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Department of Computer Science

Technical Services and Support

VMs for Academic Use

by Hanz Makmur – Jan 25, 2017

LCSR  provides users ability to run virtual machines (VM) for Computer Science users, faculty and graduate students for academic purposes. 
 
Note: If you want to run VMs of your own personal computer, see VMWare software for free VMPlayer you can download.

All these VMs will run in a private network which means they are only accessible with in Rutgers University or within the host VMs. To access it from outside RUNet, please utilize university VPN.

These VMs are divided into 3 categories as followed:

1. Virtual machine for individual student.
  • All our iLab/Faculty Ubuntu 22.04 Linux machines can run user configured virtual machines using KVM and  VMPlayer  app installed on every machine. This user created VM should be used for academic purpose and only temporarily.
  • This type of VM is only accessible from the host it runs on.  
  • Due to disk space limitation, users are recommended to use non quota based storage like /freespace/local or or /filer/tmp1, or larger quota disk like: /common/users/, /common/home  to store the virtual machine.  Please note that /freespace/local  and /filer/tmp1 is  wiped every semester and are NOT backed up.
  • Virtual Machine players can also be run of personal computers via free VMPlayer on WindowsOS or LinuxOS and free VMWare Fusion for Intel based or Apple Silicon Macs.  As of Oct 19, 2023, VMWare Fusion 13.5 also support Apple Silicon and Windows11.
  • We recommend user to use containers likeDockers or Singularity for specialize requirement  like machine learning. Running Docker on CS machines are supported for non root user.
2. Virtual machines for class use.
  • Some classes need special VMs to support educational material taught in class because public machines not equipped to handle.  These type of VMs, normally limited in resources ( mostly 1-2 cores, 4GB of memory and 10GB of disk space). 
  • We recommend user to use containers likeDockers or Singularity  for specialize requirement  like machine learning. Running Docker on CS machines are supported for non root user.
  • If specialized VM is needed, the master copy of the VM should be setup and prepared by the faculty/TAs of the class containing all needed software and configuration needed for the class. Once the VM is ready, it should be submitted to LCSR to be run in our KVM based VM servers.
  • In cases where faculty needs help with generic VM setup for a class to start with, LCSR can provide generic VM that can be changed to meet your class needs. 
  • Please note that class VMs should requested a few weeks before the start of the semester so proper arrangement and testing can be done to avoid problems during the semester. These VMs are also turned off and may be deleted at the end of the semester. Please notify us if these VMs should last longer.
3. Virtual Machines for graduate students academic work
  • Some graduate students may need experiment virtual machine that last longer than a semester in order to complete his/her academic work. For these students, we can run VM with limited resources that can last for the duration of users academic work at Rutgers University.
  • In general this vm is used for experiment and not for sole computing resource for your graduate work.  As such it will be limited at 4 cores, 16GB of memory and 25 GB of disk space.  In cases where you need help with generic VM setup to start with, LCSR can provide generic VM that can be change to meet your class needs. 
  • We recommend user to use containers like Dockers or Singularity for specialize requirement  like machine learning. Running Docker on CS machines are supported for non root user
  • This type of VM is only accessible from inside RUNet and not accessible from the Internet. To access it from outside RUNet, please utilize university VPN.

For help with our systems or If you need immediate assistant, visit LCSR Operator at CoRE 235 or call 848-445-2443. Otherwise, see CS HelpDesk. Don’t forget to include your NetID along with descriptions of your problem.