![]() |
Funding for the Millennium Project has ended. A small portion of the Computer Science Department cluster is still operational, but development has been frozen. Please consider using the new CITRIS Itanium 2 Cluster and the PSI Fast Storage Cluster.
Computing has become the third pillar of science and engineering, complementing the traditional activities of theory and experimentation. As a result, adequate computing capabilities are as central a resource at premiere research universities like Berkeley as are libraries and laboratories. Furthermore, information processing activities, such as data base indexing and financial modeling, are becoming more computationally and I/O intensive and require high performance computing facilities. The UC Berkeley Millennium Project aims to develop and deploy a hierarchical campus-wide "cluster of clusters" to support advanced applications in scientific computing, simulation, and modeling. (more)
The Millennium Cluster has been reduced to 1 frontend; napa.Millennium.Berkeley.EDU
and 7 compute nodes; .
|
|
The Millennium Cluster is open for shared interactive use
This
is an unscheduled shared resource. You can view the current use of the machines by running
gstat or viewing the
Ganglia graphs.
gstat provides an ordered list of available machines. Machines
with a load >= 2 are fully loaded and should be avoided until current jobs have
completed.
Run gexec to launch jobs.
cd /work/$user(returns the hostname of 10 machines)
gexec -n 10 hostname(runs foo on 20 machines)
cp $home/foo /work/$user
gexec -n 20 ./foo
For more information on using gexec, please see the documentation.
In keeping with the retro spirit of the Millennium cluster, older LanAI 7.2 Myrinet is available.
If you are unfamiliar with MPI, please read our MPI Tutorial. MPI jobs can be run over gigabit ethernet using our modified P4 version, or over Myrinet 2000 (the preferred, faster way).
IP over Myrinet is available. Nodes can be reached by prepending "m" to the hostname. IP over Myrinet can be disabled during scheduled experiments to free up channels.
While you should be able execute jobs from your EECS department home
directory, we strongly suggest that you launch all jobs from a /work/$user
directory. Before executing a program, copy all binaries
and data files into your /work directory, cd into that
directory, and execute from there. This avoids putting unnecessary load on EECS department fileservers, which
are sometimes unable to handle many simultaneous mount requests.
Note: /work has a 30 day deletion policy.
Any file not touched for 30 days will be deleted
without warning. /work is meant for staging runs on
the cluster, not for long-term storage. /work is never backed up.
Similarly, /scratch is available on every machine
in the cluster. /scratch is non-RAID storage local to each machine and
is intended for use for program check pointing. /scratch has a
similar 10 day deletion policy. Data left on compute nodes is never backed
up.