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