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This paper describes a methodology that provides detailed predictive performance information throughout the software design and implementation cycles. It is struc-tured around a hierarchy of performance models that describe the computing system in terms of its software, parallelization, and hardware components. The methodology is illustrated with an initial(More)
Workload and resource management are essential functionalities in the software infrastructure for grid computing. The management and scheduling of dynamic grid resources in a scalable way requires new technologies to implement a next generation intelligent grid environment. This work demonstrates that AI technologies can be utilised to achieve effective(More)
This paper addresses workload allocation techniques for two types of sequential jobs that might be found in multicluster systems, namely, non-real-time jobs and soft real-time jobs. Two workload allocation strategies, the optimized mean response time (ORT) and the optimized mean miss rate (OMR), are developed by establishing and numerically solving two(More)
Before an application modelled as a directed acyclic graph (DAG) is executed on a heterogeneous system, a DAG mapping policy is often enacted. After mapping, the tasks (in the DAG-based application) to be executed at each computational resource are determined. The tasks are then sent to the corresponding resources, where they are orchestrated in the(More)
There is a wide range of models being developed for the performance evaluation of parallel and distributed systems. This has become an important area of research especially with the development of dynamic processing capabilities promised with Computational GRIDs [3]. A performance modelling approach described in this paper is based on a layered framework of(More)
Performance prediction is set to play a significant role in supportive middleware that is designed to manage workload on parallel and distributed computing systems. This middleware underpins the discovery of available resources, the identification of a task's requirements and the match-making, scheduling and staging that follow. This paper documents two(More)
Grid middleware development has advanced rapidly over the past few years to support component-based programming models and service-orientated architectures. This is most evident with the forthcoming release of the Globus toolkit (GT4) which represents a convergence of concepts (and standards) from the web services community. Grid applications are(More)
There is a wide range of performance models being developed for the performance evaluation of parallel and distributed systems. A performance modelling approach described in this paper is based on a layered framework of the PACE methodology. With an initial implementation system, the model described by a performance specification language, CHIP³S, can(More)
Resource management constitutes an important infrastructural component of a computational grid environment. The aim of grid resource management is to efficiently schedule applications over the available resources provided by the supporting grid architecture. Such goals within the high performance community rely, in part, on accurate performance prediction(More)
There is a wide range of performance models being developed for the performance evaluation of parallel and distributed systems. A performance modelling approach described in this paper is based on a layered framework of the PACE methodology. With an initial implementation system, the model described by a performance specification language, CHIP³S, can(More)