobs need to exceed the restrictions of the partitions, please have your instructor or TF contact us.

Course members are welcome to use the public partitions of the cluster. However, we request that students be respectful in their usage as not to disrupt ongoing research work.

See each tab below for more information about the available education partitions.

Use the education partition for CPU-only jobs.

Request Defaults

Unless specified, your jobs will run with the following options to salloc and sbatch options for this partition.

--time=01:00:00 --nodes=1 --ntasks=1 --cpus-per-task=1 --mem-per-cpu=5120

Job Limits

Jobs submitted to the education partition are subject to the following limits:

Limit Value
Maximum job time limit 1-00:00:00
Maximum CPUs per group 2000
Maximum memory per group 30000G
Maximum CPUs per user 1000
Maximum memory per user 15000G

Available Compute Nodes

Requests for --cpus-per-task and --mem can't exceed what is available on a single compute node.

Count CPU Type CPUs/Node Memory/Node (GiB) Node Features
2 cpugen:emeraldrapids 64 990 cpugen:emeraldrapids, cpumodel:8562Y+, common:yes

Use the education_gpu partition for jobs that make use of GPUs. You must request GPUs explicitly with the --gpus option in order to use them.

Request Defaults

Unless specified, your jobs will run with the following options to salloc and sbatch options for this partition.

--time=01:00:00 --nodes=1 --ntasks=1 --cpus-per-task=1 --mem-per-cpu=5120

GPU jobs need GPUs!

Jobs submitted to this partition do not request a GPU by default. You must request one with the --gpus option.

Job Limits

Jobs submitted to the education_gpu partition are subject to the following limits:

Limit Value
Maximum job time limit 1-00:00:00
Maximum GPUs per user 2
Maximum submitted jobs per user 1

Available Compute Nodes

Requests for --cpus-per-task and --mem can't exceed what is available on a single compute node.

Count CPU Type CPUs/Node Memory/Node (GiB) GPU Type GPUs/Node vRAM/GPU (GB) Node Features
4 cpugen:emeraldrapids 48 479 rtx_5000_ada 4 32 cpugen:emeraldrapids, cpumodel:6542Y, common:yes, gpu:rtx_5000_ada

Interactive Jobs

salloc -p education

or if you need to request a GPU

salloc -p education_gpu --gpus=1

Batch Jobs

Add the following to your submission script:

#SBATCH -p education

or if you need to request a GPU

#SBATCH -p education_gpu --gpus=1

Web Portal

In any of the app submission forms, select the correct paritition name into the "Partition" field.

Cluster Maintenance

Bouchet undergoes regularly scheduled maintenance throughout the year. The maintenance schedule is published here.

Please account for the cluster unavailability when developing course schedules and (for students) completing your assignments.

End of Semester Course Deletion

As mentioned above, all course allocations are temporary. All associated accounts and data will be removed one month after the last day of exams for that semester. If you would like to retain any data in your course account, please download it prior to the deletion date or, if applicable, submit a request to research.computing@yale.edu to transfer the data into your research account.

A reminder of the removal will be sent to the instructor to see if it needs to be delayed for any incompletes (for example). Students will not receive a reminder. Instructors, if you would like to retain course materials for future semesters, please submit a request to research.computing@yale.edu to have the materials stored in our course repository.

Transfer Data to Research Account

If you have a research account on one of our clusters and would like to transfer data from your course account to it, please contact us for assistance.

Frequently Asked Questions

  • Which partition should I use for my course work?
    Use the education partition for CPU workloads and education_gpu for GPU workloads whenever possible. These partitions are intended for course use and generally provide more resources that are readily available to students. Course members may also use public partitions such as day and gpu_devel when needed.

  • Why does my Jupyter or RStudio session not start in the education partition?
    The partition may be busy, or one or more compute nodes may be unavailable. If your session still has not started after 5 minutes, you can try the public day partition. Submitting multiple sessions will not help your session start sooner and may increase overall wait times for all the course members.

  • I’m getting Error – failed to map user (NetID)
    Make sure you are using your course-specific URL, such as coursename.ycrc.yale.edu. If you still get this error, it usually means that you have not been added to the course account. Please contact your instructor or TA and ask them to reach out to us so we can add you to the course.

  • My session is running, but I’m unable to load the JupyterLab or RStudio interface
    Please contact us for assistance. We respond during business hours, Monday through Friday, 9 a.m.–5 p.m.

  • I’m getting This website is under heavy load (queue full) or Proxy error
    Please contact us for assistance. We respond during business hours, Monday through Friday, 9 a.m.–5 p.m.

  • I have a question about an assignment or coursework, or I need help troubleshooting my code
    Please contact your instructor or TA first. They are the best resource for questions about assignments, course content, and troubleshooting course-specific code.

  • Can I use my course account for research or personal projects?
    No. Course accounts are temporary and intended for coursework only. Students will not receive a reminder before their course accounts are removed.

Last update: August 17, 2026