The CSDMS High Performance Computing Cluster (HPCC), beach.colorado.edu, provides CSDMS researchers a state-of-the-art supercomputing facility. Use of the CSDMS HPCC is available free of charge to the CSDMS community! Follow these guidelines to request a one year guest account on our machine.
The CSDMS High Performance Computing Cluster is an SGI Altix XE 1300 that consists of 88 Altix XE320 compute nodes (for a total of 704 cores). The compute nodes are configured with two quad-core 3.0GHz E5472 (Harpertown) processors. 62 of the 88 nodes have 2 GB of memory per core, while the remaining nodes have 4 GB of memory per core. The cluster is controlled through an Altix XE250 head node. Internode communication is accomplished through either gigabit ethernet or over a non-blocking InfiniBand fabric.
Each compute node has 250 GB of local temporary storage. However, all nodes are able to access 36TB of RAID storage through NFS.
The CSDMS system will be tied in to a 153 Tflop front range HPCC called Janus, that offers 1368 compute nodes with 2 2,8 Ghz 6 core Intel Westmere processors for a total of 16,428 cores employing non-blocking QDR Infiniband network.
Some benchmarks that we've run on beach:
|beach.colorado.edu||Head (Altix XE250)|| 2 Quad-Core Xeon
Processors are Quad-core Intel Xeon E5472 (Harpertown):
Memory is DDR2 800 MHz FBDIMM
|cl1n001 - cl1n056||Compute (Altix XE320)||2 Quad-Core Xeon||16GB||250GB SATA|
|cl1n057 - cl1n080||Compute (Altix XE320)||2 Quad-Core Xeon||32GB||250GB SATA|
|cl1n081 - cl1n088||Compute (Altix XE320)||2 Quad-Core Xeon||16GB||250GB SATA|
Below is a list of some of the software that we have installed on beach. If there is a particular software package that is not listed below and would like to use it, please feel free to send an email to us outlining what it is you need.
Python 2.4 modules:
Python 2.6 modules:
Monitoring Usage on beach
The CSDMS high performance computing cluster uses the Ganglia Monitoring System to provide real-time usage statistics. Note that although we constantly monitor each computational node of the cluster, Ganglia was designed with high performance computing in mind and the monitoring process itself will not negatively impact you job's execution time.
Attribution and Reporting of Results
When reporting results which were obtained on the CSDMS cluster, we request that the following language be used as an acknowledgement:
"We acknowledge computing time on the CU-CSDMS High-Performance Computing Cluster."
Also, please notify us of any tech reports, conference papers, journal articles, theses, or dissertations which contain results which were obtained on beach. Your assistance will help to ensure that our online bibliography of results is as complete as possible. Citations should be sent to us.