General questions
Haas management has decided that Research computing needs to be managed by two different departments, One department manages windows based research computers and the other department manages Linux based computers. Please click here to view the services offered to reserachers and instructors.
In general, anytime you have a question or an issue to report, you can email helpdesk@haas.berkeley.edu. If you wish, you can contact tony_cricelli@berkeley.edu directly since he is the web developer and database administrator for this site.
Haas maintains four general use clusters:
  • Ubuntu-based Linux Cluster
  • Microsoft-based Windows Cluster
  • Kubernetes Jupyterhub-based Cluster
  • Analytic Environment on Demand (AEoD) for custom Virtual Machines
    Haas maintains the following software packages
  • Matlab
  • SAS
  • Python
  • R
  • C,C++,Fortran
  • Julia
In general, Haas has systems administrators, not programmers. The Haas administrators main duties are to keep the computer systems updated and available 24/7. Systems administrators also ensure that research software applications are fully-functioning. It does not hurt to ask, the Haas administrators have helped thousands of students debug codes over the years. Send an email to helpdesk@haas.berkeley.edu and ask for a Haas Research Computing staff member for assistance.

The Berkeley Data Lab (D-Lab) provides consulting for research applications and programming languages. Go here D-Lab Consulting to schedule a consulting appointment.

Jupyterhub is a web interface to other software such has Python, R, SAS, MATLAB, etc.... R and Python are the main two languages used.
Kubernetes is the software we use to manage our Jupyterhub teaching workload. It manages containerized workloads and services automatically.
Yes, we use Kopia to do encrypted snapshots every 12 hours. The snapshots are stord in the Google Cloud.
Yes, we use Kopia to do encrypted snapshots every 12 hours. The snapshots are stord in the Google Cloud. We will keep the last 60 snapshots which allow us to go back 30 days.
Yes, we use Kopia to do encrypted snapshots every 12 hours. The snapshots are stord in the Google Cloud. We will keep the last 60 snapshots which allow us to go back 30 days.
Yes, we snapshot research data located on our HPC cluster to Google Cloud every 12 hours. In case of emergency, we can spin up a cluster on Google cloud and restore latest snapshot. Our specific procedure is: we would allocate a Google Filestore large enough to be able to restore data. We would then allocate a Linux based (Ubuntu 20.+) node and mount our Kopia snapshot to it. We would first mount the /etc snapshot to recover all accounts and passwords. Then we would mount the /apps folder to recover all installed apps and finally we would mount the /home snapshot and have immediate account to all research data. Then we would mount the Google Filestore and start copying the research files from the mounted /home snapshot. We estimate this would take 4 hours to complete.
Linux Cluster FAQs
Please email helpdesk@haas.berkeley.edu and request access to the Haas Linux research cluster.
In order to access the Haas research cluster, you must be on the U.C. Berkeley network or have the Berkeley VPN connected. SSH and SFTP are the only two connection methods supported.
There are many ssh and sftp clients available so it is mostly personal preference.
  • MacOS ships with ssh. Many researchers, open a terminal windows and enter: ssh haas-hpc00.haas.berkeley.edu
  • Windows has two main clients researchers tend to use, putty and mobaxterm, both freely downloadable. Download puTTY here: puTTY Downloads. Download MobaXTerm here: MobaXTerm Download
  • Fast-X is an excellent SSH client that accelerates GUI-based applications such as XSTATA, RStudio, Spyder and others. FastX is available for Windows, MacOS, and Linux. Download here: FastX Downloads
Yes open a ticket by emailing helpdesk@haas.berkeley.edu You can also contact tony@haas.berkeley.edu or zane@berkeley.edu directly. We will do our best to install any package that is available to us and does not break the system.
Yes ! You may create your own Python environment with this command: conda init bash
Yes ! There are several ways to run it. Below are the setup directions:
Two  Steps in preparation to launch jupyter that only have to be done once:

1. Create your virtual Environment:
   conda init bash
   conda create -n my_new_environment_name
   conda activate  my_new_environment_name

2. Pick a browser that you normally do not use on your computer. Some browser names
   are Chrome, Brave, Disenter, FireFox, Opera, Edge, etc....


   This browser is going to be set up differently than your normal browsers. 
   It is going to  be set up so that it uses a "proxy".  The proxy  is 
   going to be created by ssh.

   I chose firefox as my jupyterhub browser. After starting the browser:

   a. Click on the 3 horizontal lines on the upper left of the browser (often called the "hamburger")
   b. Click on preferences
   c. Click on General on the right
   d. Scroll to the bottom of the page
   e. Click on settings under network settings
   f. Select Manual proxy configuration
   g. Click on Socks Host box and enter 127.0.0.1
   h. In the port box put a number in, like 3456
   i. Click OK and save it.

   What we just did is force the browser to "surf" through localhost port 3456.

Next are the steps to launch a jupyterhub-notebook job to the cluster and use ssh
to connect  your local browser to the HPC computer node running jupyterhub.

  1. ssh to hpc.haastech.org:

     ssh -C -D 3456 username@hpc.haastech.org

  2. launch jupyterhub:
     /apps/bin/jupyturehub

     (make note of JobID)

  3. run bpeek command after about 10 seconds waiting for jupyterhub to start:
     bpeek jobid

     Towards the bottom of the output, you will see something like this:

        http://haas-hpc10:2225/?token=72abceasyas1230b3b52a2220055eb1662f628e12707c5e3

  4. The final step is to enter the above URL into your home browser that is being proxied.
     But you will run into a problem because your home computer does not know what
     haas-hpc10 is. From home you have to put the IP address, so haas-hpc10 becomes 10.10.10.20.

     Examples:
     haas-hpc01  becomes 10.10.10.11
     haas-hpc07  becomes 10.10.10.17
     haas-hpc08  becomes 10.10.10.18
     haas-hpc09  becomes 10.10.10.19
     haas-hpc10  becomes 10.10.10.20

     So the output of the third step was:

     http://haas-hpc10:2225/?token=72abceasyas1230b3b52a2220055eb1662f628e12707c5e3
     but you change it to this:
     http://10.10.10.20:2225/?token=72abceasyas1230b3b52a2220055eb1662f628e12707c5e3


   5. Enjoy  your custom jupyterhub! Since you are in a virtual environment, 
      you may  add custom languages and custom libraries.  You can close your 
     browser at any time  and return days later and pick up where you left off.

The cluster offers several queues for users of varying sizes. The command to use is
bqueues
. To submit a job to a specific queue use the bsub command with the -q option. For examples:
bsub -q Queue Name
.
Sometimes this question comes up and is tricky to answer. It is akin to asking, I have access to a Boeing 747, how do I fly it? The answer could be, first sit in the pilots seat ... The cluster is a computer, you can edit files, store files, write programs in many languages, run interactive jobs, run batch jobs, etc...
The Linux cluster has the following softare installed:
  • STATA, SAS, Matlab
  • R, Python, Julia, C, C++, Fortran
  • Bash, Perl, Awk
  • Emacs, Vi, RStudio, Spyder
  • Jupyter Notebook, JupyterHub

  • The FastX clients are here:
    Google Drive
    Once you have fastx installed, on startup you should see something like this:

    Click the + and add your information:


    Click OK then double click on the line that shows up:



    On the next screen you will see another + sign:



    You will see:



    I use XFCE as my GUI.
    That will get you this:

    All the setup will be saved, next time you start up fastx, it will pick-up where you left off. All the above setup is done just once.
    You may safely ignore this window if it pops up. We do not run the webserver part of FastX

    Windows Cluster FAQs
    Send an email to helpdesk@haas.berkeley.edu with your CalNet ID.
    Use a remote desktop client to connect to TS-Research.haas.berkeley with your Calnet ID and your passcode.
    Send an email to helpdesk@haas.berkeley.edu with your CalNet ID.
    Send an email to helpdesk@haas.berkeley.edu with your CalNet ID.
    Send an email to helpdesk@haas.berkeley.edu with your CalNet ID.
    Send an email to helpdesk@haas.berkeley.edu with your CalNet ID
    Send an email to helpdesk@haas.berkeley.edu with your CalNet ID.
    Yes, you can save your files or folders on your documents and download folders. Make sure to back up your files or folders.
    ANACONDA Navigator
    IBM SPSS AMOS
    IBM SPSS Statistics
    MATHEMATICA
    Matlab
    Python
    R
    Rscript
    SAS
    STATA SE/MP
    AEoD VM Service FAQs
    The AEoD cluster itself is not on the public Berkeley network so it is not accessible. The VMs we install for you are accessible via https://citrix.berkeley.edu -- sign in with your CalNet ID and passphrase. Then look for your VM under the "Desktops" section.
    Please send an email to helpdesk@haas.berkeley.edu or zane@berkeley.edu with your requirments: Operating System, RAM, disksize, backup requirements, software to be installed, admin access, Calnet IDs of users who need access, etc...