Geyser and Caldera

Hardware | Central file systems | License use guidelines

 

The Geyser and Caldera clusters are being decommissioned at the end of December 2018.
Please use the new Casper system for data analysis and visualization.

 

 


Hardware

Geyser

16 large-memory nodes

1 TB DDR3-1600 memory per node (1000 GB usable memory per node)
IBM x3850, quad-socket nodes
Four 10-core, 2.4-GHz Intel Xeon E7-4870 (Westmere EX) processors per node
FDR Mellanox InfiniBand, full fat tree
1 NVIDIA GPU per node

Caldera

30 nodes, 16 with GPUs

64 GB DDR3-1600 memory per node (62 GB usable memory per node)
IBM x360 M4, dual-socket nodes
Two 8-core 2.6-GHz Intel Xeon E5-2670 (Sandy Bridge) processors per node with AVX
FDR Mellanox InfiniBand, full fat tree
2 NVIDIA GPUs per node (16 nodes)

Central file systems

Geyser, Caldera, and Cheyenne all mount the central GLADE file systems. This means you can analyze your data files in place, without sending large amounts of data across a network or creating copies in multiple locations. Some differences between Cheyenne, Geyser, and Caldera architectures are addressed here: Where to compile.


License use guidelines

The CISL user community shares a limited number of licenses for running MATLAB, MATLAB Toolboxes, and some other applications.

Follow these guidelines to ensure fair access for all users:

  • Avoid monopolizing these licenses.
  • If you need to use multiple licenses at one time, be considerate of others and finish your session as quickly as possible.
  • Close applications when you are done to free up licenses for others to use.

CISL reserves the right to kill jobs/tasks of users who monopolize these licenses.

To see how many licenses are being used, run licstats at your command line.

licstats

Run it with option -h for additional information.

licstats -h

MATLAB alternative - Octave

Many MATLAB codes run with very little or no modification under Octave, a free interactive data analysis software package with syntax and functionality that are very similar to MATLAB's. Since using Octave is not constrained by license issues, we encourage MATLAB users to try it, particularly those who have long-running MATLAB jobs. Depending on compute intensity, Octave usually runs slower than MATLAB but it may be suitable for most data analysis work and you won't risk having jobs killed because of a lack of licenses.

To use Octave interactively, start an interactive job and load the module.

module load octave

Run octave to start the command line interface, or run the following command to use the GUI.

octave --force-gui