Industrial stochastic simulations on a European meta-computer

Meacham, Ken; Floros, N; Surridge, Mike

doi:10.1007/bfb0057975

Cited by 8 publications

(9 citation statements)

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“…Deviations from the designed planarity affect the performance of the antennae, and in extreme cases make communication with the satellite impossible, which is obviously critical to satellite operation. The analysis was conducted over the Internet, using a pool of over 100 non-dedicated workstations across eight sites, some of which were secure, one of the first large-scale, industrial meta-applications to be carried out over the Internet in Europe [2].…”

Section: Applications Of the Meta-application Managermentioning

confidence: 99%

“…The value of the PAC's approach to meta-application management was demonstrated through the PROMEN-VIR Internet experiment, outlined in Section 2.2 and described in [2]. In this experiment, a typical probabilistic engineering problem from the space industry (developed by CEIT and CASA) was analysed, by running a large stochastic Monte Carlo simulation.…”

Section: Transparent Access To Meta-computersmentioning

confidence: 99%

“…Many lessons were learned from this experience relating to security, Internet reliability and solver version control, which are described in [2]. In the context of this paper, the most interesting lesson related to machine availability: of the 102 machines provided, only 79 were actually used during the experiment.…”

Section: Transparent Access To Meta-computersmentioning

confidence: 99%

“…The meta-application management software developed by PAC has been used to run some large-scale applications, including some tests running over the Internet across several secure sites, the results of which are reported elsewhere [2]. The purpose of this paper is to expand on the performance modelling requirements for 'predictive resource management', to show how these have been addressed for a number of application software packages, and to present some enhancements which are the subject of ongoing research at the PAC.…”

Section: Introductionmentioning

confidence: 99%

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Predictive resource management for meta-applications

Floros

Hey

Meacham

et al. 1999

Future Generation Computer Systems

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This paper defines meta-applications as large, related collections of computational tasks, designed to achieve a specific overall result, running on a (possibly geographically) distributed, non-dedicated meta-computing platform. To carry out such applications in an industrial context, one requires resource management and job scheduling facilities (including capacity planning), to ensure that the application is feasible using the available resources, that each component job will be sent to an appropriate resource, and that everything will finish before the computing resources are needed for other purposes.This requirement has been addressed by the PAC in three major European collaborative projects: PROMENVIR, TOOL-SHED and HPC-VAO, leading to the creation of job scheduling software, in which scheduling is brought together with performance modelling of applications and systems, to provide meta-applications management facilities. This software is described, focusing on the performance modelling approach which was needed to support it.Early results from this approach are discussed, raising some new issues in performance modelling and software deployment for meta-applications. An indication is given about ongoing work at the PAC designed to overcome current limitations and address these outstanding issues.

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Section: Applications Of the Meta-application Managermentioning

confidence: 99%

Section: Transparent Access To Meta-computersmentioning

confidence: 99%

Section: Transparent Access To Meta-computersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Predictive resource management for meta-applications

Floros

Hey

Meacham

et al. 1999

Future Generation Computer Systems

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“…Support for execution in PSE's is normally understood in the context of distributed systems and is concerned with resource management and the way that the computational components are scheduled. Systems that emphasize this aspect include well known schedulers such as PBS, and resource management systems such as INTREPID [5,6].…”

Section: Introductionmentioning

confidence: 99%

A Problem Solving Environment Based on CORBA

Lancaster

2001

Scientific Programming

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We have investigated aspects of the design of Problem Solving Environments (PSE) by constructing a prototype using CORBA as middleware. The two issues we are mainly concerned with are the use of non-trivial (containing more than just a start() method) CORBA interfaces for the computational components, and the provision of interactivity using the same mechanisms used for flow control. After describing the design decisions that allow us to investigate these issues, and contrasting them with alternatives, we describe the architecture of the prototype and its use in the context of a study of photonic materials. We argue that having several methods on a component interface can be used to mitigate performance problems that may arise when trying to solve problems in PSE's based on small components. We describe how our mechanism allows a high degree of computational steering over all components.

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The role of performance engineering techniques in the context of the Grid

Hey

Papay

Surridge³

2005

Concurrency and Computation

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SUMMARYPerformance engineering can be described as a collection of techniques and methodologies whose aim is to provide reliable prediction, measurement and validation of the performance of applications on a variety of computing platforms. This paper reviews techniques for performance estimation and performance engineering developed at the University of Southampton and presents application case studies in task scheduling for engineering meta-applications, and capacity engineering for a financial transaction processing system. These show that it is important to describe performance in terms of a resource model, and that the choice of models may have to trade accuracy for utility in addressing the operational issues. We then present work from the on-going EU funded Grid project GRIA, and show how lessons learned from the earlier work have been applied to support a viable business model for Grid service delivery to a specified quality of service level. The key in this case is to accept the limitations of performance estimation methods, and design business models that take these limitations into account rather than attempting to provide hard guarantees over performance. We conclude by identifying some of the key lessons learned in the course of our work over many years and suggest possible directions for future investigations. Copyright

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Industrial stochastic simulations on a European meta-computer

Cited by 8 publications

References 1 publication

Predictive resource management for meta-applications

Predictive resource management for meta-applications

A Problem Solving Environment Based on CORBA

The role of performance engineering techniques in the context of the Grid

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