No abstract

Ensembles of distributed, heterogeneous resources, also known as Computational Grids, have emerged as critical platforms for high-performance and resource-intensive applications. Such platforms provide the potential for applications to aggregate enormous bandwidth, computational power, memory, secondary storage, and other resources during a single execution. However, achieving this performance potential in dynamic, heterogeneous environments is challenging. Recent experience with distributed applications indicates that adaptivity is fundamental to achieving application performance in dynamic grid environments. The AppLeS (Application Level Scheduling) project provides a methodology, application software, and software environments for adaptively scheduling and deploying applications in heterogeneous, multiuser grid environments. In this article, we discuss the AppLeS project and outline our findings.

Heterogeneous networks are increasingly being used as platforms for resource-intensive distributed parallel applications. A critical contributor to the performance of such applications is the scheduling of constituent application tasks on the network. Since often the distributed resources cannot be brought under the control of a single global scheduler, the application mu s t b e s c heduled by the user. To obtain the best performance, the user must take i n to account both application-speci c and dynamic system information in developing a schedule which meets his or her performance criteria.In this paper, we de ne a set of principles underlying application-level scheduling and describe our work-in-progress building AppLeS (application-level scheduling) agents. We illustrate the application-level scheduling approach with a detailed description and results for a distributed 2D Jacobi application on two production heterogeneous platforms.

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.

The Computational Grid is a promising platform for the efficient execution ofparameter sweep applicationsover large parameter spaces. To achieve performance on the Grid, such applications must be scheduled so that shared data files are strategically placed to maximize re-use, and so that the application execution can adapt to the deliverable performance potential of target heterogeneous, distributed and shared resources. Parameter sweep applications are an important class of applications and would greatly benefit from the development ofGrid middlewarethat embeds a scheduler for performance and targets Grid resources transparently. In this paper we describe a user-level Grid middleware project, the AppLeS Parameter Sweep Template (APST), that uses application-level scheduling techniques [1] and various Grid technologies to allow the efficient deployment of parameter sweep applications over the Grid. We discuss several possible scheduling algorithms and detail our software design. We then describe our current implementation of APST using systems like Globus [2], NetSolve [3] and the Network Weather Service [4], and present experimental results.