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Computerworld - When Novartis AG needed extra processing power, the pharmaceutical giant found it—5 trillion floating-point operations per second of unused capacity, to be precise—in 2,700 desktop PCs at its headquarters in Basel, Switzerland. The company lashed the PCs together in a compute grid that it now uses to run number-crunching supercomputer applications that model the interactions between proteins and other chemicals that might be used in drugs.

"The grid has opened up a number of opportunities for us which were just not there before," says Manuel Peitsch, head of informatics and knowledge management at subsidiary Novartis Research. "People couldn't imagine doing the things that we are doing today on a routine basis."

The Novartis drug research software is loaded onto the desktops by way of a server running Grid MetaProcessor software from United Devices Inc. in Austin. By investing $400,000 in grid technology, Novartis avoided spending $2 million on a new Linux cluster.

Credit: Philip Anderson

The Novartis success story is far from unique. Drug companies, university computation centers, product development and engineering departments, federally funded research consortia and a few financial services firms have set up computer grids. They report big savings in hardware costs and sometimes productivity improvements as well.

Grids consist of geographically dispersed computers linked dynamically in order to present to users a unified view of computational resources such as compute cycles, disk space, software or data. There are intracompany grids, such as the one at Novartis, and partnership grids, such as the National Science Foundation-sponsored TeraGrid.

Utility grids, which proponents say could provide unlimited on-demand access to computer resources in much the same way the U.S. electric power grid provides on-demand access to electricity, are a dream of companies such as IBM and Hewlett-Packard Co. However, they don't yet exist.

Grid Limits

Today, most grid applications share three characteristics. First, they are computationally intensive. Second, most are written for parallel or massively parallel execution. Third, like the Novartis grid, most are built to harvest unused compute cycles. Some, however, focus on getting at distributed data or disk resources.

Although IT vendors tout grids for all kinds of applications, grids have barely begun to move beyond scientific, engineering and mathematical/statistical applications. One reason is that most business applications weren't written with parallel processing in mind, so they're less able to take advantage of the many semi-independent processors that form grids.

"Parallelizing these applications is a major rewrite," says Carl Greiner, an analyst at Meta Group Inc. in Stamford, Conn. "That's why grids are having a difficult time in the commercial space." It will be five years before applications such as supply chain systems become suitable for grid computing, he predicts.