Oscar
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  • Overview
  • Quickstart
  • Getting Started
  • System Hardware
  • Account Information
  • Short "How to" Videos
  • Quick Reference
    • Common Acronyms and Terms
    • Managing Modules
    • Common Linux Commands
  • Getting Help
    • ❓FAQ
  • Citing CCV
  • CCV Account Information
  • Student Accounts
  • Offboarding
  • Connecting to Oscar
    • SSH (Terminal)
      • SSH Key Login (Passwordless SSH)
        • Mac/Linux/Windows(PowerShell)
        • Windows(PuTTY)
      • SSH Configuration File
      • X-Forwarding
      • SSH Agent Forwarding
        • Mac/Linux
        • Windows (PuTTY)
      • Arbiter2
    • Open OnDemand
      • Using File Explorer on OOD
      • Web-based Terminal App
      • Interactive Apps on OOD
      • Using Python or Conda environments in the Jupyter App
      • Using RStudio
      • Desktop App (VNC)
    • SMB (Local Mount)
    • Remote IDE (VS Code)
      • From Non-compliant Networks (2-FA)
      • Setup virtual environment and debugger
  • Managing files
    • Oscar's Filesystem
    • Transferring Files to and from Oscar
    • Transferring Files between Oscar and Campus File Storage (Replicated and Non-Replicated)
    • Resolving quota issues
      • Understanding Disk Quotas
    • Inspecting Disk Usage (Ncdu)
    • Restoring Deleted Files
    • Best Practices for I/O
    • Version Control
  • Submitting jobs
    • Running Jobs
    • Slurm Partitions
    • Interactive Jobs
    • Batch Jobs
    • Managing Jobs
    • Job Arrays
    • MPI Jobs
    • Condo/Priority Jobs
    • Dependent Jobs
    • Associations & Quality of Service (QOS)
  • GPU Computing
    • GPUs on Oscar
      • Grace Hopper GH200 GPUs
      • H100 NVL Tensor Core GPUs
      • Ampere Architecture GPUs
    • Submitting GPU Jobs
    • Intro to CUDA
    • Compiling CUDA
    • Installing Frameworks (PyTorch, TensorFlow, Jax)
      • Installing JAX
      • Installing TensorFlow
    • Mixing MPI and CUDA
  • Large Memory Computing
    • Large Memory Nodes on Oscar
  • Software
    • Software on Oscar
    • Using Modules
    • Migration of MPI Apps to Slurm 22.05.7
    • Python on Oscar
    • Python in batch jobs
    • Installing Python Packages
    • Installing R Packages
    • Using CCMake
    • Intro to Parallel Programming
    • Anaconda
    • Conda and Mamba
    • DMTCP
    • Screen
    • VASP
    • Gaussian
    • IDL
    • MPI4PY
  • Jupyter Notebooks/Labs
    • Jupyter Notebooks on Oscar
    • Jupyter Labs on Oscar
    • Tunneling into Jupyter with Windows
  • Debugging
    • Arm Forge
      • Configuring Remote Launch
      • Setting Job Submission Settings
  • MATLAB
    • Matlab GUI
    • Matlab Batch Jobs
    • Improving Performance and Memory Management
    • Parallel Matlab
  • Visualization 🕶
    • ParaView Remote Rendering
  • Singularity Containers
    • Intro to Apptainer
    • Building Images
    • Running Images
    • Accessing Oscar Filesystem
      • Example Container (TensorFlow)
    • Singularity Tips and Tricks
  • Installing Software Packages Locally
    • Installing your own version of Quantum Espresso
    • Installing your own version of Qmcpack
  • dbGaP
    • dbGaP Architecture
    • dbGaP Data Transfers
    • dbGaP Job Submission
  • RHEL9 Migration
    • RHEL-9 Migration
    • LMOD - New Module System
    • Module Changes
    • Testing Jupyter Notebooks on RHEL9 mini-cluster
  • Large Language Models
    • Ollama
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On this page
  • Accounts
  • Hardware
  • Scheduler
  • Software
  • Storage
  • Connecting to Oscar
  • Maintenance Schedule
  • Unplanned Outage
  • User and Research Support

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Overview

Overview of OSCAR Supercomputer

NextQuickstart

Last updated 7 months ago

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Oscar is Brown University's high performance computing cluster for both research and classes. Oscar is maintained and supported by .

Please contact if there are any questions on Oscar.

Accounts

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.

Authorized users must comply with the following Brown University policies:

Hardware

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

  • 8 PB of storage

  • Red Hat Enterprise Linux 9.2 (Linux)

  • Mellanox InfiniBand network

  • Slurm Workload manager

Scheduler

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

Software

  • Operating systems of all Oscar nodes: Red Hat 9.2

  • CCV Staff install software upon user requests or help users on software installation

Storage

Access and User Accounts - User accounts are controlled via central authentication and directories on Oscar 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.

Connecting to Oscar

Oscar users can connect to Oscar by

Maintenance Schedule

  • 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

Unplanned Outage

  • During Business Hours:

  • 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.

User and Research Support

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 provides short videos (coming soon) for users to learn as well.

More details can be found at the .

Individuals external to Brown can get access to Oscar by having a sponsored Brown account. Please work with your department to for any external collaborators.

.

.

Please refer to the details at.

Hundreds of users can share computing resources in Oscar. such as cores and GPUs.

More than 500

Oscar has 8 PB of all-flash storage from VAST, which provides high-performance access to storage. Users have ~/home, ~/scratch, and ~/data directories as their storage with quota in Oscar. Please refer to the details at .

Users can from and to. In particular, users can

Send email to . A ticket will get created and CCV staff will attempt to address the issue as soon as possible.

Send email to .

CCV staff provides tutorials on using Oscar for classes, groups and individual. Please check for upcoming trainings and office hours.

CCV Rates page
get sponsored Brown accounts
Acceptable Use Policy
Computing Passwords Policy
Computing Policies
Oscar hardware
Slurm is used in Oscar to manage user jobs and computing resources
software modules
Oscar's filesystem
transfer files
Oscar filesystem
transfer files between Oscar filesystem and Campus File Storage.
SSH
Open OnDemand
VS Code Remote IDE
support@ccv.brown.edu
support@ccv.brown.edu
CCV Events
Center for Computation and Visualization (CCV)
support@ccv.brown.edu
LogoCCV New User Account