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A Framework for Comparing Models of Computation
 IEEE Transactions on ComputerAided Design of Integrated Circuits and Systems
, 1998
"... Abstract—We give a denotational framework (a “meta model”) within which certain properties of models of computation can be compared. It describes concurrent processes in general terms as sets of possible behaviors. A process is determinate if, given the constraints imposed by the inputs, there are e ..."
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Cited by 245 (54 self)
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Abstract—We give a denotational framework (a “meta model”) within which certain properties of models of computation can be compared. It describes concurrent processes in general terms as sets of possible behaviors. A process is determinate if, given the constraints imposed by the inputs, there are exactly one or exactly zero behaviors. Compositions of processes are processes with behaviors in the intersection of the behaviors of the component processes. The interaction between processes is through signals, which are collections of events. Each event is a valuetag pair, where the tags can come from a partially ordered or totally ordered set. Timed models are where the set of tags is totally ordered. Synchronous events share the same tag, and synchronous signals contain events with the same set of tags. Synchronous processes have only synchronous signals as behaviors. Strict causality (in timed tag systems) and continuity (in untimed tag systems) ensure determinacy under certain technical conditions. The framework is used to compare certain essential features of various models of computation, including Kahn process networks, dataflow, sequential processes, concurrent sequential processes with rendezvous, Petri nets, and discreteevent systems. I.
Comparing Models of Computation
 IN PROC. ICCAD
, 1996
"... We give a denotational framework (a "meta model") within which certain properties of models of computation can be understood and compared. It describes concurrent processes as sets of possible behaviors. Compositions of processes are given as intersections of their behaviors. The interaction between ..."
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Cited by 28 (1 self)
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We give a denotational framework (a "meta model") within which certain properties of models of computation can be understood and compared. It describes concurrent processes as sets of possible behaviors. Compositions of processes are given as intersections of their behaviors. The interaction between processes is through signals, which are collections of events. Each event is a valuetag pair, where the tags can come from a partially ordered or totally ordered set. Timed models are where the set of tags is totally ordered. Synchronous events share the same tag, and synchronous signals contain events with the same set of tags. Synchronous systems contain synchronous signals. Strict causality (in timed systems) and continuity (in untimed systems) ensure determinacy under certain technical conditions. The framework is used to compare certain essential features of various models of computation, including Kahn process networks, dataflow, sequential processes, concurrent sequential processes with rendezvous, Petri nets, and discreteevent systems.
Modeling Timed Concurrent Systems
 in CONCUR 2006  Concurrency Theory
, 2006
"... Abstract. Timed concurrent systems are widely used in concurrent and distributed realtime software, modeling of hybrid systems, design of hardware systems (using hardware description languages), discreteevent simulation, and modeling of communication networks. They consist of concurrent components ..."
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Cited by 16 (13 self)
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Abstract. Timed concurrent systems are widely used in concurrent and distributed realtime software, modeling of hybrid systems, design of hardware systems (using hardware description languages), discreteevent simulation, and modeling of communication networks. They consist of concurrent components that communicate using timed signals, that is, sets of (semantically) timestamped events. The denotational semantics of such systems is traditionally formulated in a metric space, wherein causal components are modeled as contracting functions. We show that this formulation excessively restricts the models of time that can be used. In particular, it cannot handle superdense time, commonly used in hardware description languages and hybrid systems modeling, finite time lines, and time with no origin. Moreover, if we admit continuoustime and mixed signals (essential for hybrid systems modeling) or certain Zeno signals, then causality is no longer equivalent to its formalization in terms of contracting functions. In this paper, we offer an alternative semantic framework using a generalized ultrametric that overcomes these limitations. 1
Causality Interfaces and Compositional Causality Analysis
 FIT 2005 PRELIMINARY VERSION
, 2005
"... In this paper, we consider concurrent models of computation where ”actors” (components that are in charge of their own actions) communicate by exchanging messages. The interfaces of actors principally consist of “ports,” which mediate the exchange of messages. Actororiented architectures contrast w ..."
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Cited by 13 (10 self)
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In this paper, we consider concurrent models of computation where ”actors” (components that are in charge of their own actions) communicate by exchanging messages. The interfaces of actors principally consist of “ports,” which mediate the exchange of messages. Actororiented architectures contrast with and complement objectoriented models by emphasizing the exchange of data between concurrent components rather than transfer of control. Examples of such models of computation include the classical actor model, synchronous languages, dataflow models, and discreteevent models. Many of these models of computation benefit considerably from having access to causality information about the components. This paper augments the interfaces of such components to include such causality information. It shows how this causality information can be algebraically composed so that compositions of components acquire causality interfaces that are inferred from their components and the interconnections. We illustrate the use of these causality interfaces to statically analyze discreteevent models for uniqueness of behaviors, synchronous models for causality loops, and dataflow models for schedulability.
A Constructive FixedPoint Theorem and the Feedback Semantics of Timed Systems
 in Workshop on Discrete Event Systems (WODES), Ann Arbor
, 2006
"... Abstract — Deterministic timed systems can be modeled as fixed point problems [15], [16], [4]. In particular, any connected network of timed systems can be modeled as a single system with feedback, and the system behavior is the fixed point of the corresponding system equation, when it exists. For d ..."
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Cited by 9 (8 self)
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Abstract — Deterministic timed systems can be modeled as fixed point problems [15], [16], [4]. In particular, any connected network of timed systems can be modeled as a single system with feedback, and the system behavior is the fixed point of the corresponding system equation, when it exists. For deltacausal systems, we can use the Cantor metric to measure the distance between signals and the Banach fixedpoint theorem to prove the existence and uniqueness of a system behavior. Moreover, the Banach fixedpoint theorem is constructive: it provides a method to construct the unique fixed point through iteration. In this paper, we extend this result to systems modeled with the superdense model of time [7], [8] used in hybrid systems. We call the systems we consider eventually deltacausal, a strict generalization of deltacausal in which multiple events may be generated on a signal in zero time. With this model of time, we can use a generalized ultrametric [14] instead of a metric to model the distance between signals. The existence and uniqueness of behaviors for such systems comes from the fixedpoint theorem of [13], but this theorem gives no constructive method to compute the fixed point. This leads us to define petrics, a generalization of metrics, which we use to generalize the Banach fixedpoint theorem to provide a constructive fixedpoint theorem. This new fixedpoint theorem allows us to construct the unique behavior of eventually deltacausal systems. I.
Modal Models in Ptolemy
, 2010
"... Ptolemy is an opensource and extensible modeling and simulation framework. It offers heterogeneous modeling capabilities by allowing different models of computation to be composed hierarchically in an arbitrary fashion. This paper describes modal models, which allow to hierarchically compose finite ..."
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Cited by 4 (3 self)
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Ptolemy is an opensource and extensible modeling and simulation framework. It offers heterogeneous modeling capabilities by allowing different models of computation to be composed hierarchically in an arbitrary fashion. This paper describes modal models, which allow to hierarchically compose finitestate machines with other models of computation, both untimed and timed. The semantics of modal models in Ptolemy are defined in a modular manner.