% -*- Mode:TeX -*-

\chapter{Products and transferable technology}

The proposed work will provide the scientific community with the
capability to efficiently handle an important class of models and
algorithms which until now were not in practice computationally
accessible.  \Cam-8 will add several orders of magnitude in performance
to what is possible today: we expect that the existence of this machine
will be an important stimulus to the entire field of cellular automata
research, and will provide an incentive for scientists working in a
broad range of disciplines to investigate a new class of computational
models.  Some of these models are of immediate relevance to a number of
technological applications: materials science, aerodynamics, plasma
dynamics, radar and sonar path analysis, and analysis of satellite
pictures.

This work will accelerate the development of concepts, methods, and
techniques relevant to large-scale, high-performance parallel
computation; it will provide a testbed for programming and modeling
methods suitable for large, locally-connected systems, and for the
evaluation of alternative architectures useful in this context.
Finally, it will stimulate the exchange of problems and resources
between computer science and physics.

\medskip

In a limited but quite concrete way, the \cam-6 project has shown how
quickly methodology and technology can be transferred to the scientific
user community when the issues addressed respond to widely-felt needs.
We expect that the \cam-8 project will result in consequences of a
similar nature but of much wider scope.


\section{A scalable architecture for massive simulations}

Perhaps the most important features of the \cam-8 architecture are its
scalability and its economy.  The scalability is inherited from the
scalability of the underlying cellular automaton architecture, while the
economy derives from its use of conventional memory chips running at
full I/O bandwidth on a 100\%\ duty cycle for both its processing and
its storage elements---this helps make massive simulations affordable.

In addition to being upwardly scalable, the architecture is also scalable
down to a small number of modules (in fact, we plan to develop the
smaller machines first).  Such ``small'' machines will be cheap enough
to be widely disseminated, but will be able to run exactly the same
models as much bigger ones.  They will have the advantage of
allowing highly interactive experimentation (which would be more
wasteful on bigger machines) while retaining complete software
compatibility with large machines: experiments developed using small
machines will run without change on big ones.  Such compatibility
significantly enhances the usefulness of machines of all sizes.

Another aspect of the scalability of this architecture is the fact that
relatively simple rules that employ a relatively small neighborhood can
be cast directly into silicon (see Section~\ref{ps-parallel}), using a
highly parallel version of the \cam-8 architecture (with logic replacing
lookup tables).  The additional orders of magnitude in performance that
this makes available make cellular automata models
more attractive, and hence make the need for useful simulation tools
such as \cam-8 more imperative.

\section{A new environment for modeling}

In addition to powerful hardware, an architecture such as \cam-8 that is
based on cellular automata inherits some novel software aspects that
distinguish it from ``conventional'' supercomputers.  In particular,
there is little difficulty in writing correct programs: a typical
cellular automaton rule consists of just a few lines of
code---describing what a single cell should do\cite{margolus-super}.
Complex initial conditions are easily treated: one just ``draws''
complicated obstacles or materials at exactly the places one wants them
(see Section~\ref{related-models}).  The most difficult aspect of
experiment development will involve verifying that rules suggested by
various techniques (such as microphysical analogy or elaboration of
existing models) actually produce the desired macroscopic behavior over
the desired range of initial conditions.

Since the analytical treatment of nonlinear models is in general
difficult, extensive simulation and measurement are mandatory.  In this
context, the \cam-8 architecture's unique capabilities for real-time
display and analysis will play an irreplaceable role, bringing for the
first time truly {\em interactive} development into the discipline of
massive modeling: models may be modified and re-run in the space of a
few seconds rather than days.

\medskip

The data-analysis component of such experiments will be quite separate
from the description of the rule itself.  In a search for a rule with
given macroscopic properties, data analysis might consist of having the
host compare appropriate functions of the state of the system with the
desired macroscopic behavior.  For sufficiently complicated functions of
the system state, the data-analysis component will require significant
sophistication (routines to handle common cases will be provided as part
of the software environment).

Given a rule with desired macroscopic properties, one may wish to use it
in a simulation loop in which it is the initial conditions that are
varied.  An example of such an experiment would be a wind-tunnel
simulation in which the position or shape of the obstacles are varied
while various drag parameters are measured.  Again, given \cam-8's fast
turnaround, it becomes practical to conduct a directed search for
initial conditions satisfying certain criteria (e.g., lowest drag).

\medskip

In conclusion, the extensive simulation capabilities of \cam-8, in
conjunction with the integrated modeling environment that will accompany
them, will be invaluable both for arriving at useful models and for
making concrete use of them.


