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\chapter{Introduction}\label{sect.intro}

We propose to develop and make accessible to a wide scientific public
a modeling methodology---called {\em programmable matter}---made
possible by a novel kind of computing environment that is ideally
suited to the modeling needs of materials science.

Programmable matter is meant to complement, rather than displace, more
traditional modeling approaches. It demands a spatially-extended
computational medium that is quite unlike the structure of
conventional computers: statistical mechanical systems extensively
used by physicists as conceptual models can be brought to life as
simulation models and practically investigated. This approach seeks to
reproduce macroscopic phenomenology starting directly from a digital
pseudo-microdynamics.


\section{Programmable matter}

In response to a variety of scientific demands, we have developed a
very fine-grained, parallel, uniform, scalable multiprocessor
architecture---known as \cam-8---offering unprecedented performance in
the fine-grained modeling of spatially-extended systems. This
architecture is described in \cite{cams,pm}; its essential
features are summarized in \app{cam8}.

The advent of \cam-8 is the culmination of several years of issues
analysis, conceptual design, and hands-on experience with more modest
cellular automata machines. This development work has been supported
mostly by \darpa. We have had working prototypes since June 1992, and
we are now in the process of making \cam-8 units available to a first
group of interested investigators.


\medskip

\Cam-8 is the embodiment of a computational scheme, called {\em
conveyor-collision processes}, which is oriented towards fine-grained,
massively parallel processing.  This scheme has its roots in the
tradition of cellular automata, but incorporates significant
innovations that on one hand promote a closer correspondence between a
computation and the physical processes it represents, while on the
other lead to a very flexible and efficient utilization of hardware
resources.

Certain important aspects of physics, such as uniformity and locality
in three-dimensional space, are incorporated in the design of \cam-8;
other aspects, such as microscopic reversibility and inertia, are
directly supported. These architectural features make \cam-8
conceptually very well-suited to the implementation of fine-grained
simulation models of physical materials and systems.  Just as
important, again because of its close match with physics, the \cam-8
computer architecture lends itself to a very efficient physical
implementation, so that these models of materials and systems can be
run orders of magnitude faster than with conventional scientific
computers.

\medskip

In brief, \cam-8 provides a general-purpose instrument for the
systematic exploration of a region of the computational spectrum that
is barely accessible with conventional computers. {\em Such an
instrument, the region it is aimed at, and the approach we plan to use
in this exploration, together define the concept of `programmable
matter'}.


\section{Project origins and goals}

The {\em Information Mechanics} group of the MIT Laboratory for
Computer Science has been active for over a decade in areas where
computer science and physics are intimately connected. Some of our
pioneering contributions have been
 \begin{itemize}
	\item The use of cellular automata for physical modeling.
	\item The development of computational schemes that faithfully
reflect certain essential aspects of physics, such as
microscopic reversibility.
	\item The development and dissemination of cellular automata
machines, and their use in modeling a variety of physical phenomena
from low-level digital primitives. In particular, we contributed to
the development of lattice-gas models for hydrodynamics. Our book {\em
Cellular Automata Machines---A new environment for modeling}, which is
now in its fifth printing and has just appeared in a Russian
translation, still represents the standard introduction to
fine-grained modeling techniques using cellular automata.
	\item Finally, the identification of the concept of
`conveyor-collision processes'---a computational scheme related to
cellular automata but featuring, for physical modeling purposes,
significant conceptual and practical advantages; and the development
of a new fine-grain parallel architecture (namely, \cam-8) to
efficiently implement this concept.
 \end{itemize}

\medskip

The principal objective of the proposed work is to stimulate and
provide support for the use of programmable matter as a modeling tool
in materials science.

We plan to do so by developing an integrated body of concepts,
techniques, and representative examples---in brief, a modeling {\em
methodology}. This methodology will be made immediately accessible by
the software we shall concomitantly develop for the \cam-8
architecture. A good deal of the material needed for this task is
already available in some preliminary form; this material will have
to be augmented, consolidated, and presented in a form suited to the
intended audience and use. By means of this methodology and software, the
\cam-8 hardware will literally be turned into a ``programmable matter
laboratory.''

While we do not set out to explore new physical theories, in order to
realistically exercise and illustrate the capabilities of programmable
matter we will certainly turn our attention to physical questions of
current interest and develop new physical models.  However, the chief
emphasis will be not on resolving specific physical problems, but on
exploring how programmable matter can be applied to a wide range of
materials science problems.

\medskip

The challenge of real modeling problems, and feedback on our
progress in addressing them, will be provided by collaborations with
specialists of representative areas.

For example, we have been collaborating for a while with Yaneer
Bar-Yam (Boston University) in the modeling of polymer dynamics.  We
shall continue our long-term collaboration with Charles Bennett (IBM
Research) on a number of theoretical materials science issues.  Gary
Doolen and Brosl Hasslacher (Los Alamos National Lab.) have been
strong supporters of the \cam-8 project, owing to their involvement in
lattice-gas hydrodynamics; we are looking forward to exploring with
them its potential in this field.  Under the auspices of Jane
Alexander (DARPA) and Larry Cooper (ONR) we will contribute cellular
automata modeling expertise to a project aimed at domesticating
quantum effects for fine-grained parallel computation; among likely
collaborators are Gary Frazier (TI), Pradip Bakshi (Boston College) and
Dimitri Antoniadis (MIT). We also plan to collaborate with Daniel Rothman
(MIT) on multiphase flow modeling, with Jeff Yepez (Air Force Philips
Research Lab.) on issues of micrometeorology, and with Nihat Berker and
Roland Netz (MIT) on Monte-Carlo techniques in renormalization group
calculations.



\section{Significance to DOE}

The proposed work falls within the domain of two major components of
the High-Performance Computing and Communications Program: {\em
High Performance Computing Systems} (HPCS) and {\em Advanced Software
Technology and Algorithms} (ASTA).

Indeed, what we propose is ``research and development associated with
evaluating the effectiveness of a new parallel computing system,''
namely \cam-8, developed with \darpa{} support and evolved from
earlier conceptual research supported in part by {\sc nsf}. This work
will entail developing a modeling methodology and a software
environment capable of bringing out the best of the new hardware.

\medskip

Of most specific relevance to DOE is programmable matter's promise for
materials science. 

In terms of more general objectives, we are convinced we have
identified a very natural and effective approach to harnessing massive
parallelism for concrete scientific problems.


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