GPFS addresses this issue by breaking up the files into chunks that range in size between 256 and 1,024 kilobytes, depending on system resources, and storing these chunks across all of the disks in the file system. To access a file, GPFS initiates multiple pathways in parallel. This parallel file system differs from a so-called "distributed" file system, in which data is transferred through a single path. Moreover, because the system disperses the data traffic, it is effectively self-healing: if one pathway fails, data immediately flows to another one.

Because IBM manages each component of the supercomputer at LLNL, it has been able to finely tune the hardware -- processors, networking devices, and storage controllers -- to work optimally with GPFS, and thus achieve the record 102 gigabytes per second. "Few companies have ownership of all the components," Govindaraju says, "so IBM is uniquely positioned to explore the breadth and depth [of the technology]."

But even companies that don't have IBM systems in their data centers can speed up their supercomputers by using GPFS. Govindaraju says that because the technology is open source, customers without IBM components can incorporate it into their systems and modify it appropriately.

In one example of such an application, IBM is working with the University of Pennsylvania on a project called the National Digital Mammography Archive, an effort to store digitized images of mammograms and make them easily accessible to doctors around the world. Govindaraju gives this example of how it works: a woman has a mammogram in Pennsylvania, then moves to California, where she has another scan. Her doctor in California wants to compare the test results, which he can do by accessing the mammography database. The physician notices a change between the results of the mammograms and is able to compare that change to changes in thousands of other mammograms throughout the world via the database. Also, the doctor can quickly search for the course of treatment that was most effective in similar cases and prescribe that treatment to his or her patient.

Further, Govindaraju adds, all personal identifying information can be stripped off, so that privacy is maintained. The database could also be used to train medical students to make more informed treatment decisions. "What started off as a simple file-sharing experiment is spawning much more powerful applications, to make the medical system more efficient," he says.