In this paper, a simulation model for incorporation within a performance-oriented parallel software development environment is presented. This development environment is composed of a graphical design tool, a simulation facility, and a visualisation tool. Simulation allows parallel program performance to be predicted and design alternatives to be compared. The target parallel system models a virtual machine composed of a cluster of workstations interconnected by a local area network. The simulation model architecture is modular and extensible which allows re-configuration of the platform. The model description and the validation experiments which have been conducted to assess the correctness and the accuracy of the model are also presented. 1 Introduction The key obstacle to the widespread adoption of parallel computing is the difficulty in program development. Firstly, an application has to be decomposed into parallel objects (processes, or tasks) according to the computational model ...

Computer simulation is a fundamental discipline for studying complex systems. Like any other discipline, simulation must grow and be fine-tuned so that it maintains its position as the base methodology for doing computational science and constructing digital worlds. We discuss ten areas outside of simulation and demonstrate growth by identifying relationships between simulation and each of the areas. We outline each field by describing it briefly and then specifying outstanding issues which remain to be resolved. We have found that we are better able to characterize basic simulation methodology by integrating and extending simulation within the context of other fields. INTRODUCTION The field of computer simulation is approximately forty years old, and is still vibrant and growing. As technology develops faster hardware, old forms of simulation are made faster, and new varieties of simulation emerge through an extension process. Extending the core simulation knowledge base involves tak...

In this paper we present a method for translating the synchronisation behaviour of a process oriented discrete event simulation language into a process algebra. Such translations serve two purposes. The first exploits the formal structure of the target process algebraic representations to provide proofs of properties of the source system (such as deadlock freedom, fairness, liveness, ...) which can be very difficult to establish by simulation experiment. The second exploits the denotational semantics to better understand the language constructs as abstract entities and to reason about simulation models. Here we give the intuition and present the basic mechanisms using the ßDemos simulation language and the CCS and SCCS process algebras. The analysis of the synchronisations of full Demos is treated in a companion paper.

. In this paper, a simulation model for incorporation within a performance-oriented parallel software development environment is presented. This development environment is composed of a graphical design tool, a simulation facility, and a visualisation tool. Simulation allows a parallel program performance to be predicted and design alternatives to be compared. The target parallel system models a virtual machine composed of a cluster of workstations interconnected by a local area network. The simulation model architecture is modular and extensible which allows the re-configuration of the platform. The model description and the validation experiments which have been conducted to assess the correctness and the accuracy of the model are also presented. 1 Introduction The key obstacle to the widespread adoption of parallel computing is the difficulty in program development. Firstly, an application has to be decomposed into parallel objects (processes, or tasks) according to the computation...

Recent advances in logics for reasoning about resources provide a new approach to compositional reasoning in interacting systems. We present a calculus of resources and processes, based on a development of Milner's synchronous calculus of communication systems, SCCS, that uses an explicit model of resource. Our calculus models the co-evolution of resources and processes with synchronization constrained by the availability of resources. We provide a logical characterization, analogous to Hennessy-Milner logic's characterization of bisimulation in CCS, of bisimulation between resource processes which is compositional in the concurrent and local structure of systems.

... often, models are required to be executable, as a simulation, on a computer. In this paper, we present some contributions to the process-theoretic and logical foundations of discrete-event modelling with resources and processes. We present a process calculus with an explicit representation of resources in which processes and resources co-evolve. The calculus is closely connected to a logic that may be used as a specification language for properties of models. The logic is strong enough to allow requirements that a system has certain structure; for example, that it is a parallel composite of subsystems. This work consolidates, extends, and improves upon aspects of earlier work of ours in this area. An extended example, consisting of a semantics for a simple parallel programming language, indicates a connection with separating logics for concurrency.

We discuss a new model for the analysis and simulation of stochastic systems which we call stochastic automata. Basically, they are a combination of the timed automata model and generalised semi-markovian processes (GSMPs for short). We discuss their behaviour and we compare them to the GSMPs model. In addition, we define a stochastic process algebra that supports general distribution (both continuous and discrete). Its semantics is given in terms of stochastic automata. We show that stochastic automata can be expressed in terms of the process algebra. We discuss a concrete example and we finish by discussing our current work on the topic and possible future directions. 1 Introduction In the world of performance modelling, many models have been defined to analyse and simulate systems such as queuing networks, stochastic Petri-nets, or generalised semi-markovian processes. It has been argued many times that, in these kind of models, the difficulty of the design and modelling of a syste...

Experience of practical systems modelling suggests that the key conceptual components of a model of a system are processes, resources, locations, and environment. In recent work, we have given a process-theoretic account of this view in which resources as well as processes are first-class citizens. This process calculus, SCRP, captures the structural aspects of the semantics of the Demos2k modelling tool. Demos2k represents environment stochastically using a wide range of probability distributions and queue-like data structures. Associated with SCRP is a (bunched) modal logic, MBI, which combines the usual additive connectives of Hennessy-Milner logic with their multiplicative counterparts. In this paper, we complete our conceptual framework by adding to SCRP and MBI an account of a notion of location that is simple, yet sufficiently expressive to capture naturally a wide range of forms of location, both spatial and logical. We also provide a description of an extension of the Demos2k tool to incorporate this notion of location. 1

Simulation modelling is an important tool for exploring and reasoning about complex systems. Many supporting languages are available. Commonly occurring features of these languages are constructs capturing concepts such as process, resource, and location. We describe a mathematical framework that supports a modelling idiom based on these core concepts, and which adopts stochastic methods for representing the environments within which systems exist. We explain how this framework can be used to give a semantics to a simulation modelling language, Core Gnosis, that includes basic constructs for process, resource, and location. We include a brief discussion of a logic for reasoning about models that is compositional with respect to their structure. Our mathematical analysis of systems in terms of process, resource, location, and stochastic environment, together with a language that captures these concepts quite directly, yields an efficient and robust modelling framework within which natural mathematical reasoning about systems is captured.

We describe a programme of research in resource semantics, concurrency theory, bunched logic, and stochastic processes, as applied to mathematical systems modelling. Motivated by a desire for structurally and semantically rigorous discrete event modelling tools, applicable to enterprise-scale as well as componentscale systems, we introduce a new approach to compositional reasoning based on a development of SCCS with an explicit model of resource. Our calculus models the co-evolution of resources and processes with synchronization constrained by the availability of resources. We provide a simple denotational semantics as a parametrization of Abramsky’s synchronization trees semantics for SCCS. We also provide a logical characterization, analogous to Hennessy-Milner logic’s characterization of bisimulation in CCS, of bisimulation between resource processes which is compositional in the concurrent and local structure of systems. We discuss applications to ideas such as location and access control.