TimeBench/SRVN is a prototype toolset for computer-aided design and performance analysis of software, with an emphasis on distributed client-server systems. The performance behaviour of such systems may defy intuition because it involves factors in the software design (such as the partitioning of the functionality and the frequency with which requests will be made to each server) and in the configuration of the distributed system (including replication of services, the distribution of data, and the speed of network access). The novelty of the tool consists in providing support both for developing design specifications and also for performance analysis. The integrated approach avoids the semantic gap between a designer's domain and the performance modeling domain, and assists the designer to explore factors that impact the performance of a design. The performance models are based on the Stochastic Rendezvous Network (SRVN) formalism for client-server systems with synchronous service req...

Early performance estimates for a new software system aid the design process by providing feedback when design decisions can be easily revised. Unfortunately, constructing a performance model of a distributed and concurrent software system can require significant effort. An automated performance model generation technique is described that reduces the model building effort by providing: easy specification of performance experiments, empirical estimates for model parameters, automated model generation, and support for different types of models. A prototype is used to describe a software system, from which causal traces (angio traces) are recorded during execution. These traces are then processed into sequences of resource demands (workthreads), aggregated into system execution descriptions (workthread classes), and combined to generate a performance model. The technique can also be applied at other stages of the development process, including the redesign of existing software. Page ii...

. In the development of e#cient parallel applications, reliable performance predictions are essential. However, many performance modelling formalisms, such as queueing networks, are not directly suitable for modelling parallel applications, while for other formalisms the analysis is too expensive. We present a methodology for performance modelling of parallel processing systems #Glamis#, based on extended queueing networks, aiming to overcome these problems. The methodology yields reliable performance predictions for a class of parallel machines and programs at relatively low #polynomial time# analysis cost. Additional reductions of analysis cost are obtained by exploiting inherent replications in parallel systems. 1 Introduction Performance predictions of a parallel program running on a parallel machine can be of great importance in a number of situations. A #rst application is the decision which one from a range of parallel machines is most suitable for a given applicatio...

This report describes the results of preliminary research in the field of probabilistic performance modelling of parallel applications. The work was carried out as part of the ProcMod (Processor Modelling) sub-project of the parTool project. The ProcMod sub-project aims at the development of a performance modelling technique and associated tool support which, based on a generic machine modelling paradigm, predicts parallel application performance at different hierarchical levels. In this way, performance feedback is available at all modelling levels, enabling the use of performance information during all stages of the application development process. The application of this technique is twofold: on the one hand, performance can be optimised by means of feedback to the user (or parallelising compiler) for a given target machine (or machine class); on the other hand, a comparative analysis of target machine performance can be made given a parallel application (or application class). In an earlier report the emphasis was on the description of parallel computer architectures [18]. This report, on the other hand, concentrates on the performance modelling and prediction techniques