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Systems Status

Current System Status


Faculty offices, plus some servers. Of the servers, we currently recommend using only nconstance and richelieu.

These are not very powerful systems. They're intended primarily to keep records in an environment with no students. Serious computing is normally done on the research cluster.

Faculty Machines


Ilab (2nd floor hill) and grad student offices. Most students access these systems remotely, by ssh or XtoGo.  We recommend looking at the usage graphs to find a system that isn't in heavy use.

Instructional Laboratory (iLab) Systems

Graduate Systems

Research cluster

Servers for use by faculty and grad students working on research projects. Faculty can authorize students to have access. The major system here is aurora, a large mult-core system with SSD storage. Older systems tall3 and tall4 are also available.

Research Machines

Research Web Server


Many of our systems have GPUs:

  • 30 of the Ilab systems have Radeon 8830

  • atlas: K40, QuadroK4000

  • cray1: 2 Xeon Phi

  • k40c-1: 2 K40

  • gpu: K40, Titan

CBIM systems

CBIM has a set of servers with large memory and GPUs. Those outside CBIM need permission from Dimitri Metaxas to use them, but that is generally available for CS researchers.

  • 12 Dell systems with 4 K80 each, 512 G memory, 2 SSD

  • 3 HP systems, with 2 K80, 256 G memory, 13 TB disk

High-performance systems: OARC

OARC is a University group that provides high-performance computing. Computer science in general doesn't have a conventional HPC cluster. We concentrate on GPUs and more specialized hardware. For large-scale HPC, OARC is the best source. They have a large cluster, Amarel. It is intended as a "condo" cluster. I.e. grants buy nodes, and are guaranteed at least as much capacity as they purchased. The cost is matched by the University. Howver some capacity is available for those who haven't bought into the system, particularly for course work and student use. 

For more information see the OARC web site.

Some of OARCs nodes have GPUs, typically Nvidia.

Virtual machines

LCSR can provide virtual machines, both for researchers and for use by classes. To request a system, please send mail to

Researchers commonly use VMs for web servers and other support services. We normally put those VMs on the same servers used for LCSR infrastructure.

For course use, we talk with the instructor to find out the configuration and software needed, then create one VM per user. We can also create VMs for grad students. These VMs are placed on one of two large (1 TB each) VM servers purchased specifically for instruction.

Virtual Machines for Student Academic Use

Virtual Machines for Faculty and Research


Windows Remote Desktop


Getting Help

1. If you have issues with any CS computing resources

2. If you have issues with Non CS computing resources