Oscar

Oscar is Brown's high-performance computing cluster managed by the Brown Center for Computation and Visualization (CCV). Long-term visitors to ICERM with a Brown sponsored ID are provided with an exploratory account on Oscar upon arrival. Oscar access may also be requested by short-term visitors on a request-basis with advance notice.

Overview of Oscar
SSH Access to Oscar
Open OnDemand Access to Oscar
Oscar Software Modules

Currently Available Modules
Oscar: Sage
Oscar: MATLAB
Oscar: Mathematica

Overview of Oscar

Long-term visitors to ICERM who receive a Brown ID are provided with an exploratory account on the Oscar high performance computing cluster maintained by Brown's Center for Computation and Visualization. Oscar access may also be provided to short-term visitors on request-basis with advance notice.

If you are coming for a short-term visit and would like to request Oscar access, please contact ICERM IT staff no later than three weeks before your planned visit to ensure enough time to process a sponsored ID and enable Oscar access.

Oscar can be used via SSH terminal or via Oscar OnDemand through a web browser.

Using Oscar

Oscar provides both command line (SSH) access and VNC through Open OnDemand access to the computing cluster. All Oscar accounts are capable of using both interfaces, so you should choose the method that will work best for what you are trying to accomplish.

Oscar accounts are tied to Brown Shibboleth accounts, so you must have an ICERM Sponsored Brown ID to use Oscar. Once Oscar access is enabled for your Brown account, you can log in to CCV resources using your Brown Shibboleth username and password.

SSH Usage

Oscar's SSH interface provides a standard command line shell for interacting with the cluster. This is the best option for using simple command line scripts and submitting scripts for batch job processing. See the SSH Login Instructions for information on how to connect and basic usage. It's important to note that you should never run complex scripts or computations within the SSH login nodes. Computations should either be submitted as batch jobs or run in an interactive compute session using the interact command.

Open OnDemand

Oscar's OOD is a web portal to the Oscar computing cluster. This is the easiest way to access a number of CCV resources including an Oscar Shell, interactive applications like MATLAB, and a fully featured Linux GUI. See the OOD Login Instructions for information on how to get started with the web portal.

Available Software

Oscar maintains a large library of software packages for use on the HPC cluster. Some of the most commonly used mathematical applications and languages available include:

MATLAB
Mathematica
Sage
Julia
R
Python
Maple
Magma

To see the most up to date list of available software, log in to your Oscar account and run the terminal command module avail.

Loading Software Modules

Oscar has a large library of software available on the cluster, but only a few apps are pre-loaded in to your sessions. The commands below will allow you to list all available modules, search the list of modules, and load/unload software packages. When using Oscar over the Linux GUI, you must open the Terminal Emulator to run these commands.

To view all available software packages, type module avail.
To search the list of available packages, type module avail <package>.
For example, to search for all available versions of mathematica: module avail mathematica. Many packages, like Mathematica, have multiple versions available. This command lets you see all available versions of the package you searched for.
To load a package into your session, type module load <package/version>.
For example, module load mathematica/11.0. This will load the Mathematica 11.0 into your session and make it available for use.
To unload a package you are no longer using, type module unload <packagename>

Module-specific Guides

Running Jobs

Oscar supports two main methods of running jobs: batch jobs and interactive sessions.

Batch jobs are pre-scripted and can be submitted to the cluster's scheduler via the sbatch command.
Interactive jobs are command-line sessions run directly on a compute node via the interact command that can be used in real time.

The Running Jobs page of the Oscar User Manual provides the most detailed and up-to-date instructions on scripting and submitting jobs.

Important Notes About the Oscar Cluster

Please do not run any computations or simulations on the login nodes, as they are shared with other users. Use SLURM to submit a batch job to the queue for computations or start an interactive session on one of the compute nodes with the command interact.
The full Oscar User Manual is available on the CCV website.
Oscar uses SLURM for managing batch jobs and interactive sessions on the cluster. Detailed instructions on submitting jobs is available on the Running Jobs page of the Oscar User Manual.
CCV has a large library of software already installed on the cluster. For a full list of available software, run the command module avail. More information about Oscar's software packages are available in the Oscar User Manual. If you require a software package that is not currently available on the Oscar cluster, please contact ICERM's IT staff and we will work with CCV to get the software installed.
Users can install sub-packages for some modules (like Sage and Python) to their home folders on their own by using the –user as an option in the install command. For example, with Sage, the command would be something like sage -i <package name> –user.

If you have questions about these instructions or require further assistance, please contact the ICERM IT staff by dropping by the administrative offices or emailing support@icerm.brown.edu.

SSH Access to Oscar

1. Open your preferred terminal application.

2. In the terminal, type ssh <your ccv username>@ssh.ccv.brown.edu. If you are asked to verify the authenticity of the host 'ssh.ccv.brown.edu', type yes.

3. You will now be prompted for your password. Enter your password (nothing will show up when you type in the terminal password prompt) and press enter.

4. Once logged in, you should see a “Welcome to Oscar!” message. This means you're now connected to one of the login nodes, which you can use to manage your files and submit batch jobs.

Please DO NOT run any computations directly on the login nodes. Use the batch system to submit your computations to the queue to be processed on the computation nodes or start an interactive session on one of the compute nodes with the command interact. See CCV's Oscar Documentation page on Running Jobs for detailed instructions on batch jobs and interactive sessions.

Open OnDemand Access to Oscar

Open OnDemand (OOD) is a web portal to the Oscar computing cluster. An Oscar account is required to access Open OnDemand. Visit this link in a web browser and sign in with your Brown username and password to access this portal.

Benefits of OOD:

No installation needed. Just use your favorite browser!
No need to enter your password again. SSH into Oscar in seconds!
No need to use two-factor authentication multiple times. Just do it once, when you log into OOD.
Use it with, or without, VPN. Your workflow remains the same.

Once logged in you'll see a landing page that looks similar to the photo below:

Screen Shot 2022-10-26 at 13.57.44.png

Guides to help you figure your way out once logged in:

Using File Explorer on OOD

Web-based Terminal App

Interactive Apps on OOD

Using Python or Conda environments in the Jupyter App

Oscar Software Modules

List and instructions for software modules available on the Oscar cluster.

Oscar Software Modules

Currently Available Modules

If you require a software package that is not currently available on the Oscar cluster, please contact ICERM's IT staff and we will work with CCV to get the software installed.

This list is current as of January 7, 2025. To see the most up to date list of software modules, log into your Oscar account and run the command module avail.

---- /oscar/runtime/software/spack/0.20.1/share/spack/lmod/linux-rhel9-x86_64/Core ----
   abaqus-container/2021-akaeexs
   abaqus/2017-q4ghhm5
   abaqus/2021.1-i675dvw
   abaqus/2024-h5273a3                       (D)
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   gaussian/16-C01-bb2r2gh                   (D)
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   go/1.23.3-d3wvs6z                         (D)
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   python/3.11.0s-ixrhc3q                    (D)
   qgis/3.28.3-5axmqsj
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   quantum-espresso-mpi/7.1s-ia43pjk
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   r/4.0.0-p7gxu4e
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   rust/1.73.0-647r2tw
   rust/1.81.0-3qqoayc                       (D)
   sage-container/10.3-avpqipf
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   schmutzi-container/1.5.7-3imwf7h          (D)
   schrodinger/2023-4-h3kvbn3
   schrodinger/2024-1-yqi27-m4qqm46          (D)
   scons/4.5.2-housgyw
   seqkit/0.10.1-qtiftw4
   seqtk/1.3-kbdjwob
   shapeit4/4.2.2-3us45un
   singular/4.4.0-aeloppr
   skewer/0.2.2-nwhklgr
   slicer/5.4.0-rb2kk4l
   slim/4.0.1-kymgtmu
   slim/4.3-u22vcwu                          (D)
   spdlog/1.11.0-qbi24my
   splash/2.1.4-unrsfpj
   spm/8-77b5myx
   spm/12_r7606-prcq7fg                      (D)
   sratoolkit/3.0.0-u4jvgps
   stacks/2.65-geg4r7a
   star/2.7.10b-fj6kao2
   stata/mp17-v7a7uoo
   stata/mp18-3wq5b4o                        (D)
   stow/2.4.0-y2q7tsn
   stringtie/2.2.1-7uti3ny
   sublime-text/4.4143-im3loi3
   subread/2.0.2-5agghnd
   swig/4.1.1-bq46cxl
   synopsys/2023.12-df4a3ab
   synopsys/2024.09-q3jwzot                  (D)
   tabix/2013-12-16-d6qvxp7
   tcsh/6.24.10-dtqo5ky
   tecplot/2022r1-q5cg2zq
   tesseract/4.1.1-l2ejycz
   tesseract/5.3.3-vq3altt                   (D)
   texlive/20220321-pocclov
   texstudio/3.0.1-64vxo64
   tmux/3.3a-zyhjvvh
   tn93/1.0.12-tcvbyl4
   tree/2.1.0-7tlhzo7
   trimal/1.4.1-ace7du2
   trimgalore/0.6.6-iwfrq4c
   trimgalore/0.6.9-hisz5xp                  (D)
   trimmomatic/0.39-w5jnhai
   udunits/2.2.28-rycabdx
   usearch/11.0.667-wx6utmj
   v8/3.14.5-aompxje
   vasp-mpi/5.4.4-mdh3hpy
   vasp-mpi/6.3.2_avandewa-chn3w3j
   vasp-mpi/6.4.2_cfgoldsm_vtst-cff5qmk
   vasp-mpi/6.4.2_cfgoldsm-7krhcss
   vasp-mpi/6.4.3_yqi27-6uzdgwn              (D)
   vcftools/0.1.14-syssqsi
   vim/9.1.0867-wl3haj7
   virtualgl/3.1-yphbrfj
   visit-container/3.3.3-qz3dni6
   visit-mpi/3.3.3s-lz2dp7m
   vmd/1.9.3-oin2dnj
   vscode/1.84.2-4tfimgp
   wcstools/3.9.7-lo4forb
   wxwidgets/3.2.2.1-mk5eiyq
   xcrysden/1.5.60-nuxe46i
   xeyes/1.2.0-nge56yb
   xgboost/1.6.2-fp3ii65
   yaml-cpp/0.7.0-6nno2ru
   zlib/1.2.13-jv5y5e7
   zoxide/0.9.2-ydhigq6
   zstd/1.5.5-zokfqsc

Oscar Software Modules

Oscar: Sage

Loading and Launching Sage

1. Once authenticated to Oscar, use the following commands at the command line.

2. Start an interactive job by using the interact command. This command can take additional parameters to extend the resources and time allotted to the node as well as the partition that the node operates on.

3. The Sage module provides containers. To load them use module load sage-container/10.3.

4. To start the container use apptainer shell /oscar/rt/9.2/software/0.20-generic/0.20.1/opt/spack/linux-rhel9-x86_64_v3/gcc-11.3.1/sage-container-10.3-avpqipfsnbneig726l72jrgdmlrivg4m/sage.sif

5. Once inside the container's shell use sage to launch the Sage console.

Sage on Oscar OnDemand

The easiest way to run Sage on Oscar OcDemand is to run sage in an interactive job via the terminal in your OnDemand session.

Use the interact command with parameters for your specific job to start the interactive session, then load your modules and run the sage binary (steps 2-4 above).

interact -n 2 -m 32g -t 04:00:00 -f 'haswell|broadwell|skylake'

Using Sage with Batch Scripts

Thanks to Trevor Hyde from Summer@ICERM 2019 for these instructions.

One method for running computations with Sage on Oscar is to write a script and use the slurm batch scheduler to have Oscar run your script. This requires two pieces:

A shell script to configure and submit your batch job to the cluster.
Your Sage code/program you'd like to run.

Example Batch Script

sage-batch.sh

#!/bin/bash
 
#SBATCH -J test_program
#SBATCH --array=0-9
#SBATCH -t 1:00:00
#SBATCH --mem=8G
 
#SBATCH -e data/<oscar-username>/test_output/test%a.err
#SBATCH -o data/<oscar-username>/test_output/test%a.out
 
module load sage-container/10.3

apptainer shell /oscar/rt/9.2/software/0.20-generic/0.20.1/opt/spack/linux-rhel9-x86_64_v3/gcc-11.3.1/sage-container-10.3-avpqipfsnbneig726l72jrgdmlrivg4m/sage.sif
 
sage test_program.sage $SLURM_ARRAY_TASK_ID

#!/bin/bash tells the system this is a bash (shell) script.
#SBATCH -J test_program sets the name of the job which appears when you check the status of your jobs.
#SBATCH –array=0-9 is an easy way of doing parallel computations. In this case it says our job will run on 10 different nodes, each node will be passed a parameter and we have specified that the parameters will take the values 0 through 9. You can specify several ranges or even list individual parameters if you prefer.
#SBATCH -t 1:00:00 specifies a time limit in HH:MM:SS for each node. Once this time runs out your program will stop running on that node. Be careful setting the time limit too high as doing so may make it take a long time for your job to get scheduled to run. Before starting a big computation try to do some smaller tests to see how long you expect to need.
#SBATCH –mem=8G specifies how much memory each node gets. Standard exploratory accounts get 123GB total to use at any one time. So if you allocate too much per job, fewer jobs will run at once. On the other hand, if you allocate too little and a computation needs more than it has, then it will terminate. If this happens an “out of memory” error will show up in the .err file for that node.
#SBATCH -e data/<ccv-username>/test_output/test%a.err and #SBATCH -o data/<ccv-username>/test_output/test%a.out specify where the error messages and output for each computation should be sent. You should store these files in your user folder, not on the submit node. We each have a folder inside the data directory which you can see from the submit node. In this example I have created a folder titled test_output where I’m putting both of these files. You need to make these folders before you run the computation otherwise the output will be dumped into the void! The %a will get replaced with the array parameter. So for example, since we set our array parameters to be 0-9 there will be 10 nodes running and each of them gets a number between 0 and 9; this node corresponding to the parameter 7 will create two files test7.err and test7.out.
module load sage-container/10.3 loads the sage container into the node.
apptainer shell /oscar/rt/9.2/software/0.20-generic/0.20.1/opt/spack/linux-rhel9-x86_64_v3/gcc-11.3.1/sage-container-10.3-avpqipfsnbneig726l72jrgdmlrivg4m/sage.sif initiates the container's Sage console shell.

Everything after this in the script happens as if you typed it yourself onto the command line.

In our example, we want to run sage code, so the line sage test_program.sage $SLURM_ARRAY_TASK_ID runs our example sage program test_program.sage.
The file needs to have the .sage extension.
You should write this file in a text editor, not in a Jupyter notebook (although you can first write and test your program in a Jupyter notebook and then copy and paste it into a new file when it’s ready).
This program is written to accept one input and I have passed it $SLURM_ARRAY_TASK_ID which is the array parameter passed to each node. You can use this parameter to select which input parameters to run your program on.

Example Sage Program

test_program.sage

import sys
 
def fun_math(message):
    print message
    sys.stdout.flush()
 
job_id = int(sys.argv[1])
fun_math('hi this is a test')
fun_math('my job id is' + str(job_id))

In the Sage program, you first define all of your functions and then you include the code you want to run.
Import sys so you can access the array parameter passed to your function from the node. This is accessed in this case by sys.argv[1]. Make sure you explicitly coerce to be an integer if you want to use it as an integer; it's a string by default.
The output of the print command is appended to the .out file for this node as a new line.
Notice the line sys.stdout.flush() included in the function. This makes the program immediately send whatever output it has to the output file when called. Otherwise the program won’t output anything until it has completely finished running. If each node is running 100 potentially long computations and it finishes the first 99 but then times out on the 100th computation, and you don’t include any sys.stdout.flush() commands, everything will be lost when time runs out.

Submitting the Batch Job

To run this batch program go back to the submit node and type sbatch <NAME_OF_BATCH_FILE>. In our example here, our batch file is called sage-batch.sh, so we simply type sbatch sage-batch.sh Slurm will return a line that tells you your job has been submitted together with a job id number.
To check the progress of your jobs type myq from anywhere on Oscar. This will show you what jobs you have running, how much time they have left, and which jobs are still waiting to run. Be patient, sometimes it takes a minute for things to get started.
If you realize your code is never going to finish or that you’ve made some terrible mistake, you can cancel a batch job by typing scancel <JOB_ID>. You can specify a single node or just put the general job id for the whole run and cancel everything.

Oscar Software Modules

Oscar: MATLAB

Loading and Launching MATLAB

1. Open the Terminal and use the following commands at the command line.

2. module avail matlab to list all the available matlab versions.

3. module load matlab to load the latest version of matlab (R2023a). Other versions can be specified with the command module load matlab/R2019a.

4. matlab to launch the MATLAB app.

Installing MATLAB Packages such as YALMIP

MATLAB script packages, such as YALMIP, can be installed directly by the user on their Oscar account.

1. Open the Terminal and connect to Oscar.

2. Navigate to your home folder by typing cd ~

3. mkdir -p MATLAB

4. wget -O yalmip.zip https://github.com/yalmip/yalmip/archive/master.zip

5. unzip yalmip.zip

6. In MATLAB, add the YALMIP-master directory to your path.

In the MATLAB file browser, navigate to the MATLAB folder you created in your home folder. cd ~/MATLAB
Right click on the YALMIP-master folder.
Select Add to Path > Selected Folders and Subfolders. This adds the YALMIP folders to your path.

7. To save your MATLAB path, use the savepath command in the MATLAB command prompt. savepath ~/MATLAB/pathdef.m

YALMIP also requires a solver like SDPT3. The steps below add SDPT3 to MATLAB.

1. Open the Terminal.

2. cd ~/MATLAB

3. wget -O sdpt3.zip https://github.com/sqlp/sdpt3/archive/master.zip

4. unzip sdpt3.zip

5. In MATLAB, add the sdpt3 directory to your path.

In the MATLAB file browser, navigate to the MATLAB folder you created in your home folder. cd ~/MATLAB
Right click on the sdpt3-master folder.
Select Add to Path > Selected Folders and Subfolders. This adds the SDPT3 folders to your path.

6. To update/save your MATLAB path, use the savepath command in the MATLAB command prompt. savepath ~/MATLAB/pathdef.m

Oscar Software Modules

Oscar: Mathematica

Loading and Launching Mathematica

1. Open the Terminal and use the following commands at the command line.

2. module avail mathematica to list all the available mathematica versions.

3. module load mathematica to load the latest mathematica version.

4. mathematica to launch the Mathematica app.