We describe computational science as an interdisciplinary approach to doing science on computers. Our purpose is to introduce computational science as a legitimate interest of computer scientists. We present a foundation for computational science based on the need to incorporate computation at the scientific level; i.e., computational aspects must be considered when a model is formulated. We next present some obstacles to computer scientists' participation in computational science, including a cultural bias in computer science that inhibits participation. Finally, we look at some areas of conventional computer science and indicate areas of mutual interest between computational science and computer science. Keywords: education, computational science. 1 What is Computational Science ? In December, 1991, the U. S. Congress passed the High Performance Computing and Communications Act, commonly known as the HPCC . This act focuses on several aspects of computing technology, but two have...

In this paper we review the current state of the problem solving environment (PSE) field and make projections for the future. First we describe the computing context, the definition of a PSE and the goals of a PSE. The state-of-the-art is summarized along with sources (books, bibliographics, web sites) of more detailed information. The principal components and paradigms for building PSEs are presented. The discussion of the future is given in three parts: future trends, scenarios for 2010/2025, and research

: : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : xvi 1. INTRODUCTION : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 1 1.1 Modeling with Partial Differential Equations : : : : : : : : : : : : : : 1 1.2 Evolution of PDE Solving Software : : : : : : : : : : : : : : : : : : : 3 1.3 Problem Solving Environments : : : : : : : : : : : : : : : : : : : : : 8 1.3.1 Properties of PSEs : : : : : : : : : : : : : : : : : : : : : : : : 8 1.3.2 PSEs vs. PSE Frameworks : : : : : : : : : : : : : : : : : : : : 9 1.4 PDE Based Applications and Application PSEs : : : : : : : : : : : : 10 1.4.1 The PDELab Prototype : : : : : : : : : : : : : : : : : : : : : 11 1.5 Overview of the Thesis : : : : : : : : : : : : : : : : : : : : : : : : : : 12 2. THE ARCHITECTURE OF A SOFTWARE FRAMEWORK FOR BUILDING PROBLEM SOLVING ENVIRONMENTS FOR PDE BASED APPLICATIONS : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 13 2.1 Introduction : : : : : : : : : : : : : : ...

We summarize our work consisting of the development of FALCON, a programming environment based on MATLAB. This environment includes capabilities for the rapid prototyping of algorithms, and for the interactive and automatic transformations at both the operation-level and the functionor algorithmic-level in order to obtain good numerical and computational performance. FALCON supports the development and reuse of numerical programs and libraries, and combines the transformation and analysis techniques used in restructuring compilers with the algebraic techniques used by developers to express and manipulate their algorithms in an intuitively useful manner.

In this paper, we present the Ctadel system, a Code-generation Tool for Applications based on Differential Equations using a very high level Language specification. The Ctadel system generates efficient and vectorizable Fortran 77 code automatically from a very high level language description of a model described by partial differential equations (PDEs). The system combines algebraic simplification and powerful global common subexpression elimination to guarantee the generation of efficient code. A prototype implementation has been developed which is currently limited to explicit finite difference methods as solution method. After an informal, but detailed description of the Ctadel system, results of this prototype implementation will be presented for the time-dependent Euler equations to simulate an inviscid, compressible flow and for the calculation of the explicit dynamical tendencies within the hirlam model, which is a production code for limited area numerical weather forecasting....

The Ctadel system provides an automated means of generating specific high performance scientific codes optimized for serial, vector, or shared virtual memory and distributed memory parallel computer architectures. One of the key elements of this system is the employment of algebraic simplification techniques and powerful methods for global common subexpression elimination to guarantee the generation of efficient high performance codes for various target architectures. In this paper we present the Ctadel Code-generation Tool for Applications based on Differential Equations using high-level Language specifications. A prototype implementation has been developed which is limited to explicit finite difference methods as numerical solution method. Performance results of the codes generated with this prototype implementation will be presented for a limited area numerical weather forecast routine on various hardware platforms. These results show that generation of efficient code is well feasib...

We advocate the use of Common Lisp as a powerful glue for building scientific computing environments. Naturally one then has to address mixing pre-existing (non Lisp) code into this system. We provide a specific example as an elaborate FORTRAN system written by David Bailey for arbitraryprecision floating-point numeric calculation. We discuss the advantages and disadvantages of wholesale importing into Lisp. A major advantage is being able to use state-of-the art packaged software sooner, while overcoming the disadvantages caused by FORTRAN's traditional batch orientation and weak storage model. In this paper we emphasize in particular how e#ective use of imported systems may require one to address the contrast between the functional (Lisplike) versus state-transition-based (Fortran-like) approaches to dealing with compound objects. While our example is high-precision floats, other highly useful packages including those for simulation, PDE solutions, signal processing, statistical comp...

In complex domains such as scientific computing, users need support in choosing, chaining, and executing the adequate programs for problem solving. Problem solving environments are developed in order to solve automatically routine problems, decomposing them recursively in more and more elementary subproblems, and finally executing the corresponding programs. But often, the problem solving process cannot be completely automated ; the user is requested to provide missing parameter values, to solve specific subtasks, or to validate input or output data. Besides, the user must have the possibility to supervise the whole problem solving process and all the decisions made by the computer system. He must be able to intervene whenever he wants, either to modify the systems decisions, or his own choices, concerning parameter values for example. SCARP is a shell that allows to develop problem solving environments providing the necessary cooperation facilities for interactive problem solving. Its...

Techniques are introduced that utilize structural information to improve the code generation while rapid prototyping numerical algorithms with FALCON. These techniques are then extended to also modify the data representation allowing even further improvements in the code. Finally, results are presented that illustrate the performance improvements possible from the techniques. INTRODUCTION Scientific applications rely upon numerical algorithms to effectively utilize high-performance computers; however, the steps necessary to provide an application developer with efficient algorithms can be very complex, therefore problem solving environments (PSEs) that help the user in this endeavor are desirable. A typical scenario has the user who needs to accomplish some problem-solving task (e.g. consisting of input, simulation, and output steps) and in response designs a solution method and implements it on the target computational platform(s). In many instances the above process is repeated unt...

this document, we describe the initial design of a generic MPSE framework based on a network of computational agents assuming a net-centric run-time support environment. Moreover, we present the realization of this framework for designing a prototype MPSE (GasTurbnLab) for supporting simulations needed for the design of efficient gas turbine engines