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How Network Management Speeds Research at Baylor College of Medicine
2/7/2008
Dell hardware. About a third of those servers are attached to a storage area network (SAN) running controllers from IBM and EMC. Switches are from QLogic. King also manages about 100 desktop computers, loaded with either Windows XP or RedHat Enterprise Linux 4 Desktop. He's also seen a recent influx of Macs.Anything of a sensitive nature, according to King, has two-factor biometric access. The user enters an access ID then has his or her hand analyzed for further authentication.
The fMRI machines themselves aren't connected directly to the network. Made by Siemens, the machines link to the network through gateway PCs connected to each scanner and running a specialized version of Windows XP.
Time-consuming Research
When a scientist performs an experiment, a vast amount of raw data is generated in the form of medical images. In order to be able to make sense of the data, the researcher needs to massage the images.
That preprocessing step, said King, involves doing a "normalization" of the images. "It pushes and pulls the images so that they overlay on top of a 'perfect' brain. This way, we can compare results across people. If you've got 15 people in a study, everybody's brain is a little different, so you have to normalize the brain to a 'perfect' standard."
Previously, the normalization work was done on a desktop PC, one study subject at a time, in a sequence. The scans for those 15 study subjects would require a total of about 15 hours of preprocessing time before the analysis could begin.
A couple of years ago, the lab figured out that a bit of automation could speed up that part of the work. It purchased a 32-node, 64-processor cluster from IBM to run Statistical Parametric Mapping (SPM), open source software especially well suited to this type of analysis. "Now, you just go into our Web interface, pick people you want, submit it, and off you go," said King. "An hour later, [the information] is preprocessed, and you're ready to start analyzing. The computationally heavy part is off-loaded."
Another challenge: managing storage. A single research project could require terabytes of storage space. What King didn't want was a researcher being midway through a project and discovering that he or she had run out of storage space.
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