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 value-tag 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 discrete-event systems. I.

This paper surveys the design of embedded computer systems, which use software running on programmable computers to im-plement system functions. Creating an embedded computer system which meets its performance, cost, and design time goals is a hardware-software co-design problewhe design of the hard-ware and software components influence each other. This paper emphasizes a historical approach to show the relationships be-tween well-understood design problems and the as-yet unsolved problems in co-design. We describe the relationship between hard-ware and sofhvare architecture in the early stages of embedded system design. We describe analysis techniques for hardware and software relevant to the architectural choices required for hard-ware-software co-design. We also describe design and synthesis techniques for co-design and related problems.

Proceedings of the IEEE January 2003 The paper describes a model-integrated approach for embedded software development that is based on domain-specific, multiple view models used in all phases of the development process. Models explicitly represent the embedded software and the environment it operates in, and capture the requirements and the design of the application, simultaneously. Models are descriptive, in the sense that they allow the formal analysis, verification and validation of the embedded system at design time. Models are also generative, in the sense that they carry enough information for automatically generating embedded systems using the techniques of program generators. Because of the widely varying nature of embedded systems, a single modeling language may not be suitable for all domains, thus modeling languages are often domain-specific. To decrease the cost of defining and integrating domain-specific modeling languages and corresponding analysis and synthesis tools, the model-integrated approach is applied in a metamodeling architecture, where formal models of domain-specific modeling languages – called metamodels – play a key role in customizing and connecting components of tool chains. The paper will discuss the principles and techniques of model-integrated embedded software development in detail, as well as the capabilities of the tools supporting the process. Examples in terms of real systems will be given that illustrate how the model-integrated approach addresses the physical nature, the assurance issues, and the dynamic structure of embedded software.

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This paper addresses the design of reactive real-time embedded systems. Such systems are often heterogeneous in implementation technologies and design styles, for example by combining hardware ASICs with embedded software. The concurrent design process for such embedded systems involves solving the specification, validation, and synthesis problems. We review the variety of approaches to these problems that have been taken.

Abstract — We present a programming interface called YAPI to model signal processing applications as process networks. The purpose of YAPI is to enable the reuse of signal processing applications and the mapping of signal processing applications onto heterogeneous systems that contain hardware and software components. To this end, YAPI separates the concerns of the application programmer, who determines the functionality of the system, and the system designer, who determines the implementation of the functionality. The proposed model of computation extends the existing model of Kahn process networks with channel selection to support non-deterministic events. We provide an efficient implementation of YAPI in the form of a C++ run-time library to execute the applications on a workstation. Subsequently, the applications are used by the system designer as input for mapping and performance analysis in the design of complex signal processing systems. We evaluate this methodology on the design of a digital video broadcast system-on-chip.

Modern embedded computing systems tend to be heterogeneous in the sense of being composed of subsystems with very different characteristics, which communicate and interact in a variety of ways---synchronous or asynchronous, buffered or unbuffered, etc. Obviously, when designing such systems, a modeling language needs to reflect this heterogeneity. Today's modeling environments usually offer a variant of what we call amorphous heterogeneity to address this problem. This paper argues that modeling systems in this manner leads to unexpected and hard-to-analyze interactions between the communication mechanisms and proposes a more structured approach to heterogeneity, called hierarchical heterogeneity to solve this problem. It proposes a model structure and semantic framework that support this form of heterogeneity, and discusses the issues arising from heterogeneous component interaction and the desire for component reuse. It introduces the notion of domain polymorphism as a way to address these issues.

Ptolemy is an environment for simulation, prototyping, and software synthesis for heterogeneous systems. It uses modern object-oriented software technology (in C++) to model each subsystem in a natural and efficient manner, and to integrate these subsystems into a whole. The objectives of Ptolemy encompass practically all aspects of designing signal processing and communications systems, ranging from algorithms and communication strategies, through simulation, hardware and software design, parallel computing, and generation of real-time prototypes. In this paper we will introduce the software synthesis aspects of the Ptolemy system. The environment presented here is both modular and extensible. Ptolemy allows the user to choose among various single- or multiple-processor schedulers. 1.0 Introduction Practical signal processing systems today are rarely implemented without software or firmware, even at the ASIC level. Programmable DSPs, in particular, form the heart of many implementati...

We present a methodology for the exploration of signal processing architectures at the system level. The methodology, named Spade, provides a means to quickly build models of architectures at an abstract level, to easily map applications, modeled as Kahn Process Networks, onto these architecture models, and to analyze the performance of the resulting system by simulation. The methodology distinguishes between applications and architectures, and uses a trace-driven simulation technique for co-simulation of application models and architecture models. As a consequence, architecture models need not be functionally complete to be used for performance analysis while data dependent behavior is still handled correctly. We have used the methodology for the exploration of architectures and mappings of an MPEG-2 video decoder application.

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