  In this chapter we will argue that studying such multi-scale multi-science
systems gives rise to inherently hybrid models containing many different
algorithms best serviced by different types of computing environments (ranging
from massively parallel computers, via large-scale special purpose machines to
clusters of PC's) whose total integrated computing capacity can easily reach
the PFlop/s scale. Such hybrid models, in combination with the by now
inherently distributed nature of the data on which the models `feed' suggest a
distributed computing model, where parts of the multi-scale multi-science model
are executed on the most suitable computing environment, and/or where the
computations are carried out close to the required data (i.e. bring the
computations to the data instead of the other way around). We presents an
estimate for the compute requirements to simulate the Galaxy as a typical
example of a multi-scale multi-physics application, requiring distributed
Petaflop/s computational power.
