When biotech company Applied Biosystems "bought" 36,000 hours of computing time on 1,000 machines, it figured it could quickly translate data from a genetic project. But how much more quicker than doing it inhouse?As the senior director of computational genetics at Applied Biosystems, Francisco De La Vega was familiar with the advantages of using clusters of inexpensive computers working together to solve tough scientific computing problems.
But there is still a limit to how many hundreds of computers he can afford to keep on hand. At the time that a monster computing challenge came along in October, the biotech company had actually downsized its in-house computer farm and was looking for an alternative way of handling peak demands for computer power.
That was when the National Institutes of Health (NIH) announced the completion of the first phase of an international project to validate millions of genetic sequence variations.
Applied Biosystems is in the business of providing researchers and biotech companies with genetic assays, which test for the presence of a given sequence.
To stay abreast of the market, Applied Biosystems needed to rapidly translate the NIH data into updates to its product line. Time to market would largely be determined by how quickly it could run through the genetic data through its proprietary analytic programs.
That's when De La Vega turned to the Sun Grid, the Sun Microsystems service that offers access to computer power on the basis of $1 per CPU hour (that is, the amount of computing that one processor can deliver per hour). Applied Biosystems rented time on 1,000 computers, which were able to complete in a week a job that he had estimated would take three months for him to run on his existing servers.
"It basically saved us a couple of months worth of computing time," De La Vega says. "The alternative would have been for us to expand our internal compute farm, and pay the electricity and cooling costs on that, even knowing that it would be idle probably 50% of the time."
This is exactly the concept behind utility computing, the idea that you ought to be able to buy access to computational power as you need it, with capacity that flexibly grows and shrinks in pace with your needs. Grid computing turns out to be a complimentary concept, since grids of computers that can be dynamically assigned to different tasks are one way of delivering utility functionality.
And although Sun actually packages some other rent-a-data center offerings under the Sun Grid banner, Applied Biosystems was tapping into the more grid-like part of it, where Sun supplies access to lots of relatively inexpensive servers working in tandem. Those servers run Solaris 10 but in combination with AMD Opteron processors, rather than Sun's proprietary CPUs.
Read the full story on eWEEK.com: Grid Computing: Buying Computing Power, by the Hour
