Other issues arise around licensing and pricing. Vendors who move their products to grid must figure out ways to price their software. Per-CPU or per-seat pricing often makes sense in a world where those numbers stay relatively static, but with grid, an application could run on 500 processors one minute and none the next. Being charged for every one of those processors could drive much of the cost benefit out of grid for customers, but adopting a "buy it once, use it everywhere" model could push vendors out of the grid business. Ultimately, per-use price models?likely based on specifications supplied in the OGSA?could dominate, but the tools for tracking such usage have yet to be fully developed. "We believe that companies are going to have to change their business models and their attitudes for how they license their products in a grid world," says Platform’s Baird. "These apps are going to have to float around in the ether and not be fixed to a particular CPU or a particular seat. Dynamic is the key element here."

Grid can even introduce dilemmas for the bean counters. For instance, a CIO at one computer hardware maker says he would love to grid-enable thousands of machines as they go through the burn-in process at the company’s manufacturing plants. The machines run various software for extended periods so that the quality assurance people can make sure no components are about to fail before the machine goes out the door. Why not, asks the CIO, run the company’s grid-enabled software during the burn-in? "It would be like finding a new source of oil," he says. But the company’s accountants can’t decide how to describe a product that’s been used, no matter how briefly, for work inside the manufacturer. Is it still new? Has it become a depreciable asset? So far, that gusher remains untapped.

Is Grid Right for You?

Right now, many applications simply don’t lend themselves to grid computing?especially those that depend more on data handling than CPU power, such as most accounting, CRM and ERP apps. Such applications often take a large chunk of data and run many functions on it, with each task depending upon the previous one. These applications will generally work better on a single processor machine.

The best candidates for grid are applications that run the same or similar computations on thousands or millions of pieces of data, with no single calculation dependent on those that came before. These so-called embarrassingly parallel applications?which include numerous scientific tools, cryptography, and the actuarial and derivative examples mentioned earlier?are ideal for grid, as they scale almost perfectly with the applications able to take advantage of every new processor you throw at them.