General questions
Haas maintains four general use clusters:
  • CentOS 7 based Linux Cluster
  • Microsoft based Windows Cluster
  • Kubernetes Jupyterhub based Cluster
  • VMware Cluster for custom Virtual Machines
    Haas maintains the following software packages
  • Matlab
  • SAS
  • Python
  • R
  • C,C++,Fortran
In general, Haas has systems administrators, not programmers. The Haas administrators main duties are to keep the computer systems updated and available 24/7. It does not hurt to ask, the Haas administrators have helped thousands of students debug codes over the years.
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.
Linux Cluster FAQs
Please email Maggie 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.
  • OSX ships with ssh. Many researchers, open a terminal windows and enter: ssh yogi.haas.berkeley.edu
  • Windows has two main clients researchers tend to use, putty and mobaxterm, both freely downloadable.
Yes open a ticket by emailing helpdesk@haas.berkeley.edu . You can also contact tony@haas.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: /home/campus.berkeley.edu/apps/Anaconda3/bin/conda init bash
Yes ! There are several ways to run this, the easest is to submit a job to the cluster and then using firefox to connect to it. For example, this command:
 bsub -q 4C-16G  -Is  /home/campus.berkeley.edu/apps/Anaconda3/bin/jupyter-notebook --ip="0.0.0.0" --port 61001 
will submit a job to the queue that has 4 core machines with 16 Gigs of ram. Notice the --port is 61001. You should choose your own random port. You will see something like this:
Job <1621> is submitted to queue <4C-16G>.
<>
<>
[I 15:38:42.212 NotebookApp] JupyterLab extension loaded from /home/campus.berkeley.edu/apps/Anaconda3/lib/python3.7/site-packages/jupyterlab
[I 15:38:42.212 NotebookApp] JupyterLab application directory is /home/campus.berkeley.edu/apps/Anaconda3/share/jupyter/lab
[I 15:38:42.215 NotebookApp] Serving notebooks from local directory: /home/campus.berkeley.edu/pvt-tony
[I 15:38:42.215 NotebookApp] The Jupyter Notebook is running at:
[I 15:38:42.215 NotebookApp] http://cn-08.haas.local:61001/?token=915ff8ca2f3b792f28408c2894b2856a4332864b4e03d713
[I 15:38:42.215 NotebookApp]  or http://127.0.0.1:61001/?token=915ff8ca2f3b792f28408c2894b2856a4332864b4e03d713
[I 15:38:42.215 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[W 15:38:42.226 NotebookApp] No web browser found: could not locate runnable browser.
[C 15:38:42.226 NotebookApp]

    To access the notebook, open this file in a browser:
        file:///home/campus.berkeley.edu/pvt-tony/.local/share/jupyter/runtime/nbserver-7179-open.html
    Or copy and paste one of these URLs:
        http://cn-08.haas.local:61001/?token=915ff8ca2f3b792f28408c2894b2856a4332864b4e03d713
     or http://127.0.0.1:61001/?token=915ff8ca2f3b792f28408c2894b2856a4332864b4e03d713
Then use firefox to connect to http://cn-08.haas.local:61001/?token=915ff8ca2f3b792f28408c2894b2856a4332864b4e03d713
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 R, Python, Stata, SAS, Matlab, C, C++, Bash, PERL, Awk and Sed.
Yes, once you are able to loging, please email helpdesk or tony@haas.berkeley.edu. The data will be transferred for you. or you can use sftp/scp to do it yourself.
The Equallogic Storage units used for Bear will not be destroyed intentionally and left up and running for as long as possible. The old disk drives needed are becoming difficult to find and we are having to resort to purchasing "refurbished" drives. We do back it up and should always have the data to restore if someone needs it.
R-Studio is an integrated development option ment to develop R scripts. So most of the time it is run on the desktop. It is freely available on the "web" for many platforms. In previous Haas work flows, students would develop scripts on their personal computers and then run those scripts on the cluster. For development work, a free website provides R-Studio https://rstudio.cloud . Haas also provides R-studio at rstudio.haas.berkeley.edu for developement work. Haas is working on providing an R-Studio server on the Yogi research cluster which provides multi-cpu-core and high memory access.
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
VMware Cluster FAQs
The VMware cluster itself is not on the public Berkeley network so it is not accessible. The VMs we install for you will receive a public IP address that you will use.
Please send an email to helpdesk@haas.berkeley.edu with your requirments: OS, RAM, Disksize, Firewall Port Settings, IP addresses needed, Backup requirements, Admin Access, etc...