Advances in networking technologies will soon make it possible to use the global information infrastructure in a qualitatively different way—as a computational as well as an information resource. As described in the recent book The Grid: Blueprint for a New Computing Infrastructure, this Grid will connect the nation’s computers, databases, instruments, and people in a seamless web of computing and distributed intelligence, which can be used in an on-demand fashion as a problem-solving resource in many fields of human endeavor—and, in particular, science and engineering. The availability of grid resources will give rise to dramatically new classes of applications, in which computing resources are no longer localized but, rather, distributed, heterogeneous, and dynamic; computation is increasingly sophisticated and multidisciplinary; and computation is integrated into our daily lives and, hence, subject to stricter time constraints than at present. The impact of these new applications will be pervasive, ranging from new systems for scientific inquiry, through computing support for crisis management, to the use of ambient computing to enhance personal mobile computing environments. To realize this vision, significant scientific and technical obstacles must be overcome. Principal among these is usability. The goal of the Grid Application Development Software (GrADS) project is to simplify distributed heterogeneous computing in the same way that the World Wide Web simplified information sharing over the Internet. To that end, the project is exploring the scientific and technical problems that must be solved to make it easier for ordinary scientific users to develop, execute, and tune applications on the Grid. In this paper, the authors describe the vision and strategies underlying the GrADS project, including the base software architecture for grid execution and performance monitoring, strategies and tools for construction of applications from libraries of grid-aware components, and development of innovative new science and engineering applications that can exploit these new technologies to run effectively in grid environments.

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As machines and programs have become more complex, the process of programming applications that can exploit the power of high-performance systems has become more difficult and correspondingly more labor-intensive. This has substantially widened the software gap the discrepancy between the need for new software and the aggregate capacity of the workforce to produce it. This problem has been compounded by the slow growth of programming productivity, especially for high-performance programs, over the past two decades. One way to bridge this gap is to make it possible for end users to develop programs in high-level domain-specific programming systems. In the past, a major impediment to the acceptance of such systems has been the poor performance of the resulting applications. To address this problem, we are developing a new compiler-based infrastructure, called TeleGen, that will make it practical to construct efficient domain-specific high-level languages from annotated component libraries. We call these languages telescoping languages, because they can be nested within one another. For programs written in telescoping languages, high performance and reasonable compilation times can be achieved by exhaustively analyzing the component libraries in advance to produce a language processor that recognizes and optimizes library operations as primitives in the language. The key to making this strategy practical is to keep compile times low by generating a custom compiler with extensive built-in knowledge of the underlying libraries. The goal is to achieve compile times that are linearly proportional to the size of the program presented by the user, rather than to the aggregate size of that program plus the base libraries.2001 Elsevier Science