HP's David Valenta, global market development manager for life sciences, concurs that life sciences customers' perceptions, especially among pharmaceutical companies, is that "security is not good enough." Many of them still use courier services to transport floppy disks rather than trust data transfer over the Internet. While protection of intellectual property is one concern, Valenta says that "What really keeps them up at night is that they hold a lot of genetic information about people." Indeed, in the U.S. at least controversies over exposing someone's credit card information pale next to the issues raised by exposing someone's genetic data and potential predisposition to diseases and other medical conditions.
On the systems side, the Blue Gene project launched by IBM in late 1999 to build a supercomputer aimed at computationally intensive operations such as modeling the folding of human proteins, produced technology developments in load-balancing, self-healing, and fault-tolerance that made their appearance in the eServer p690, Nunes said. That Unix machine shipped last December to customers such as retailer Gap Inc., which is using it for global supply chain management, according to IBM.
HP's Valenta sees Linux getting a shot in the arm from the life sciences market: Because Linux-based systems are perceived to be relatively inexpensive, they have been well-received in academia, where many life sciences applications are developed. The consequence is that now the big pharmaceutical companies want commercialized, turnkey Linux systems to run these applications -- and companies such as HP will likely do their best to deliver.
The development of software and hardware to manage very large-scale clusters or compute farms is becoming very important for Compaq, according to Rabe. Many of the company's life sciences customers are using dozens to hundreds of four-processor Alpha systems connected together. "The difficulties are: How do you manage the environment? And how do you get useful work from compute farms?" Rabe said.
Users in the life sciences community are thus among the most vocal in discussions of emerging standards in grid computing, Rabe said. Grid computing aims to create a computational resource analogous to the electricity grid, so that systems can be tapped, shared, and aggregated regardless of geographical location. Issues with which users are grappling include keeping track of computing resources that are available, and applying policies for the availability of those resources. Other areas of concern for grid computing are security -- how users are identified as being authentic when accessing the grid -- and standard procedures for accessing data.
