SciAgents is an an agent-based approach to building
Multidisciplinary Problem Solving Environments
which is naturally parallel
and highly scalable; and is especially suited for a distributed high
performance computing environments. The new economic realities require the
rapid prototyping of manufactured artifacts and rapid solutions to problems
with numerous interrelated elements. This, in turn, requires the fast,
accurate simulation of physical processes and design optimization using
knowledge and computational models from multiple disciplines in science and
engineering. High Performance Computing & Communication (HPCC) Systems
facilitate this scenario. Many hitherto dormant and difficult challenges in
applied sciences and engineering, such as modeling protein folding or internal combustion
engine design or intelligent transportation systems (ITS), have become feasible to attack using the power of HPCC. The
evolution of the Internet into the Global Information Infrastructure (GII),
and the concomitant growth of computational power and network bandwidth
suggests that computational modeling and experimentation will continue to grow
in importance as a tool for big and small science. Networked Scientific
Computing (NSC), which will allow us to use the high performance communication
infrastructure (vBNS, Internet II etc.) to view heterogeneous networked
hardware(HPC) and software resources as a single ``meta computer'', seems to
be the next step in the evolution of the HPCC. NSC enables scientists to
begin to address the class of complex problems that are envisaged in the
Accelerated Strategic Computing Initiative (ASCI) from DOE. In this type of
problems, the design process will operate at the scale of the whole physical
system with a large number of components that have different shapes, obey
different physical laws and manufacturing constraints, and interact with each
other through geometric and physical interfaces.
The SciAgents system is
guided by this vision, and uses software components and agent based
collaborative techniques. It allows wholesale reuse of legacy software and
provide a natural approach to parallel and distributed problem solving.
Anupam Joshi |