tems perspective of data instead of a focus on one locale, one experiment, or one medium at a time. Those are the directions that IT and informatics are taking. The challenge will lie in understanding how to harness information for EPA’s science needs for the future and understanding the role of advanced computer science and informatics in EPA.
EPA’s National Computer Center in Research Triangle Park, North Carolina, houses many of the agency’s computing resources, including the super-computing resources used by the Environmental Modeling and Visualization Laboratory and resources for such major applications as computational toxicology, exposure research, and risk assessment. Those resources are traditional high-performance computing machines, the products of a shrinking and struggling industry segment. The future of high-performance computing machines will look entirely different, and it is important that EPA adjust to the change to remain at the leading edge of the field.
Central processing units (CPUs) can no longer be made to run faster, so progress requires putting multiple CPUs, or “cores”, on each chip to operate concurrently. That, in turn, requires a decomposition of applications into independent components that can run in parallel. An important opportunity afforded by the effort to create highly parallel programs is that they can also be exported to external networks of underused processing for the few jobs that require massive resources. The existing tools for that style of programming are poor, and the skill is seldom taught. Fortunately, EPA has had experience in this regard in its supercomputing projects, but it will need to expand its overall skills inventory greatly to continue to take advantage of parallel and emerging techniques in computing as Moore’s law is repealed.
Cloud computing will redefine the economics of computation for the next 20 years. A cloud-computing server typically provides services to its clients in three ways: complete applications (software as a service, or SaaS); a platform for clients to build on (PaaS); or a raw infrastructure of processors, storage, and networks (IaaS). Clouds generally are classified as public (provided commercially), private (to one or more organizations), or hybrid (public with a secure connection to private). Services can be scaled up or down in capacity and performance instantly; the client is charged for the amount of time, storage, CPUs, and bandwidth, moment by moment. Even organizations with extreme needs for computation, storage, and bandwidth and high volatility of demand over the