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Computing Clusters: Sometimes You Can't Make It On Your Own

11/18/2005

By Dian Schaffhauser

'We support research, discovery, and scholarship that requires high-end computational resources. That's obviously a moving target.' In fact, he says, every six months or so, the center redefines what it means by 'high-end' in terms of data, networking, visualization, or computing requirements. If a project requires fewer than, say, 16 processors running concurrently, Miller and his team will probably kick the request back to the individual to take back to his or her lab, department, or school for handling. An advisory committee evaluates troublesome proposals, but most of the time, the decisions are 'obvious.'

At NCSA, the process for gaining access is more formal. The proposal process is modeled after the NSF process, says Towns, which involves-for large requests-a peer review performed by a national review committee that meets quarterly. These are proposals requiring in excess of 200,000 CPU hours per year. Smaller requests-from 10,000 to 20,000 hours of time-are considered 'development accounts,' for start-up projects. Reviewed and rewarded continuously, the smaller accounts allow researchers to try out their applications on the system and understand performance characteristics in preparation for submitting larger proposals.

What's a CPU hour in cluster terms? According to Towns, it's equivalent to one hour of time on a single processor node. Since these are dual processor nodes, there's a total of 2,480 processors on Tungsten. If a project is running on 64 nodes, which is 128 processors, and it runs for one hour, the user has accumulated 128 service units or CPU hours.

Neither organization charges its academic users for the time they use on the clusters. In the case of NCSA, Towns says, they're granted allocations of time as part of grant awards, and those allocations are billed from their usage.

CCR considers its clusters part of the 'university infrastructure,' says Miller, 'to support leading-edge science research.'

Both centers also attract funds from academic users in situations where they've budgeted compute time in their grant proposals to cover expanded demands on staff time; compensation also comes from commercial users that make use of the resources.

The NCSA has about 100 staff members and another '15 or 20' graduate students working in its center to provide 24/7 support for its community of users. CCR has a technical team of 13, consisting of operations people and computational scientists. The former, system administrators, keep the systems running, and the latter work closely with users to figure out, for example, what applications are needed for a particular project or to help optimize code.

Miller estimates that about half of the applications running on the CCR computers are off-the-shelf-code that has been paid for or is freeware or shareware. The other half is 'home-grown.' In the case of NCSA, Towns says, 'By and large [the majority of our users are faculty researchers] using applications they've developed to solve the problems that they're attacking.'

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