The Purdue PSE Kernel: Towards a kernel for building PSEs

Abstract Problem Solvillg Environments (PSEs

Software reuse methodologies for parallel and netcentric scientific computing

The process of prototyping is part of every scientific inquiry, product design, and learning activity. New economic realities require the rapid prototyping of physical 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. Thus, the realization of rapid multidisciplinary prototyping is a new grand challenge. For the realization of this scenario the natural computational resource is a “computational grid” that connects the needed distributed high performance hardware and software resources used to simulate the elements of the artifact. Our research goal is to address this scenario in the context of parallel computing and Intranet/Internet based computational grids. To achieve this goal, in this dissertation we first address the “reuse” of legacy sequential scientific software to build parallel scientific applications. Second, we present a Web/Internet based server that “reuses” scientific problem solving environment (PSE) components to virtually place their capabilities at the fingertips of any scientist and engineer. Third, we describe the design and architecture of a generic multidisciplinary PSE (MPSE) framework that enables the “reuse” of legacy scientific code via encapsulation within a network of computational agents. We present the initial realization of this framework in the design of a prototype MPSE (GasTurbnLab), for supporting simulations needed for the design of efficient gas turbine engines

Web//ELLPACK: A Networked Computing Service on the World Wide Web

This paper describes the //ELLPACK networked computing service that we have made available through the World Wide Web. //ELLPACK is a problem solving environmen

PDELab: An Object-Oriented Framework for Building Problem Solving Environments for PDE Based Applications

In this paper we present an object-oriented methodology and tools for creating high level, high performance problem solving systems (workbenches) for scientific applications modeled by partial differential equations. This methodology is validated by the creation of a scientific computing workbench for bioseparation analysis. One of the design objectives of PDELab is to provide workbench developers and users with much the same kind of independence in software as they have come to expect in hardware. The adopted architecture of this software platform for creating problem solving environments for PDE applications is devoted to "clean layering." At the bottom are the various "smart" libraries that support the numerical simulation of various "physical" objects together with the corresponding knowledge bases needed to support the computational intelligence aspects of the various workbenches; at the top is a set of interactive tools that allow the user to carry out his objectives ..

On the Software Engineering of Multi-Platform Parallel/Distributed Software

This paper describes our experience in developing and maintaining multi-platform parallel / distributed scientific computing software. We gained this experience while developing the parallel computation environment for //ELLPAC

Network Servers for Multidisciplinary Problem Solving

The evolution of the Internet into the Global Information Infrastructure (GII) is impacting many institutions of life in general, and, the way we view computing in particular. This future computational and communication infrastructure will allow computing everywhere. Learning and training simulators will be part of any classroom and laboratory. The very concept of classroom, laboratory and individual workplace will change; they will become virtual places based on an array of multimedia devices [1]. We are developing the software architecture of such an environment and are working on related research issues. The advent of such environments will affect the process of prototyping, which is part of every scientific inquiry, product design, and learning activity. The new economic realities require the rapid prototyping of manufactured artifacts and rapid solutions to problems with numerous interrelated elements [2]. This, in turn, requires the fast, accurate simulation of physical processes..