The Computational Grid is a promising platform for the efficient execution of parameter sweep applications over large parameter spaces. To achieve performance on the Grid, such applications must be scheduled so that shared data files are strategically placed to maximize reuse, 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 of Grid middleware that 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...

Ensembles of distributed, heterogeneous resources, also known as Computational Grids are emerging 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 dynamic, heterogeneous, multi-user Grid environments. In this paper, we discuss the AppLeS project and outline our results.

The Computational Grid is a promising platform for the deployment of various high-performance computing applications. A number of projects have addressed the idea of software as a service on the network. These systems usually implement client-server architectures with many servers running on distributed Grid resources and have commonly been referred to as Network-enabled servers (NES). An important question is that of scheduling in this multi-client multi-server scenario. Note that in this context most requests are computationally intensive as they are generated by high-performance computing applications. The Bricks simulation framework has been developed and extensively used to evaluate scheduling strategies for NES systems. In this paper we first present recent developments and extensions to the Bricks simulation models. We discuss a deadline scheduling strategy that is appropriate for the multi-client multi-server case, and augment it with “Load Correction” and “Fallback ” mechanisms which could improve the performance of the algorithm. We then give Bricks simulation results. The results show that future NES systems should use deadline-scheduling with multiple fallbacks and it is possible to allow users to make a trade-off between failure-rate and cost by adjusting the level of conservatism of deadlinescheduling algorithms.

The Computational Grid [1] is a promising platform for running large scale scientic applications. It provides a base software infrastructure that allows for the development of \middleware" aimed at deploying applications on Grid resources. The NetworkEnabled Server (NES) paradigm is a good candidate as a viable Grid middleware that oers a simple yet powerful programming model (RPC-style programming for the Grid). This paradigm is amenable to many large-scale applications and especially to scienti c simulations. This paper builds on the experience acquired while building two well-known NES systems (Ninf [2] and NetSolve [3]). Our goal is to clarify major NES design issues as well as to dene a common set of services and concepts that are necessary for implementing and deploying NES systems on the Computational Grid. This paper also describes current work with scientic and engineering simulations that are enabled by NES systems in the Grid context.