Current Fingerprints:
2048 05:66:1f:4c:1f:83:9c:dc:9d:31:2e:10:aa:30:a4:c7 (RSA1)BIG NEWS! The upgrade was finally successful. The main server at 150.108.20.61 now has 96 GiB of memory and 8 cores. The secondary server at 150.108.20.62 now has 32 GiB of memory and 8 cores. The new VMWare version means that we can dynamically increase the system memory when necessary (please let me know if your work needs more!)
Additionally, Sage has been updated to 5.12, Magma has been updated to 2.19-10, and Mathematica has been updated to 9.01.
We expect the hardware upgrade to take place next week, probably Wednesday, October 2. If you have long-running jobs, you may want to wait until after the upgrade to start them, so that they are not disturbed.
Sage has been upgraded to version 5.11, with all doctests passing. You can find it at /app/sage-5.11/sage or at /app/bin/sage (which should already be in your command path, so just sage will do).
Errors are cropping up with the System Status graphs, due to poor configuration of the faculty.fordham.edu FTP server. I'm looking into a workaround, but for now the graphs may be truncated or slightly out-of-date. If you are logged into the server, you can always use top or htop to see live status on that server.
The new website, http://faculty.fordham.edu/rcc, is up! Initial documentation is available.
The system is still in `test harness' phase, as we await the delivery of more powerful hardware. Please run jobs and test the environment, but don't expect your jobs to run more quickly than on a standard workstation. Contact the administrator at rcc@fordham.edu if there is anything you need.
I am currently in the process of trying to install SPSS, SAS, and Mathematica from the existing university licenses. There are various annoying technical difficulties, due to poorly made installer programs and version incompatibilities that I'm trying to work out.
A MatLab license needs to be purchased. The best bet is to pool our FREPs ($400 per TT faculty per year) to get a license.
The Research Computation Cluster (RCC) provides a stable and current Red Hat Enterprise Linux environment for computation and data analysis. The primary means of access is Secure Shell (SSH) and the usual Linux command-line environment.
The RCC provides a full suite of open-source scientific and programming tools, including:
This is a multi-user system, and many users may be running jobs at once. Of course, the system is made to be used. There are two things to balance: Processor allocation and memory allocation.
Processor time is easy to sub-divide, as it is divided into time-steps called "jiffies". During a single jiffy on a single processor core, a single process may be run. Thus, if there are two jobs with equal priority are running on the same processor core, the Linux kernel allocates every-other jiffy to each job. Thus, in real time, each job runs half as quickly as it could on its own core. In that sense of time-sharing, CPU time is infinitely divisible.
Memory allocation is more difficult. The machine has a fixed amount of fast physical memory as well as some slow overflow space on disk that is called "swap". Jobs request memory as they run, and there is no way to forcibly remove memory from a job without killing that job. Of course, the Linux kernelneeds some memory to keep essential processes running, too. Therefore, if too much memory is requested by running jobs, the Linux kernel enters the dreaded Out-Of-Memory [OOM] condition and risks crashing. This is like having too much cargo on a sinking ship --- if you can quickly throw some containers overboard, the rest of the ship might be saved. The kernel must decide which jobs to kill.
To deal with both of these problems, there is an hourly process that examines all of the running jobs and classifies them as "young" or "old". Once a job has used 12 processor-hours, it is classified as "old," and thereafter receives 50% of the share of a young job. So, instead of each job getting every-other jiffy, the young job gets two jiffies of every three. The goal is to get short jobs out of the queue as rapidly as possible. Also, "old" jobs are the first to have their active memory pushed to slow disk swap in the event that system memory is low.
However, old jobs are increasingly protected from being killed by the Out-Of-Memory killer. Obviously, your fellow researchers get very upset when a 2-month-old job was killed because your runaway 10-second job ate all the memory. Under the current configuration, by the time a job has been running for 10 CPU-days, it should never be killed by an Out-Of-Memory condition (unless the entire machine crashes for some horrible reason). On the system status pages (linked above), you can see the "OOM Score". The higher the score, the more likely a job is to be killed in an OOM condition. A score of -1000 means "never kill"; a score of "0" is neutral. Even with this fix, we have the potential problem that many 10-day-old jobs could eat all the memory and sink the ship, so please be careful. There is essentially no way to guarantee that OOM will never happen.


SSH allows you to move files over the network using the scp or sftp commands. A more efficient way for bulk transfers is to use rsync, which can recursively transfer entire directories while only moving the changed parts of files. For example:
A good rule of thumb for computers is "if you are typing a complex command more than twice, you are doing it wrong." SSH allows several options to be set for every connection on a per-server basis, using the configuration file ~/.ssh/config. Here is an example:
Host ace1This means that I can type "ssh ace1" and many of my favorite options are automatically used. In this case, it saves me from typing "ssh -C -X -D 9051 -L 8080:localhost:8085 asmith122@150.108.20.61".
It is wise to read the System Manual Pages obtained from the commands "man 1 ssh" and "man 5 ssh_config" to learn what is possible with SSH.
For complete functionality, three programs are used. However, some of them are optional:






















