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Research Computing Systems |
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Research Computing aims to provide a friendly, integrated environment for high
performing computational resources. These consist of large memory machines,
tightly coupled clusters, distributed systems,
and connectivity to various grid resources.
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In addition, we provide fast, reliable data storage systems
optimized for research data and connected by advanced 10 Gigabit networks
as well as common libraries, compilers, and software packages.
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To apply for a research computing account, please go to http://rc.rit.edu/apply
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Combined Systems Status Page
Systems Status Reports Archive
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lmc
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An SMP (Symmetric Multi-Processor) large memory machine,
(similar to a desktop workstation), but larger.
It is targeted to run interactive and single threaded
jobs that may be memory, cpu, or disk
bound on a researcher's office workstation.
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It has two dual core AMD Opteron
processors rated at 2.8 GHz, 32 GB of
main memory, and connected via NFS to our high performance fileserver.
lmc status
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condor
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Condor flocks are groups of workstations
that individually volunteer to run
pieces of jobs that don't have to communicate
with each other while running. Condor jobs run only if no other jobs/users need the system.
UW-Madison CS Pool
Condor Pools by state
Purdue Pool
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Currently there over 1000 clients in the Research
Computing condor system. These consist of Sun/Solaris,
Windows, MacIntosh, and Linux computers.
The Condor Project facilitates
High Throughput Computing (HTC).
RC Pool aggregate snapshot
RC Pool machine & job stats
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cluster
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A cluster of
44 server nodes, each built from dual P3 1.4
GHz processors and 512 MB RAM. This
linux cluster was designed to run parallel
computing jobs that are tightly coupled
and use the MPI over high speed
interconnects (currently 1 Gigabit
ethernet switched network).
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It also runs multiple serial jobs that do
not need to communicate with each
other but expect to run on dedicated
processors. Completely indeterministic
serial jobs will also run here in the
background under Condor when other
queued jobs are not utilizing all of the
processors.
cluster home page
cluster status
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