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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.
High-Performance Computing
EPA's National Computer Center in Research Triangle Park, North Caro-
lina, 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 toxicol-
ogy, exposure research, and risk assessment. Those resources are traditional
high-performance computing machines, the products of a shrinking and strug-
gling 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.
Parallel Programming
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 inde-
pendent 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 mas-
sive 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computing as Moore's law is repealed.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
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 commer-
cially), 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 per-
formance 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
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