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Overview
Overview of OSCAR Supercomputer
Oscar - Ocean State Center for Advanced Resources - is Brown University's high performance computing cluster for both research and classes. Oscar is maintained and supported by Center for Computation and Visualization (CCV).
If you do not have an Oscar account, you can request one by clicking the following link:
Anyone with a Brown account can get a free Exploratory account on Oscar, or pay for priority accounts. A free Exploratory account allows:
- 32 cores and 246GB memory for up to 48 hours in the batch queue
- 4 cores, 192GB memory and 2 GPUs for up to 48 hours in the gpu queue
- 32 cores and 752GB memory for up to 48 hours in the bigmem queue
Individuals external to Brown can get access to Oscar by having a sponsored Brown account. Please work with your department to get sponsored Brown accounts for any external collaborators.
Authorized users must comply with the following Brown University policies:
Users can run their computing-intensive and/or long runtime jobs/program in Oscar to take advantage of high performance computing resources there, as highlighted below:
- 2 Login nodes
- 3.27 PB of storage
- Red Hat EL 7.7 (Linux)
- Mellanox InfiniBand network
- Slurm Workload manager
Hundreds of users can share computing resources in Oscar. Slurm is used in Oscar to manage user jobs and computing resources such as cores and GPUs.
Users should not run computations or simulations on the login nodes, because they are shared with other users. You can use the login nodes to compile your codes, manage files, and launch jobs on the compute nodes.
To allow users sharing access to Oscar, there are limits on the maximum number of pending and running jobs a user account may have/submit:
- 1200 for a priority account
- 1000 for an exploratory account
- Operating systems of all Oscar nodes: RedHat 7.3
- CCV Staff install software upon user requests or help users on software installation
Oscar has 3.27PB storage from the General Parallel File System (GPFS) of IBM, which provides high performance access of storage. Users have Home, Scratch, and Data directories as their storage with quota in Oscar. Please refer to the details at Oscar's filesystem.
Access and User Accounts - User accounts are controlled via central authentication and directories on HPC are only deleted on the request of the user, PI, or departmental chair.
Files not accessed for 30 days will be deleted from your scratch directory. Use ~/data for files you wish to keep long term.
Users can transfer files from and to Oscar filesystem. In particular, users can transfer files between Oscar filesystem and Campus File Storage.
Oscar users can connect to Oscar by
- Non-disruptive Maintenance:
- non-disruptive work, including software changes, maintenance, and testing
- may occur at any time
- no notification provided
- Monthly Scheduled Maintenance:
- no downtime expected, but there may be limited degradation of performance
- first Tuesday of the month, 8:00 am - 12:00 noon
- no notification provided
- Unscheduled Maintenance:
- maximum 1 day downtime
- occurs very rarely and includes any unplanned emergency issues that arise
- Prior notification provided (depending on the issue, 1 day to 4 weeks advance notice provided)
- Major Upgrade Maintenance:
- service may be brought down for 3-5 days
- occurs annually
- 4-week prior notification provided
- During Business Hours:
- Send email to [email protected]. A ticket will get created and CCV staff will attempt to address the issue as soon as possible.
- During Non-Business Hours:
- Call CIS Operations Center at (401) 863-7562. A ticket will get created and CCV staff will be contacted to address the issue.
CCV staff support for researchers seeking help with statistical modeling, machine learning, data mining, data visualization, computational biology, high-performance computing, and software engineering.
CCV staff provides tutorials on using Oscar for classes, groups and individual. Please check CCV Events for upcoming trainings and office hours.
CCV provides short videos (coming soon) for users to learn as well.
Last modified 11d ago